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Masuo A, Kubota J, Yokoyama K, Karaki K, Yuasa H, Ito Y, Takeo J, Sakuma T, Kato S. Machine learning-based screening for outpatients with dementia using drawing features from the clock drawing test. Clin Neuropsychol 2024:1-12. [PMID: 39435954 DOI: 10.1080/13854046.2024.2413555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 10/03/2024] [Indexed: 10/23/2024]
Abstract
Background and Objectives: In geriatrics and dementia care, early diagnosis is crucial. We developed a dementia screening model using drawing features from clock drawing tests (CDT) and investigated the features contributing to the discrimination of dementia and its screening performance. Methods: This study included 129 older adults attending a dementia outpatient clinic. We obtained information on the diagnosis of dementia and CDT data from medical records and quantified 12 types of drawing features according to the Freedman scoring system. Based on the dementia diagnosis information, participants were assigned to two groups: 58 in the dementia diagnosis group and 71 in the non-diagnosis group. Using Boruta, an iterative feature selection algorithm, and a support vector machine, a machine learning method, we analyzed the drawing features contributing to dementia discrimination and evaluated discrimination performance. Results: Five types of drawing features were selected as contributors to discrimination, including "numbers in the correct position," "minute target number indicated," and "hand in correct proportion." These features exhibited a discriminating sensitivity of 0.74 ± 0.16 and specificity of 0.74 ± 0.18 for detecting dementia. Conclusion: This study demonstrated a method for identifying individuals likely to be diagnosed with dementia among patients attending a dementia outpatient clinic using drawing features. The knowledge of drawing features contributing to dementia differentiation may assist healthcare practitioners in clinical reasoning and provide novel insights for clinical practice. In the future, we plan to develop a primary screening for dementia based on machine learning using CDT.
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Affiliation(s)
- Akira Masuo
- Seijoh University, Aichi, Japan
- Graduate School of Engineering, Nagoya Institute of Technology, Aichi, Japan
- Nagoya College of Medical Health and Sports, Aichi, Japan
| | | | | | | | | | - Yuki Ito
- Graduate School of Engineering, Nagoya Institute of Technology, Aichi, Japan
| | - Jun Takeo
- Graduate School of Engineering, Nagoya Institute of Technology, Aichi, Japan
- Nagoya Bunri University, Aichi, Japan
| | - Takuto Sakuma
- Graduate School of Engineering, Nagoya Institute of Technology, Aichi, Japan
| | - Shohei Kato
- Graduate School of Engineering, Nagoya Institute of Technology, Aichi, Japan
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2
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Kamatham PT, Shukla R, Khatri DK, Vora LK. Pathogenesis, diagnostics, and therapeutics for Alzheimer's disease: Breaking the memory barrier. Ageing Res Rev 2024; 101:102481. [PMID: 39236855 DOI: 10.1016/j.arr.2024.102481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 06/28/2024] [Accepted: 08/29/2024] [Indexed: 09/07/2024]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia and accounts for 60-70 % of all cases. It affects millions of people worldwide. AD poses a substantial economic burden on societies and healthcare systems. AD is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. As the prevalence of AD continues to increase, understanding its pathogenesis, improving diagnostic methods, and developing effective therapeutics have become paramount. This comprehensive review delves into the intricate mechanisms underlying AD, explores the current state of diagnostic techniques, and examines emerging therapeutic strategies. By revealing the complexities of AD, this review aims to contribute to the growing body of knowledge surrounding this devastating disease.
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Affiliation(s)
- Pushpa Tryphena Kamatham
- Molecular and Cellular Neuroscience Laboratory, Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana 500037, India
| | - Rashi Shukla
- Molecular and Cellular Neuroscience Laboratory, Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana 500037, India
| | - Dharmendra Kumar Khatri
- Department of Pharmacology, Nims Institute of Pharmacy, Nims University Rajasthan, Jaipur, India.
| | - Lalitkumar K Vora
- School of Pharmacy, Medical Biology Centre, Queen's University Belfast, 97 Lisburn Road, Belfast, Northern Ireland BT9 7BL, UK.
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3
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Afrashteh F, Almasi-Dooghaee M, Kamyari N, Rajabi R, Baradaran HR. Is Montreal Cognitive Assessment a valuable test for the differentiation of Alzheimer's disease, frontotemporal dementia, dementia with Lewy body, and vascular dementia? Dement Neuropsychol 2024; 18:e20230124. [PMID: 39193467 PMCID: PMC11348881 DOI: 10.1590/1980-5764-dn-2023-0124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 04/20/2024] [Accepted: 05/06/2024] [Indexed: 08/29/2024] Open
Abstract
Dementia is one of the growing diseases in the world and has different types based on its definition. The Montreal Cognitive Assessment (MoCA) test has been employed to screen patients with dementia, cognitive impairment, and disruption of daily activities. Objective This study examined the diagnostic value of the total MoCA score and its subscores in differentiating Alzheimer's disease (AD), frontotemporal dementia (FTD), dementia with Lewy body (DLB), and vascular dementia (VaD). Methods A total of 241 patients (AD=110, FTD=90, DLB=28, and VaD=13) and 59 healthy persons, who were referred to a dementia clinic with memory impairment in Firoozgar Hospital, were included in this study. MoCA tests were performed in all patients and normal persons. Results By using the receiver operating characteristic (ROC) curve and measuring the area under the curve (AUC) for the total MoCA score in each group, AUC was 0.616, 0.681, 0.6117, and 0.583 for differentiating AD, FTD, DLB, and VaD patients, respectively. Among the groups, just the VaD group showed no significant usefulness in using the total MoCA score to differentiate it. To compare MoCA subscores, AD patients had higher scores in digit span, literal fluency, and abstraction but lower delayed recall scores compared with FTD patients. Conclusion The total MoCA score and its subscores could not differentiate people with different types of dementia in the setting of screening.
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Affiliation(s)
- Fatemeh Afrashteh
- Iran University of Medical Sciences, School of Medicine, Tehran, Iran
| | - Mostafa Almasi-Dooghaee
- Iran University of Medical Sciences, Department of Neurology, Firoozgar Clinical Research Development Center (FCRDC), Tehran, Iran
| | - Naser Kamyari
- Abadan University of Medical Sciences, Department of Biostatistics and Epidemiology, School of Health, Abadan, Iran
| | - Rayan Rajabi
- Iran University of Medical Sciences, School of Medicine, Tehran, Iran
| | - Hamid Reza Baradaran
- Iran University of Medical Sciences, Department of Epidemiology, School of Public Health, Tehran, Iran
- University of Aberdeen, Ageing Clinical and Experimental Research Team, Institute of Applied Health Sciences, Aberdeen, UK
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Mosquera-Heredia MI, Vidal OM, Morales LC, Silvera-Redondo C, Barceló E, Allegri R, Arcos-Burgos M, Vélez JI, Garavito-Galofre P. Long Non-Coding RNAs and Alzheimer's Disease: Towards Personalized Diagnosis. Int J Mol Sci 2024; 25:7641. [PMID: 39062884 PMCID: PMC11277322 DOI: 10.3390/ijms25147641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 07/06/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024] Open
Abstract
Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is the most common form of dementia. Currently, there is no single test that can diagnose AD, especially in understudied populations and developing countries. Instead, diagnosis is based on a combination of medical history, physical examination, cognitive testing, and brain imaging. Exosomes are extracellular nanovesicles, primarily composed of RNA, that participate in physiological processes related to AD pathogenesis such as cell proliferation, immune response, and neuronal and cardiovascular function. However, the identification and understanding of the potential role of long non-coding RNAs (lncRNAs) in AD diagnosis remain largely unexplored. Here, we clinically, cognitively, and genetically characterized a sample of 15 individuals diagnosed with AD (cases) and 15 controls from Barranquilla, Colombia. Advanced bioinformatics, analytics and Machine Learning (ML) techniques were used to identify lncRNAs differentially expressed between cases and controls. The expression of 28,909 lncRNAs was quantified. Of these, 18 were found to be differentially expressed and harbored in pivotal genes related to AD. Two lncRNAs, ENST00000608936 and ENST00000433747, show promise as diagnostic markers for AD, with ML models achieving > 95% sensitivity, specificity, and accuracy in both the training and testing datasets. These findings suggest that the expression profiles of lncRNAs could significantly contribute to advancing personalized AD diagnosis in this community, offering promising avenues for early detection and follow-up.
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Affiliation(s)
- Maria I. Mosquera-Heredia
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Oscar M. Vidal
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Luis C. Morales
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Carlos Silvera-Redondo
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Ernesto Barceló
- Instituto Colombiano de Neuropedagogía, Barranquilla 080020, Colombia;
- Department of Health Sciences, Universidad de La Costa, Barranquilla 080002, Colombia
- Grupo Internacional de Investigación Neuro-Conductual (GIINCO), Universidad de La Costa, Barranquilla 080002, Colombia
| | - Ricardo Allegri
- Institute for Neurological Research FLENI, Montañeses 2325, Buenos Aires C1428AQK, Argentina;
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellin 050010, Colombia;
| | - Jorge I. Vélez
- Department of Industrial Engineering, Universidad del Norte, Barranquilla 081007, Colombia
| | - Pilar Garavito-Galofre
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
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Mohamed Yusof NIS, Mohd Fauzi F. Nature's Toolbox for Alzheimer's Disease: A Review on the Potential of Natural Products as Alzheimer's Disease Drugs. Neurochem Int 2024; 176:105738. [PMID: 38616012 DOI: 10.1016/j.neuint.2024.105738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 03/18/2024] [Accepted: 04/06/2024] [Indexed: 04/16/2024]
Abstract
Numerous clinical trials involving natural products have been conducted to observe cognitive performances and biomarkers in Alzheimer's Disease (AD) patients. However, to date, no natural-based drugs have been approved by the FDA as treatments for AD. In this review, natural product-based compounds that were tested in clinical trials from 2011 to 2023, registered at www.clinicaltrials.gov were reviewed. Thirteen compounds, encompassing 7 different mechanisms of action were covered. Several observations were deduced, which are: i) several compounds showed cognitive improvement, but these improvements may not extend to AD, ii) compounds that are endogenous to the human body showed better outcomes, and iii) Docosahexaenoic acid (DHA) and cerebrolysin had the most potential as AD drugs among the 13 compounds. Based on the current findings, natural products may be more suitable as a supplement than AD drugs in most cases. However, the studies covered here were conducted in a relatively short amount of time, where compounds acting on AD pathways may take time to show any effect. Given the diverse pathways that these natural products are involved in, they may potentially produce synergistic effects that would be beneficial in treating AD. Additionally, natural products benefit from both physicochemical properties being in more favorable ranges and active transport playing a more significant role than it does for synthetic compounds.
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Affiliation(s)
| | - Fazlin Mohd Fauzi
- Faculty of Pharmacy, Universiti Teknologi MARA Selangor, Puncak Alam Campus, 42 300 Bandar Puncak Alam, Selangor, Malaysia; Center for Drug Discovery Research, Faculty of Pharmacy, Universiti Teknologi MARA Selangor, Puncak Alam Campus, 42 300 Bandar Puncak Alam, Selangor, Malaysia.
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6
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Plantinga L, Yazdany J, Bowling CB, Dunlop-Thomas C, Hoge C, Pearce BD, Lim SS, Katz P. Comparison of cognitive performance measures in individuals with systemic lupus erythematosus. Lupus Sci Med 2024; 11:e001151. [PMID: 38627039 PMCID: PMC11029380 DOI: 10.1136/lupus-2024-001151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/09/2024] [Indexed: 04/19/2024]
Abstract
OBJECTIVE Cognitive impairment is a common complaint in SLE, but approaches to measuring cognitive performance objectively vary. Leveraging data collected in a population-based cohort of individuals with validated SLE, we compared performance and potential impairment across multiple measures of cognition. METHODS During a single study visit (October 2019-May 2022), times to complete the Trail Making Test B (TMTB; N=423) were recorded; potential impairment was defined as an age-corrected and education-corrected T-score <35 (>1.5 SD longer than the normative time). A clock drawing assessment (CLOX; N=435) with two parts (free clock draw (CLOX1) and copy (CLOX2)) was also performed (score range: 0-15; higher scores=better performance); potential impairment was defined as CLOX1 <10 or CLOX2 <12. Fluid cognition (N=199; in-person visits only) was measured via the National Institutes of Health (NIH) Toolbox Fluid Cognition Battery and expressed as age-corrected standard scores; potential impairment was defined by a score <77.5 (>1.5 SD lower the normative score). RESULTS Participants (mean age 46 years; 92% female; 82% black) had a median (IQR) TMTB time of 96 (76-130) s; median (IQR) CLOX1 and CLOX2 scores of 12 (10-13) and 14 (13-15); and a mean (SD) fluid cognition standard score of 87.2 (15.6). TMTB time and fluid cognition score (ρ=-0.53, p<0.001) were the most highly intercorrelated measures. Overall, 65%, 55% and 28% were potentially impaired by the TMTB test, CLOX task and NIH Toolbox Fluid Cognition Battery, respectively. While there was overlap in potential impairment between TMTB and CLOX, more than half (58%) had impairment by only one of these assessments. Few (2%) had impairment in fluid cognition only. CONCLUSION The TMTB, CLOX and NIH Fluid Cognition Battery each provided unique and potentially important information about cognitive performance in our SLE cohort. Future studies are needed to validate these measures in SLE and explore interventions that maintain or improve cognitive performance in this population.
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Affiliation(s)
- Laura Plantinga
- Department of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Jinoos Yazdany
- Department of Medicine, University of California San Francisco, San Francisco, California, USA
| | - C Barrett Bowling
- Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
- Department of Medicine, Duke University, Durham, North Carolina, USA
| | | | - Courtney Hoge
- Department of Medicine, Emory University, Atlanta, Georgia, USA
| | - Brad D Pearce
- Department of Epidemiology, Emory University, Atlanta, Georgia, USA
| | - S Sam Lim
- Department of Medicine, Emory University, Atlanta, Georgia, USA
- Department of Epidemiology, Emory University, Atlanta, Georgia, USA
| | - Patricia Katz
- Department of Medicine, University of California San Francisco, San Francisco, California, USA
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7
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Donat-Vargas C, Mico V, San-Cristobal R, Martínez-González MÁ, Salas-Salvadó J, Corella D, Fitó M, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Damas-Fuentes M, Lapetra J, Serra-Majem L, Bueno-Cavanillas A, Tur JA, Cinza-Sanjurjo S, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Causso C, Ros E, Toledo E, Manzanares JM, Ortega-Azorín C, Castañer O, Peña-Orihuela PJ, Zazo JM, Muñoz Bravo C, Martinez-Urbistondo D, Chaplin A, Casas R, Cano Ibáñez N, Tojal-Sierra L, Gómez-Perez AM, Pascual Roquet-Jalmar E, Mestre C, Barragán R, Schröder H, Garcia-Rios A, Candela García I, Ruiz-Canela M, Babio N, Malcampo M, Daimiel L, Martínez A. Dietary Iron, Anemia Markers, Cognition, and Quality of Life in Older Community-Dwelling Subjects at High Cardiovascular Risk. Nutrients 2023; 15:4440. [PMID: 37892515 PMCID: PMC10610130 DOI: 10.3390/nu15204440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/05/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Anemia causes hypo-oxygenation in the brain, which could lead to cognitive disorders. We examined dietary iron intake as well as anemia markers (i.e., hemoglobin, hematocrit, mean corpuscular volume) and diabetes coexistence in relation to neuropsychological function and quality of life. In this study, 6117 community-dwelling adults aged 55-75 years (men) and 60-75 years (women) with overweight/obesity and metabolic syndrome were involved. We performed the Mini-Mental State Examination (MMSE), the Trail Making Test parts A and B (TMT-A/B), Semantic Verbal Fluency of animals (VFT-a), Phonological Verbal Fluency of letter P (VFT-p), Digit Span Test (DST), the Clock Drawing Test (CDT), and the Short Form-36 Health Survey (SF36-HRQL test). Dietary iron intake did not influence neuropsychological function or quality of life. However, anemia and lower levels of anemia markers were associated with worse scores in all neurophysiological and SF36-HRQL tests overall, but were especially clear in the MMSE, TMT-B (cognitive flexibility), and the physical component of the SF36-HRQL test. The relationships between anemia and diminished performance in the TMT-A/B and VFT tasks were notably pronounced and statistically significant solely among participants with diabetes. In brief, anemia and reduced levels of anemia markers were linked to inferior cognitive function, worse scores in different domains of executive function, as well as a poorer physical, but not mental, component of quality of life. It was also suggested that the coexistence of diabetes in anemic patients may exacerbate this negative impact on cognition. Nevertheless, dietary iron intake showed no correlation with any of the outcomes. To make conclusive recommendations for clinical practice, our findings need to be thoroughly tested through methodologically rigorous studies that minimize the risk of reverse causality.
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Affiliation(s)
- Carolina Donat-Vargas
- ISGlobal, Campus Mar, 08036 Barcelona, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.V.); (A.B.-C.); (N.C.I.); (H.S.)
| | - Víctor Mico
- Cardiometabolic Nutrition Group, IMDEA Food, CEI UAM + CSIC, 28049 Madrid, Spain; (V.M.); (R.S.-C.); (M.D.-R.)
| | - Rodrigo San-Cristobal
- Cardiometabolic Nutrition Group, IMDEA Food, CEI UAM + CSIC, 28049 Madrid, Spain; (V.M.); (R.S.-C.); (M.D.-R.)
| | - Miguel Ángel Martínez-González
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine and Public Health, University of Navarra, IDISNA, 31008 Pamplona, Spain
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Jordi Salas-Salvadó
- Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43201 Reus, Spain; (J.S.-S.); (J.M.M.)
- Food, Nutrition, Development and Mental Health Research Group, Institut d’Investigació Pere Virgili (IISPV), 43204 Reus, Spain
- Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain
| | - Dolores Corella
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain
| | - Montserrat Fitó
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.M.)
| | - Ángel Maria Alonso-Gómez
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009 Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- EpiPHAAN Research Group, Department of Nursing, School of Health Sciences, University of Málaga-IBIMA (Instituto de Investigación Biomédica de Málaga), 29071 Málaga, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.V.); (A.B.-C.); (N.C.I.); (H.S.)
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), 03010 Alicante, Spain
| | - Dora Romaguera
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, Spain
| | - José López-Miranda
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Córdoba, Spain
| | - Ramon Estruch
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Internal Medicine, Institut d’Investigació Biomèdica August Pi I Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain
| | - Miguel Damas-Fuentes
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), Virgen de la Victoria Hospital, University of Málaga, 29016 Málaga, Spain
| | - José Lapetra
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, 41013 Sevilla, Spain
| | - Luís Serra-Majem
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria, Preventive Medicine Service, Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, 35016 Las Palmas, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.V.); (A.B.-C.); (N.C.I.); (H.S.)
- Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
| | - Josep Antoni Tur
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, Spain
- Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, 07122 Palma de Mallorca, Spain
| | - Sergio Cinza-Sanjurjo
- CS Milladoiro, Área Sanitaria de Santiago de Compostela, 15706 Santiago de Compostela, Spain;
- Instituto de Investigación de Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain
- Departamento de Medicina, Universidad de Santiago de Compostela, 15701 Santiago de Compostela, Spain
| | - Xavier Pintó
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, 08907 Barcelona, Spain
| | - Miguel Delgado-Rodríguez
- Cardiometabolic Nutrition Group, IMDEA Food, CEI UAM + CSIC, 28049 Madrid, Spain; (V.M.); (R.S.-C.); (M.D.-R.)
- Division of Preventive Medicine, Faculty of Medicine, University of Jaén, 23071 Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain;
| | - Josep Vidal
- Department of Endocrinology, IDIBAPS, Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain;
- Biomedical Research Centre for Diabetes and Metabolic Diseases Network (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Claudia Causso
- Servicio de Endocrinologia Hospital General de Villalba, 28400 Madrid, Spain;
| | - Emilio Ros
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, 08036 Barcelona, Spain
| | - Estefanía Toledo
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine and Public Health, University of Navarra, IDISNA, 31008 Pamplona, Spain
| | - Josep Maria Manzanares
- Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43201 Reus, Spain; (J.S.-S.); (J.M.M.)
| | - Carolina Ortega-Azorín
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain
| | - Olga Castañer
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.M.)
| | - Patricia Judith Peña-Orihuela
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Córdoba, Spain
| | - Juan Manuel Zazo
- Department of Preventive Medicine and Public Health, School of Medicine, Instituto de Investigación Biomédica de Málaga, University of Málaga, 29590 Málaga, Spain;
| | - Carlos Muñoz Bravo
- Department of Public Health and Psychiatry, University of Malaga-IBIMA (Instituto de Investigación Biomédica de Málaga), 29071 Málaga, Spain
| | | | - Alice Chaplin
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma de Mallorca, Spain
| | - Rosa Casas
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Internal Medicine, Institut d’Investigació Biomèdica August Pi I Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain
| | - Naomi Cano Ibáñez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.V.); (A.B.-C.); (N.C.I.); (H.S.)
- Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.Granada, 18012 Granada, Spain
| | - Lucas Tojal-Sierra
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009 Vitoria-Gasteiz, Spain
| | - Ana María Gómez-Perez
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), Virgen de la Victoria Hospital, University of Málaga, 29016 Málaga, Spain
| | | | - Cristina Mestre
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43201 Reus, Spain; (J.S.-S.); (J.M.M.)
- Food, Nutrition, Development and Mental Health Research Group, Institut d’Investigació Pere Virgili (IISPV), 43204 Reus, Spain
| | - Rocío Barragán
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine, University of Valencia, 46010 Valencia, Spain
| | - Helmut Schröder
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.V.); (A.B.-C.); (N.C.I.); (H.S.)
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.M.)
| | - Antonio Garcia-Rios
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Córdoba, Spain
| | | | - Miguel Ruiz-Canela
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Preventive Medicine and Public Health, University of Navarra, IDISNA, 31008 Pamplona, Spain
| | - Nancy Babio
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Unitat de Nutrició Humana, Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, 43201 Reus, Spain; (J.S.-S.); (J.M.M.)
- Food, Nutrition, Development and Mental Health Research Group, Institut d’Investigació Pere Virgili (IISPV), 43204 Reus, Spain
| | - Mireia Malcampo
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), 08003 Barcelona, Spain; (O.C.); (M.M.)
| | - Lidia Daimiel
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, 28049 Madrid, Spain;
| | - Alfredo Martínez
- Cardiometabolic Nutrition Group, IMDEA Food, CEI UAM + CSIC, 28049 Madrid, Spain; (V.M.); (R.S.-C.); (M.D.-R.)
- Biomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain; (M.Á.M.-G.); (D.C.); (M.F.); (Á.M.A.-G.); (J.W.); (D.R.); (J.L.-M.); (R.E.); (M.D.-F.); (J.L.); (L.S.-M.); (J.A.T.); (X.P.); (E.R.); (E.T.); (C.O.-A.); (P.J.P.-O.); (A.C.); (R.C.); (L.T.-S.); (A.M.G.-P.); (C.M.); (R.B.); (A.G.-R.); (M.R.-C.); (N.B.)
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, 31008 Pamplona, Spain
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Bracca V, Cantoni V, Gadola Y, Rivolta J, Cosseddu M, Turrone R, Caratozzolo S, Di Luca M, Padovani A, Borroni B, Benussi A. Neurophysiological correlates of altered time awareness in Alzheimer's disease and frontotemporal dementia. Neurol Sci 2023; 44:3515-3522. [PMID: 37247033 DOI: 10.1007/s10072-023-06877-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 05/25/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Alterations in time awareness have been reported in dementia, particularly in Alzheimer's disease (AD) and frontotemporal dementia (FTD). However, the neurophysiological correlates underlying these alterations remain largely unexplored. This study aimed to investigate the neurophysiological correlates of altered time awareness in AD and FTD patients. METHODS A total of 150 participants (50 AD patients, 50 FTD patients, and 50 healthy controls [HC]) underwent a standardized neuropsychological assessment, an altered time awareness survey, and transcranial magnetic stimulation (TMS) to assess cholinergic (short latency afferent inhibition-SAI), GABAergic (short interval intracortical inhibition-SICI), and glutamatergic (intracortical facilitation-ICF) circuits. RESULTS In AD patients, the most frequent symptom was difficulty in ordering past events (52.0%), while FTD patients primarily struggled with estimating temporal intervals between events (40.0%). Significant differences were observed between HC and both patient groups, as well as between AD and FTD patients in their tendency to re-live past events. Binomial logistic regression analysis revealed that impairments in glutamatergic and cholinergic circuits significantly predicted the likelihood of participants manifesting altered time awareness symptoms. CONCLUSIONS This study provides novel insights into the neurophysiological correlates of altered time awareness in AD and FTD patients, highlighting the involvement of specific neurotransmitter circuits, particularly glutamatergic and cholinergic circuits. Further research is needed to explore the potential clinical implications and therapeutic targets arising from these findings.
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Affiliation(s)
- Valeria Bracca
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Valentina Cantoni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Yasmine Gadola
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Jasmine Rivolta
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Maura Cosseddu
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Rosanna Turrone
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Salvatore Caratozzolo
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Monica Di Luca
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy
| | - Alberto Benussi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy.
- Neurology Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy.
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Lazarova S, Grigorova D, Petrova-Antonova D. Detection of Alzheimer's Disease Using Logistic Regression and Clock Drawing Errors. Brain Sci 2023; 13:1139. [PMID: 37626495 PMCID: PMC10452900 DOI: 10.3390/brainsci13081139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/27/2023] Open
Abstract
Alzheimer's disease is an incurable disorder that accounts for up to 70% of all dementia cases. While the prevalence of Alzheimer's disease and other types of dementia has increased by more than 160% in the last 30 years, the rates of undetected cases remain critically high. The present work aims to address the underdetection of Alzheimer's disease by proposing four logistic regression models that can be used as a foundation for community-based screening tools that do not require the participation of medical professionals. Our models make use of individual clock drawing errors as well as complementary patient data that is highly available and easily collectible. All models were controlled for age, education, and gender. The discriminative ability of the models was evaluated by area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow test, and calibration plots were used to assess calibration. Finally, decision curve analysis was used to quantify clinical utility. We found that among 10 possible CDT errors, only 3 were informative for the detection of Alzheimer's disease. Our base regression model, containing only control variables and clock drawing errors, produced an AUC of 0.825. The other three models were built as extensions of the base model with the step-wise addition of three groups of complementary data, namely cognitive features (semantic fluency score), genetic predisposition (family history of dementia), and cardio-vascular features (BMI, blood pressure). The addition of verbal fluency scores significantly improved the AUC compared to the base model (0.91 AUC). However, further additions did not make a notable difference in discriminatory power. All models showed good calibration. In terms of clinical utility, the derived models scored similarly and greatly outperformed the base model. Our results suggest that the combination of clock symmetry and clock time errors plus verbal fluency scores may be a suitable candidate for developing accessible screening tools for Alzheimer's disease. However, future work should validate our findings in larger and more diverse datasets.
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Affiliation(s)
- Sophia Lazarova
- GATE Institute, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
- Institute of Neurobiology, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
| | - Denitsa Grigorova
- Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
| | - Dessislava Petrova-Antonova
- GATE Institute, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
- Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, 1504 Sofia, Bulgaria;
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Nishi SK, Babio N, Paz-Graniel I, Serra-Majem L, Vioque J, Fitó M, Corella D, Pintó X, Bueno-Cavanillas A, Tur JA, Diez-Ricote L, Martinez JA, Gómez-Martínez C, González-Botella A, Castañer O, Alvarez-Sala A, Montesdeoca-Mendoza C, Fanlo-Maresma M, Cano-Ibáñez N, Bouzas C, Daimiel L, Zulet MÁ, Sievenpiper JL, Rodriguez KL, Vázquez-Ruiz Z, Salas-Salvadó J. Water intake, hydration status and 2-year changes in cognitive performance: a prospective cohort study. BMC Med 2023; 21:82. [PMID: 36882739 PMCID: PMC9993798 DOI: 10.1186/s12916-023-02771-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 02/06/2023] [Indexed: 03/09/2023] Open
Abstract
BACKGROUND Water intake and hydration status have been suggested to impact cognition; however, longitudinal evidence is limited and often inconsistent. This study aimed to longitudinally assess the association between hydration status and water intake based on current recommendations, with changes in cognition in an older Spanish population at high cardiovascular disease risk. METHODS A prospective analysis was conducted of a cohort of 1957 adults (aged 55-75) with overweight/obesity (BMI between ≥ 27 and < 40 kg/m2) and metabolic syndrome from the PREDIMED-Plus study. Participants had completed bloodwork and validated, semiquantitative beverage and food frequency questionnaires at baseline, as well as an extensive neuropsychological battery of 8 validated tests at baseline and 2 years of follow-up. Hydration status was determined by serum osmolarity calculation and categorized as < 295 mmol/L (hydrated), 295-299.9 mmol/L (impending dehydration), and ≥ 300 mmol/L (dehydrated). Water intake was assessed as total drinking water intake and total water intake from food and beverages and according to EFSA recommendations. Global cognitive function was determined as a composite z-score summarizing individual participant results from all neuropsychological tests. Multivariable linear regression models were fitted to assess the associations between baseline hydration status and fluid intake, continuously and categorically, with 2-year changes in cognitive performance. RESULTS The mean baseline daily total water intake was 2871 ± 676 mL/day (2889 ± 677 mL/day in men; 2854 ± 674 mL/day in women), and 80.2% of participants met the ESFA reference values for an adequate intake. Serum osmolarity (mean 298 ± 24 mmol/L, range 263 to 347 mmol/L) indicated that 56% of participants were physiologically dehydrated. Lower physiological hydration status (i.e., greater serum osmolarity) was associated with a greater decline in global cognitive function z-score over a 2-year period (β: - 0.010; 95% CI - 0.017 to - 0.004, p-value = 0.002). No significant associations were observed between water intake from beverages and/or foods with 2-year changes in global cognitive function. CONCLUSIONS Reduced physiological hydration status was associated with greater reductions in global cognitive function over a 2-year period in older adults with metabolic syndrome and overweight or obesity. Future research assessing the impact of hydration on cognitive performance over a longer duration is needed. TRIAL REGISTRATION International Standard Randomized Controlled Trial Registry, ISRCTN89898870. Retrospectively registered on 24 July 2014.
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Affiliation(s)
- Stephanie K Nishi
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain.
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada.
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain.
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
| | - Lluís Serra-Majem
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante. Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Montserrat Fitó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Xavier Pintó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
- School of Medicine, Universitat de Barcelona, 08907, Barcelona, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Josep A Tur
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, 07122, Palma de Mallorca, Spain
| | - Laura Diez-Ricote
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, 28049, Madrid, Spain
| | - J Alfredo Martinez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
- Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Carlos Gómez-Martínez
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
| | | | - Olga Castañer
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | | | - Cristina Montesdeoca-Mendoza
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Marta Fanlo-Maresma
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | - Naomi Cano-Ibáñez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria Granada, IBS-Granada, Granada, Spain
| | - Cristina Bouzas
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands, 07122, Palma de Mallorca, Spain
| | - Lidia Daimiel
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, 28049, Madrid, Spain
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, 28660, Spain
| | - María Ángeles Zulet
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - John L Sievenpiper
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, ON, Canada
- Division of Endocrinology & Metabolism, St. Michael's Hospital, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Kelly L Rodriguez
- Departament of Occupational Risk Prevention, Virgen de la Arrixaca's Hospital (HCUVA), Murcia, Spain
| | - Zenaida Vázquez-Ruiz
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, Instituto de Investigación Sanitaria de Navarra (IdiSNA), University of Navarra, Pamplona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
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11
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James CE, Stucker C, Junker-Tschopp C, Fernandes AM, Revol A, Mili ID, Kliegel M, Frisoni GB, Brioschi Guevara A, Marie D. Musical and psychomotor interventions for cognitive, sensorimotor, and cerebral decline in patients with Mild Cognitive Impairment (COPE): a study protocol for a multicentric randomized controlled study. BMC Geriatr 2023; 23:76. [PMID: 36747142 PMCID: PMC9900212 DOI: 10.1186/s12877-022-03678-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/03/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Regular cognitive training can boost or maintain cognitive and brain functions known to decline with age. Most studies administered such cognitive training on a computer and in a lab setting. However, everyday life activities, like musical practice or physical exercise that are complex and variable, might be more successful at inducing transfer effects to different cognitive domains and maintaining motivation. "Body-mind exercises", like Tai Chi or psychomotor exercise, may also positively affect cognitive functioning in the elderly. We will compare the influence of active music practice and psychomotor training over 6 months in Mild Cognitive Impairment patients from university hospital memory clinics on cognitive and sensorimotor performance and brain plasticity. The acronym of the study is COPE (Countervail cOgnitive imPairmEnt), illustrating the aim of the study: learning to better "cope" with cognitive decline. METHODS We aim to conduct a randomized controlled multicenter intervention study on 32 Mild Cognitive Impairment (MCI) patients (60-80 years), divided over 2 experimental groups: 1) Music practice; 2) Psychomotor treatment. Controls will consist of a passive test-retest group of 16 age, gender and education level matched healthy volunteers. The training regimens take place twice a week for 45 min over 6 months in small groups, provided by professionals, and patients should exercise daily at home. Data collection takes place at baseline (before the interventions), 3, and 6 months after training onset, on cognitive and sensorimotor capacities, subjective well-being, daily living activities, and via functional and structural neuroimaging. Considering the current constraints of the COVID-19 pandemic, recruitment and data collection takes place in 3 waves. DISCUSSION We will investigate whether musical practice contrasted to psychomotor exercise in small groups can improve cognitive, sensorimotor and brain functioning in MCI patients, and therefore provoke specific benefits for their daily life functioning and well-being. TRIAL REGISTRATION The full protocol was approved by the Commission cantonale d'éthique de la recherche sur l'être humain de Genève (CCER, no. 2020-00510) on 04.05.2020, and an amendment by the CCER and the Commission cantonale d'éthique de la recherche sur l'être humain de Vaud (CER-VD) on 03.08.2021. The protocol was registered at clinicaltrials.gov (20.09.2020, no. NCT04546451).
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Affiliation(s)
- C E James
- Geneva School of Health Sciences, Geneva Musical Minds Lab (GEMMI lab), University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland.
- Faculty of Psychology and Educational Sciences, University of Geneva, Boulevard Carl-Vogt 101, 1205, Geneva, Switzerland.
| | - C Stucker
- Geneva School of Health Sciences, Geneva Musical Minds Lab (GEMMI lab), University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
| | - C Junker-Tschopp
- Geneva School of Social Work, Department of Psychomotricity, University of Applied Sciences and Arts Western Switzerland HES-SO, Rue Prévost-Martin 28, 1205, Geneva, Switzerland
| | - A M Fernandes
- Geneva School of Health Sciences, Geneva Musical Minds Lab (GEMMI lab), University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
| | - A Revol
- Geneva School of Social Work, Department of Psychomotricity, University of Applied Sciences and Arts Western Switzerland HES-SO, Rue Prévost-Martin 28, 1205, Geneva, Switzerland
| | - I D Mili
- Faculty of Psychology and Educational Sciences, Didactics of Arts and Movement Laboratory, University of Geneva, Switzerland. Boulevard Carl-Vogt 101, 1205, Geneva, Switzerland
| | - M Kliegel
- Faculty of Psychology and Educational Sciences, Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Switzerland, Boulevard du Pont d'Arve 28, 1205, Geneva, Switzerland
| | - G B Frisoni
- University Hospitals and University of Geneva, Memory Center, Rue Gabrielle-Perret-Gentil 6, 1205, Geneva, Switzerland
| | - A Brioschi Guevara
- Leenaards Memory Center, Lausanne University Hospital, Chemin de Mont-Paisible 16, 1011, Lausanne, Switzerland
| | - D Marie
- Geneva School of Health Sciences, Geneva Musical Minds Lab (GEMMI lab), University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, MRI HUG-UNIGE, University of Geneva, Geneva, Switzerland
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12
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Ability of clock drawing errors on Mini-Cog test to predict development of delirium after major urological cancer surgery. Curr Urol 2023. [DOI: 10.1097/cu9.0000000000000177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
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13
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Gołębiowska J, Szymala-Pędzik M, Żórawska J, Sobieszczańska M, Agrawal S. Identification of Factors Affecting the Increased Percentage of CGA Recommendations among Patients on Geriatric Ward. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2065. [PMID: 36767432 PMCID: PMC9915924 DOI: 10.3390/ijerph20032065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/17/2023] [Accepted: 01/18/2023] [Indexed: 06/18/2023]
Abstract
In Poland, the elderly population is noticeably increasing every year. Therefore, the current healthcare system has to rise to the challenge of treatment and prevention strategies targeting elderly persons. Based on the Vulnerable Elders Survey (VES-13 scale), consisting of international and validated scales, we put effort into identifying the factors affecting the increased percentage of CGA (Comprehensive Geriatric Assessment) recommendations by healthcare system physicians. The study group involved 78 patients from the Department of Geriatrics, Wroclaw Medical University, Poland, aged 60-91 (median Me = 81 years old). Of the studied patients, 51 were recommended for CGA (51/78; 64.6%). A statistically significant association was observed between CGA recommendation and age (p < 0.001); the likelihood of a CGA recommendation increased with age. Furthermore, the increased CGA recommendation was observed among geriatric patients with: (a) frailty syndrome (OR = 11.2, CI95% 2.88-43.5, p < 0.001), (b) high risk of malnutrition or malnutrition (OR = 3.87; CI95%, 1.00-14.9, p = 0.04), (c) low mental status (OR = 3.32, CI95% 1.22-9.09, p = 0.029), (d) low ability to perform basic daily duties (according to ADL scale-OR = 12.6, CI95% 1.57-101, p = 0.004 and IADL scale-OR = 4.71, CI95% 1.72-12.9, p = 0.003), and (e) fall risk (OR = 15.0, CI95% 4.67-48.3, p < 0.001). Moreover, homocysteine levels increased with age (p = 0.003) and decreased with sleep duration (p = 0.043). Taken together, all these factors seem to be important when implementing treatment programs adjusted to the individual geriatric patient.
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Affiliation(s)
- Justyna Gołębiowska
- Department and Clinic of Internal Medicine, Occupational Diseases, Hypertension and Clinical Oncology, Wroclaw Medical University, 50-556 Wroclaw, Poland
| | - Małgorzata Szymala-Pędzik
- Clinical Department of Geriatrics, Wroclaw Medical University, Pasteur 4 Street, 50-367 Wroclaw, Poland
| | - Joanna Żórawska
- Clinical Department of Geriatrics, Wroclaw Medical University, Pasteur 4 Street, 50-367 Wroclaw, Poland
| | - Małgorzata Sobieszczańska
- Clinical Department of Geriatrics, Wroclaw Medical University, Pasteur 4 Street, 50-367 Wroclaw, Poland
| | - Siddarth Agrawal
- Department and Clinic of Internal Medicine, Occupational Diseases, Hypertension and Clinical Oncology, Wroclaw Medical University, 50-556 Wroclaw, Poland
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14
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Velázquez-Díaz D, Cadenas-Sanchez C, Molina-Guzmán FA, Sáenz-Carrasco JA, Gonzalez-Rosa JJ, Erickson KI, Carbonell-Baeza A, Jiménez-Pavón D. A new set of estimated cardiorespiratory fitness equations are associated with cognitive performance in older adults. GeroScience 2023:10.1007/s11357-022-00718-w. [PMID: 36653578 PMCID: PMC10400484 DOI: 10.1007/s11357-022-00718-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/21/2022] [Indexed: 01/20/2023] Open
Abstract
This study aimed to develop new equations to estimate cardiorespiratory fitness specifically for older adults and, secondly, to analyze the associations of cardiorespiratory fitness, both objectively measured and estimated using new equations, with cognitive performance. Ninety-two older adults (41 females, 65-75 years) from baseline data of a randomized controlled trial were analyzed ("ClinicalTrials.gov" Identifier: NCT03923712). Participants completed 4 measurement sessions including (i) physiological and health indicators in a laboratory setting, (ii) field-based fitness tests, (iii) sociodemographic and physical activity questionnaires, and (iv) a battery of neuropsychological tests to evaluate cognitive performance. The main findings were as follows: (i) a set of new equations with good predictive value for estimated cardiorespiratory fitness were developed (74-87%), using different scenarios of complexity and/or equipment requirements, and (ii) higher estimated cardiorespiratory fitness, even using its simplest equation (eCRF = - 1261.99 + 1.97 × 6 min walking test (m) + 1.12 × bioimpedance basal metabolic rate (kcal/day) + 5.25 × basal heart rate (bpm)), was associated with better cognitive performance evaluated by several neuropsychological tests (i.e., language, cognitive flexibility, fluency, attention, and working memory), similar to using objectively measured cardiorespiratory fitness. In summary, a new set of estimated cardiorespiratory fitness equations have been developed with predictive values ranging from 74 to 87% that could be used based on necessity, availability of equipment, resources, or measurement context. Moreover, similar to objectively measured cardiorespiratory fitness, this measure of estimated cardiorespiratory fitness was positively associated with performance on language, fluency, cognitive flexibility, attention, and working memory, independently of sex, age, and education level.
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Affiliation(s)
- Daniel Velázquez-Díaz
- ExPhy Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain.,Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain.,Brain Aging & Cognitive Health Lab, Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,MOVE-IT Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain
| | - Cristina Cadenas-Sanchez
- PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Sport and Health University Research Institute (iMUDS), Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain.,Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
| | - Flor Abril Molina-Guzmán
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain.,MOVE-IT Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain
| | - Jesús Alfredo Sáenz-Carrasco
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain.,MOVE-IT Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain
| | - Javier J Gonzalez-Rosa
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain.,Department of Psychology, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain
| | - Kirk I Erickson
- Brain Aging & Cognitive Health Lab, Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Sport and Health University Research Institute (iMUDS), Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain.,AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, USA
| | - Ana Carbonell-Baeza
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain. .,MOVE-IT Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain.
| | - David Jiménez-Pavón
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain.,MOVE-IT Research Group, Department of Physical Education, Faculty of Education Sciences, University of Cadiz, Cádiz, Spain.,CIBER of Frailty and Healthy Aging (CIBERFES), Madrid, Spain
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15
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Heyrani R, Sarabi-Jamab A, Grafman J, Asadi N, Soltani S, Mirfazeli FS, Almasi-Dooghaei M, Shariat SV, Jahanbakhshi A, Khoeini T, Joghataei MT. Limits on using the clock drawing test as a measure to evaluate patients with neurological disorders. BMC Neurol 2022; 22:509. [PMID: 36585622 PMCID: PMC9805016 DOI: 10.1186/s12883-022-03035-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/19/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The Clock Drawing Test (CDT) is used as a quick-to-conduct test for the diagnosis of dementia and a screening tool for cognitive impairments in neurological disorders. However, the association between the pattern of CDT impairments and the location of brain lesions has been controversial. We examined whether there is an association between the CDT scores and the location of brain lesions using the two available scoring systems. METHOD One hundred five patients with brain lesions identified by CT scanning were recruited for this study. The Montreal Cognitive Assessment (MoCA) battery including the CDT were administered to all partcipants. To score the CDT, we used a qualitative scoring system devised by Rouleau et al. (1992). For the quantitative scoring system, we adapted the algorithm method used by Mendes-Santos et al. (2015) based on an earlier study by Sunderland et al. (1989). For analyses, a machine learning algorithm was used. RESULTS Remarkably, 30% of the patients were not detected by the CDT. Quantitative and qualitative errors were categorized into different clusters. The classification algorithm did not differentiate the patients with traumatic brain injury 'TBI' from non-TBI, or the laterality of the lesion. In addition, the classification accuracy for identifying patients with specific lobe lesions was low, except for the parietal lobe with an accuracy of 63%. CONCLUSION The CDT is not an accurate tool for detecting focal brain lesions. While the CDT still is beneficial for use with patients suspected of having a neurodegenerative disorder, it should be cautiously used with patients with focal neurological disorders.
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Affiliation(s)
- Raheleh Heyrani
- grid.411746.10000 0004 4911 7066Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran
| | - Atiye Sarabi-Jamab
- grid.418744.a0000 0000 8841 7951School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Jordan Grafman
- grid.477681.bShirly Ryan AbilityLab, Departments of Physical Medicine and Rehabilitation, Neurology, Cognitive Neurology, and Alzheimer’s Center, Chicago, IL USA ,grid.16753.360000 0001 2299 3507Department of Psychiatry, Feinberg School of Medicine and Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Chicago, IL USA
| | - Nesa Asadi
- grid.411746.10000 0004 4911 7066Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran
| | - Sarvenaz Soltani
- grid.411746.10000 0004 4911 7066Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Sadat Mirfazeli
- grid.411746.10000 0004 4911 7066Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran ,grid.490421.a0000 0004 0612 3773Faculty of Medicine, Rasool Akram Hospital, Iran Unversity of Medical Sciences, Tehran, Iran
| | - Mostafa Almasi-Dooghaei
- grid.411746.10000 0004 4911 7066Department of Neurology, Firoozgar Hospital, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Seyed Vahid Shariat
- grid.411746.10000 0004 4911 7066Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran
| | - Amin Jahanbakhshi
- grid.411746.10000 0004 4911 7066Department of Neurosurgery, Skull Base Research Center, Rasool Akram Hospital, Iran University of Medical Sciences, Tehran, Iran ,grid.411746.10000 0004 4911 7066Stem Cell and Regenerative Medicine Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Tara Khoeini
- grid.411746.10000 0004 4911 7066Department of Neurology, Firoozgar Hospital, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mohammad Taghi Joghataei
- grid.411746.10000 0004 4911 7066Cellular and Molecular Research Center (CMRC), Iran University of Medical Sciences, Tehran, Iran
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Kaul S, Goyal S, Paplikar A, Varghese F, Alladi S, Menon R, Sharma M, Dhaliwal RS, Ghosh A, Narayanan J, Nehra A, Tripathi M. Evaluation of Vascular Cognitive Impairment Using the ICMR-Neuro Cognitive Tool Box (ICMR-NCTB) in a Stroke Cohort from India. Ann Indian Acad Neurol 2022; 25:1130-1137. [PMID: 36911460 PMCID: PMC9996510 DOI: 10.4103/aian.aian_755_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 09/14/2022] [Accepted: 10/10/2022] [Indexed: 03/14/2023] Open
Abstract
Background and Purpose Vascular cognitive impairment (VCI) presents with a spectrum of cognitive impairment due to stroke and poses a huge socioeconomic burden especially in low middle-income countries. There is a critical need for early recognition and identification of VCI patients. Therefore, we developed and validated culturally appropriate neuropsychological instruments, the ICMR-Neuro Cognitive Tool-Box (ICMR-NCTB) and Montreal Cognitive Assessment (MoCA) to diagnose vascular MCI and dementia in the Indian context. Methods A total of 181 participants: 59 normal cognition, 25 stroke with normal cognition, 46 vascular MCI (VaMCI) and 51 vascular dementia (VaD) were recruited for the study. The ICMR-NCTB and MoCA were administered to patients with VCI and major cognitive domains were evaluated. Results The ICMR-NCTB was found to have good internal reliability in VaMCI and VaD. The sensitivity of the ICMR-NCTB to detect VaMCI and VaD ranged from 70.8% to 72.9% and 75.9% to 79.7%, respectively, and the specificity for VaMCI and VaD ranged from 84.8% to 86.1% and 82.5% to 85.2%, respectively. The MoCA had excellent sensitivity and specificity to detect VaMCI and VaD at ideal cut-off scores. Conclusion The ICMR-NCTB is a valid neuropsychological toolbox that can be used for comprehensive cognitive assessment and diagnosis of VCI in India. In addition, the Indian version of MoCA is more adept as a screening instrument to detect VCI due to its high sensitivity. The ICMR-NCTB will aid in early detection and management of many patients, thereby reducing the burden of vascular MCI and dementia in India.
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Affiliation(s)
- Subhash Kaul
- Department of Neurology, Krishna Institute of Medical Sciences, Hyderabad, Telangana, India
- Department of Neurology, Nizam's Institute of Medical Sciences, Hyderabad, Telangana, India
| | - Sheetal Goyal
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Avanthi Paplikar
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
- Department of Speech and Language Studies, Dr. S. R. Chandrasekhar Institute of Speech and Hearing, Bengaluru, Karnataka, India
| | - Feba Varghese
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Suvarna Alladi
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | - Ramshekhar Menon
- Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | | | - RS Dhaliwal
- Indian Council of Medical Research, New Delhi, India
| | - Amitabha Ghosh
- Cognitive Neurology Unit, Apollo Gleneagles Hospital, Kolkata, West Bengal, India
| | - Jwala Narayanan
- Department of Neurology, Manipal Hospitals, Bengaluru, Karnataka, India
| | - Ashima Nehra
- Neuropsychology, Neuroscience Center, All India Institute of Medical Sciences, Delhi, India
| | - Manjari Tripathi
- Department of Neurology All India Institute of Medical Sciences, Delhi, India
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Schaller N, Krusemark H, Mende E, Weiß M, Spanier B, Zelger O, Bischof J, Haller B, Halle M, Siegrist M. Bestform-F - Best Function of Range of Motion: A Feasibility Study of a Multimodal Exercise Training Program for Older Adults in Retirement Homes. Clin Interv Aging 2022; 17:1069-1080. [PMID: 35846178 PMCID: PMC9286070 DOI: 10.2147/cia.s367858] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 06/14/2022] [Indexed: 11/29/2022] Open
Abstract
Purpose Mobility is a crucial factor for independence and quality of life in old age. Nevertheless, many old people in retirement homes do not meet the physical activity recommendations. The aim of the Bestform-F – Best Function of Range of Motion feasibility study (bestform-F) was to evaluate the feasibility of implementing a machine-based multimodal exercise training program in older residents in retirement homes. Materials and Methods The participants (n = 77) were recruited from two retirement homes and took part in a six-month multimodal exercise training program (2x/week, 45 minutes) on pneumatic strength training machines, a balance platform and bicycle ergometers. Feasibility criteria were recruitment number ≥ 35 participants within six months, dropout rate < 40% of participants within six months of exercise, and training adherence ≥ 50% of participants taking part in at least 50% of offered training sessions. Additionally, physical performance, fear of falling, cognitive function, and quality of life were assessed at baseline and after six months. Results For the bestform-F study, 77 (85.6 ± 6.6 years; 78% women) out of 215 eligible residents from two senior residences were recruited. The dropout rate over six months was 10% (8/77 participants). The training adherence rate for the finishing participants was 77% (53/69 participants). In addition to the achieved feasibility criteria, significant improvements were recorded in the Chair Stand Test, Six-Minute Walk Test, and fear of falling after six months. Conclusion All feasibility criteria have been fulfilled. The high number of recruited participants, the low dropout rate, and high adherence to the training program confirm the feasibility of a multimodal machine-based exercise training program offered to residents in retirement homes. The results provide a basis for a cluster-randomized controlled trial aimed at further investigating the efficacy of the bestform-F program.
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Affiliation(s)
- Nina Schaller
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Helge Krusemark
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Esther Mende
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Michael Weiß
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Bianca Spanier
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Otto Zelger
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Jan Bischof
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Bernhard Haller
- Institute of AI and Informatics in Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
| | - Martin Halle
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Monika Siegrist
- Department of Prevention and Sports Medicine, School of Medicine, University Hospital 'rechts der Isar', Technical University of Munich, Munich, Germany
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18
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Ni J, Nishi SK, Babio N, Martínez‐González MA, Corella D, Castañer O, Martínez JA, Alonso‐Gómez ÁM, Gómez‐Gracia E, Vioque J, Romaguera D, López‐Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra‐Majem JL, Bueno‐Cavanillas A, Tur JA, Martín‐Sánchez V, Pintó X, Gaforio JJ, Barabash Bustelo A, Vidal J, Vázquez C, Daimiel L, Ros E, Toledo E, Coltell O, Gómez‐Martínez C, Zomeño MD, Donat‐Vargas C, Goicolea‐Güemez L, Bouzas C, Garcia‐de‐la‐Hera M, Chaplin A, Garcia‐Rios A, Casas R, Cornejo‐Pareja I, Santos‐Lozano JM, Rognoni T, Saiz C, Paz‐Graniel I, Malcampo M, Sánchez‐Villegas A, Salaverria‐Lete I, García‐Arellano A, Schröder H, Salas‐Salvadó J. Dairy Product Consumption and Changes in Cognitive Performance: Two-Year Analysis of the PREDIMED-Plus Cohort. Mol Nutr Food Res 2022; 66:e2101058. [PMID: 35524484 PMCID: PMC9541289 DOI: 10.1002/mnfr.202101058] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/22/2022] [Indexed: 11/06/2022]
Abstract
SCOPE Dairy consumption has been suggested to impact cognition; however, evidence is limited and inconsistent. This study aims to longitudinally assess the association between dairy consumption with cognitive changes in an older Spanish population at high cardiovascular disease risk. METHODS AND RESULTS Four thousand six hundred sixty eight participants aged 55-75 years, completed a validated food frequency questionnaire at baseline and a neuropsychological battery of tests at baseline and 2-year follow-up. Multivariable linear regression models are used, scaled by 100 (i.e., the units of β correspond to 1 SD/100), to assess associations between baseline tertile daily consumption and 2-year changes in cognitive performance. Participants in the highest tertile of total milk and whole-fat milk consumption have a greater decline in global cognitive function (β: -4.71, 95% CI: -8.74 to -0.69, p-trend = 0.020 and β: -6.64, 95% CI: -10.81 to -2.47, p-trend = 0.002, respectively) compared to those in the lowest tertile. No associations are observed between low fat milk, yogurt, cheese or fermented dairy consumption, and changes in cognitive performance. CONCLUSION Results suggest there are no clear prospective associations between consumption of most commonly consumed dairy products and cognition, although there may be an association with a greater rate of cognitive decline over a 2-year period in older adults at high cardiovascular disease risk for whole-fat milk.
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Affiliation(s)
- Jiaqi Ni
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
| | - Stephanie K. Nishi
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials UnitTorontoONCanada
- Clinical Nutrition and Risk Factor Modification CentreSt. Michael's HospitalUnity Health TorontoONCanada
| | - Nancy Babio
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
| | - Miguel A. Martínez‐González
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive Medicine and Public HealthUniversity of NavarraIdiSNAPamplonaSpain
- Department of NutritionHarvard T.H. Chan School of Public HealthBostonMAUSA
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive MedicineUniversity of ValenciaValenciaSpain
| | - Olga Castañer
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Unit of Cardiovascular Risk and NutritionInstitut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM)BarcelonaSpain
| | - J. Alfredo Martínez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of NutritionFood Sciences, and PhysiologyCenter for Nutrition ResearchUniversity of NavarraPamplonaSpain
- Precision Nutrition and Cardiometabolic Health Program, IMDEA FoodCEI UAM + CSICMadridSpain
| | - Ángel M. Alonso‐Gómez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- CardiovascularRespiratory and Metabolic AreaOsakidetza Basque Health ServiceBioaraba Health Research InstituteAraba University HospitalUniversity of the Basque Country UPV/EHUVitoria‐GasteizSpain
| | - Enrique Gómez‐Gracia
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of EpidemiologySchool of Medicine, Instituto de Investigación Biomédica de Málaga (IBIMA)MálagaSpain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
- Unidad de Epidemiología de la NutriciónUniversidad Miguel HernándezInstituto de Investigación Sanitaria y Biomédica de Alicante, (UMH‐ISABIAL)AlicanteSpain
| | - Dora Romaguera
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Health Research Institute of the Balearic Islands (IdISBa)Palma de MallorcaSpain
| | - José López‐Miranda
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Internal MedicineMaimonides Biomedical Research Institute of Cordoba (IMIBIC)Reina Sofia University HospitalUniversity of CordobaCordobaSpain
| | - Ramon Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Internal MedicineInstitut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)Hospital ClinicUniversity of BarcelonaBarcelonaSpain
| | - Francisco J. Tinahones
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Endocrinology and NutritionVirgen de la Victoria University HospitalInstituto de Investigación Biomédica de Málaga (IBIMA), University of MálagaMálagaSpain
| | - José Lapetra
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Family MedicineResearch UnitDistrito Sanitario Atención Primaria SevillaSevillaSpain
| | - J. Luís Serra‐Majem
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Research Institute of Biomedical and Health Sciences (IUIBS)University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI)Canarian Health ServiceLas Palmas de Gran CanariaSpain
| | - Aurora Bueno‐Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive Medicine and Public HealthUniversity of GranadaGranadaSpain
- Instituto de Investigación Biosanitaria ibs.GRANADAGranadaSpain
| | - Josep A. Tur
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Research Group on Community Nutrition & Oxidative StressUniversity of Balearic IslandsPalma de MallorcaSpain
| | - Vicente Martín‐Sánchez
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
- Institute of Biomedicine (IBIOMED)University of LeónLeónSpain
| | - Xavier Pintó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Lipids and Vascular Risk UnitInternal MedicineHospital Universitario de BellvitgeHospitalet de LlobregatBarcelonaSpain
- Universitat de BarcelonaBarcelonaSpain
| | - José J. Gaforio
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
- Departamento de Ciencias de la SaludInstituto Universitario de Investigación en Olivar y Aceites de OlivaUniversidad de JaénJaénSpain
| | - Ana Barabash Bustelo
- Endocrinology and Nutrition DepartmentHospital Clínico Universitario San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)MadridSpain
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM)Instituto de Salud Carlos III (ISCIII)MadridSpain
- Medicina II DepartmentFacultad de MedicinaUniversidad Complutense de MadridMadridSpain
| | - Josep Vidal
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM)Instituto de Salud Carlos III (ISCIII)MadridSpain
- Department of EndocrinologyInstitut d` Investigacions Biomédiques August Pi Sunyer (IDIBAPS)Hospital ClinicUniversity of BarcelonaBarcelonaSpain
| | - Clotilde Vázquez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Endocrinology and NutritionHospital Fundación Jimenez DíazInstituto de Investigaciones Biomédicas IISFJDUniversity AutonomaMadridSpain
| | - Lidia Daimiel
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA FoodCEI UAM + CSICMadridSpain
| | - Emili Ros
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Lipid ClinicDepartment of Endocrinology and NutritionInstitut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)Hospital ClínicBarcelonaSpain
| | - Estefanía Toledo
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive Medicine and Public HealthUniversity of NavarraIdiSNAPamplonaSpain
| | - Oscar Coltell
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Computer Languages and SystemsUniversitat Jaume ICastellonSpain
| | - Carlos Gómez‐Martínez
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
| | - María Dolores Zomeño
- Unit of Cardiovascular Risk and NutritionInstitut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM)BarcelonaSpain
- School of Health SciencesBlanquerna‐Ramon Llull UniversityBarcelonaSpain
| | - Carolina Donat‐Vargas
- IMDEA‐Food InstituteCEI UAM + CSICMadridSpain
- Department of Preventive Medicine and Public HealthSchool of MedicineUniversidad Autónoma de Madrid‐IdiPazCIBERESP (CIBER of Epidemiology and Public Health)MadridSpain
- Unit of Cardiovascular and Nutritional EpidemiologyInstitute of Environmental MedicineKarolinska InstitutetStockholmSweden
| | - Leire Goicolea‐Güemez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- CardiovascularRespiratory and Metabolic AreaOsakidetza Basque Health ServiceBioaraba Health Research InstituteAraba University HospitalUniversity of the Basque Country UPV/EHUVitoria‐GasteizSpain
| | - Cristina Bouzas
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Research Group on Community Nutrition & Oxidative StressUniversity of Balearic IslandsPalma de MallorcaSpain
| | - Manoli Garcia‐de‐la‐Hera
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
- Unidad de Epidemiología de la NutriciónUniversidad Miguel HernándezInstituto de Investigación Sanitaria y Biomédica de Alicante, (UMH‐ISABIAL)AlicanteSpain
| | - Alice Chaplin
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Health Research Institute of the Balearic Islands (IdISBa)Palma de MallorcaSpain
| | - Antonio Garcia‐Rios
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Internal MedicineMaimonides Biomedical Research Institute of Cordoba (IMIBIC)Reina Sofia University HospitalUniversity of CordobaCordobaSpain
| | - Rosa Casas
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Internal MedicineInstitut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS)Hospital ClinicUniversity of BarcelonaBarcelonaSpain
| | - Isabel Cornejo‐Pareja
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Endocrinology and NutritionVirgen de la Victoria University HospitalInstituto de Investigación Biomédica de Málaga (IBIMA), University of MálagaMálagaSpain
| | - José Manuel Santos‐Lozano
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Family MedicineResearch UnitDistrito Sanitario Atención Primaria SevillaSevillaSpain
| | - Teresa Rognoni
- Department of NeurologyClínica Universidad de NavarraMadridSpain
| | - Carmen Saiz
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive MedicineUniversity of ValenciaValenciaSpain
| | - Indira Paz‐Graniel
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
| | - Mireia Malcampo
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Unit of Cardiovascular Risk and NutritionInstitut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM)BarcelonaSpain
| | - Almudena Sánchez‐Villegas
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Research Institute of Biomedical and Health Sciences (IUIBS)University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI)Canarian Health ServiceLas Palmas de Gran CanariaSpain
- ISFOOD‐Institute for Innovation & Sustainable Development in Food ChainUniversidad Pública de Navarra (UPNA)IdiSNAInstituto de Investigación Sanitaria de NavarraSpain
| | - Itziar Salaverria‐Lete
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- CardiovascularRespiratory and Metabolic AreaOsakidetza Basque Health ServiceBioaraba Health Research InstituteAraba University HospitalUniversity of the Basque Country UPV/EHUVitoria‐GasteizSpain
| | - Ana García‐Arellano
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- Department of Preventive Medicine and Public HealthUniversity of NavarraIdiSNAPamplonaSpain
- Emergency DepartmentHospital Universitario de NavarraServicio Navarro de Salud‐OsaunbideaSpain
| | - Helmut Schröder
- Unit of Cardiovascular Risk and NutritionInstitut Hospital del Mar de Investigaciones Médicas Municipal d`Investigació Médica (IMIM)BarcelonaSpain
- CIBER de Epidemiología y Salud Pública (CIBERESP)Instituto de Salud Carlos IIIMadridSpain
| | - Jordi Salas‐Salvadó
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
- Institut d'Investigació Sanitària Pere Virgili (IISPV)ReusSpain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN)Instituto de Salud Carlos IIIMadridSpain
- University Hospital of Sant Joan de ReusNutrition UnitReusSpain
| | - PREDIMED‐Plus investigators.
- Universitat Rovira i VirgiliDepartament de Bioquímica i BiotecnologiaFacultat de Medicina i Ciències de la Salut. Unitat de Nutrició HumanaReusSpain
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Masuo A, Ito Y, Kanaiwa T, Naito K, Sakuma T, Kato S. Dementia Screening Based on SVM Using Qualitative Drawing Error of Clock Drawing Test. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:4484-4487. [PMID: 36085791 DOI: 10.1109/embc48229.2022.9871889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In the welfare of the elderly, it is important to detect the signs of dementia at an early stage and prevent it from becoming serious. We evaluated the performance of SVM-based cognitive function classification models and investigated the drawing features that contribute to distinguishing the severity of cognitive functions. Clock drawing test (CDT) was conducted on three groups of elderly people with different degrees of cognitive impairment. Feature selection was applied to the qualitative drawing features of the CDT, and a two-class classification model was constructed using support vector machine. The results showed that the five features related to conceptual deficits and spatial and planning deficits could be used to classify the dementia group and healthy control group with 79 % accuracy, and all the features showed statistically significant differences. It is suggested that these qualitative drawing features of the CDT can be applied to dementia screening.
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Preoperative and Postoperative Cognitive Assessment in Geriatric Patients Following Acute Traumatic Injuries: Towards Improving Geriatric Trauma Outcomes. J Surg Res 2022; 277:352-364. [PMID: 35567991 DOI: 10.1016/j.jss.2022.04.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/09/2022] [Accepted: 04/08/2022] [Indexed: 11/22/2022]
Abstract
INTRODUCTION A growing percentage of the US population is over the age of 65, and geriatrics account for a large portion of trauma admissions, expected to reach nearly 40% by 2050. Cognitive status is important for operative management, especially in elderly populations. This study aims to investigate preoperative and postoperative cognitive function assessment tools in geriatric patients following acute trauma and associated outcomes, including functional status, postdischarge disposition, mortality, and hospital length of stay (H-LOS). METHODS A literature search was conducted using Medline/PubMed, Google Scholar, Embase, JAMA Networks, and Cochrane databases for studies investigating the use of cognitive assessment tools for geriatric patients with acute trauma. The last literature search was conducted on November 13, 2021. RESULTS Ten studies were included in this review, of which five focused on preoperative cognitive assessment and five focused on postoperative. The evidence suggests patients with preoperative cognitive impairment had worse functional status, mortality, and postdischarge disposition along with increased LOS. Acute trauma patients with postoperative cognitive impairment also had worse functional status, mortality, and adverse postdischarge disposition. CONCLUSIONS Preoperative and postoperative cognitive impairment is common in geriatric patients with acute trauma and is associated with worse outcomes, including decreased functional status, increased LOS, and adverse discharge disposition. Cognitive assessment tools such as MMSE, MoCA, and CAM are fast and effective at detecting cognitive impairment in the acute trauma setting and allow clinicians to address preoperative or postoperative cognitive impairments to improve patient outcomes.
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Bat BKK, Chan JYC, Chan TK, Huo Z, Yip BHK, Wong MCS, Tsoi KKF. Comparing drawing under instructions with image copying for mild cognitive impairment (MCI) or dementia screening: a meta-analysis of 92 diagnostic studies. Aging Ment Health 2022; 26:1019-1026. [PMID: 33999724 DOI: 10.1080/13607863.2021.1922599] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Drawing is a major component of cognitive screening for dementia. It can be performed without language restriction. Drawing pictures under instructions and copying images are different screening approaches. The objective of this study was to compare the diagnostic performance between drawing under instructions and image copying for MCI and dementia screening. METHOD A literature search was carried out in the OVID databases with keywords related to drawing for cognitive screening. Study quality and risk of bias were assessed by QUADAS-2. The level of diagnostic accuracy across different drawing tests was pooled by bivariate analysis in a random effects model. The area under the hierarchical summary receiver-operating characteristic curve (AUC) was constructed to summarize the diagnostic performance. RESULTS Ninety-two studies with sample size of 22,085 were included. The pooled results for drawing under instructions showed a sensitivity of 79% (95% CI: 76 - 83%) and a specificity of 80% (95% CI: 77 - 83%) with AUC of 0.87 (95% CI: 0.83 - 0.89). The pooled results for image copying showed a sensitivity of 71% (95% CI: 62 - 79%) and a specificity of 83% (95% CI: 72 - 90%) with AUC of 0.83 (95% CI: 0.80 - 0.86). Clock-drawing test was the screening test used in the majority of studies. CONCLUSION Drawing under instructions showed a similar diagnostic performance when compared with image copying for cognitive screening and the administration of image copying is relatively simpler. Self-screening for dementia is feasible to be done at home in the near future.
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Affiliation(s)
- Baker K K Bat
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Joyce Y C Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Tak Kit Chan
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Zhaohua Huo
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Benjamin H K Yip
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Martin C S Wong
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Kelvin K F Tsoi
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.,Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, China
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Srivastava H, Joop A, Memon RA, Pilkington J, Wood KH, Love MN, Amara AW. Taking the Time to Assess Cognition in Parkinson's Disease: The Clock Drawing Test. JOURNAL OF PARKINSON'S DISEASE 2022; 12:713-722. [PMID: 34864688 PMCID: PMC10913933 DOI: 10.3233/jpd-212802] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Cognitive impairment is common and disabling in Parkinson's disease (PD). Cognitive testing can be time consuming in the clinical setting. One rapid test to detect cognitive impairment in non-PD populations is the Clock Drawing Test (CDT), which calls upon the brain's executive and visuospatial abilities to draw a clock designating a certain time. OBJECTIVE Test the hypothesis that PD participants would perform worse on CDT compared to controls and that CDT would correlate with other measures of cognition. METHODS This study evaluated two independent CDT scoring systems and differences in CDT performance between PD (N = 97) and control (N = 54) participants using a two-sample t-test. Pearson's correlations were conducted between the CDT and tests of sleepiness (Epworth Sleepiness Scale) and vigilance (Psychomotor Vigilance Test); executive function (Trails B-A); and global cognition (Montreal Cognitive Assessment). Receiver operating characteristic curves were used to determine cut points on the CDT that identify individuals who need additional cognitive testing. RESULTS PD participants had worse performance on CDT compared to controls. The CDT was correlated with executive function (Trails B-A) and global cognition (Montreal Cognitive Assessment). The CDT correlated with vigilance (Psychomotor Vigilance Task) only in healthy controls. However, the CDT was not correlated with measures of sleepiness (Epworth Sleepiness Scale) in either group. A cut point of 9 on the Rouleau scale and 18 on the Mendez scale identified PD participants with cognitive impairment. CONCLUSION The CDT is a rapid clinical cognitive assessment that is feasible in PD and correlates with other measures of cognition.
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Affiliation(s)
- Hemant Srivastava
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Allen Joop
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Raima A. Memon
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jennifer Pilkington
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kimberly H. Wood
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Psychology, Samford University, Birmingham, AL, USA
| | | | - Amy W. Amara
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
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Bahrampouri S, Khankeh HR, Hosseini SA, Mehmandar M, Ebadi A. Introducing practical tools for fit to drive assessment of the elderly: A step toward improving the health of the elderly. JOURNAL OF EDUCATION AND HEALTH PROMOTION 2021; 10:463. [PMID: 35233410 PMCID: PMC8826889 DOI: 10.4103/jehp.jehp_1644_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/08/2021] [Indexed: 06/14/2023]
Abstract
Today, as age increases, the demand for independent living has increased. Since driving is one of the safest and preferred ways for the elderly to travel, paying close attention to the accurate assessment of the elderly's driving ability can prevent traffic accidents in this age group. The purpose of this study was to identify and introduce practical tools for drive assessment fitness of the elderly. This systematic review was conducted according to Cochrane methodology and reported findings according to PRISMA. The following databases were searched from PubMed, ISI web of knowledge, Scopus, ProQuest, Medlib, SID, Magiran, Iran doc, and Iran Medex based on the population intervention comparison outcome method. The total records involving 12 main tools were assessed from 26 selected records in the final evaluation. The research findings indicated the selection of seven tools in the psycho-cognitive function domain such as TMT-B, Clock Drawing Test, MAZE, Montreal Cognitive Assessment, GDS-15, MMSE, and ACE-R, three tools in the sensory function domain such as Snellen, Confrontation Visual field, and Whispered Voice Test, and also two tools in motor function domain such as Rapid pace walk, and Manual test of the range of motion. The findings led to selecting practical, accurate, and fast tools for widespread use for the assessment of driving competencies of the elderly. Therefore, it is recommended that the selected tools be used in practical batteries to assess the driving skills of the elderly.
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Affiliation(s)
- Saiedeh Bahrampouri
- Health in Emergency and Disaster Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hamid Reza Khankeh
- Health in Emergency and Disaster Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Seyed Ali Hosseini
- Health in Emergency and Disaster Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Abbas Ebadi
- Behavioral Sciences Research Center, Life Style, Baqiyatallah University of Medical Sciences, Tehran, Iran
- Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
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24
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Nishi SK, Babio N, Gómez-Martínez C, Martínez-González MÁ, Ros E, Corella D, Castañer O, Martínez JA, Alonso-Gómez ÁM, Wärnberg J, Vioque J, Romaguera D, López-Miranda J, Estruch R, Tinahones FJ, Lapetra J, Serra-Majem JL, Bueno-Cavanillas A, Tur JA, Martín Sánchez V, Pintó X, Delgado-Rodríguez M, Matía-Martín P, Vidal J, Vázquez C, Daimiel L, Razquin C, Coltell O, Becerra-Tomás N, De La Torre Fornell R, Abete I, Sorto-Sanchez C, Barón-López FJ, Signes-Pastor AJ, Konieczna J, Garcia-Rios A, Casas R, Gomez-Perez AM, Santos-Lozano JM, García-Arellano A, Guillem-Saiz P, Ni J, Trinidad Soria-Florido M, Zulet MÁ, Vaquero-Luna J, Toledo E, Fitó M, Salas-Salvadó J. Mediterranean, DASH, and MIND Dietary Patterns and Cognitive Function: The 2-Year Longitudinal Changes in an Older Spanish Cohort. Front Aging Neurosci 2021; 13:782067. [PMID: 34966270 PMCID: PMC8710807 DOI: 10.3389/fnagi.2021.782067] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 11/08/2021] [Indexed: 01/10/2023] Open
Abstract
Background and Aims: Plant-forward dietary patterns have been associated with cardiometabolic health benefits, which, in turn, have been related to cognitive performance with inconsistent findings. The objective of this study was to examine the relationship between baseline adherence to three a priori dietary patterns (Mediterranean, DASH, and MIND diets) with 2-year changes in cognitive performance in older adults with overweight or obesity and high cardiovascular disease risk. Methods: A prospective cohort analysis was conducted within the PREDIMED-Plus trial, involving 6,647 men and women aged 55-75 years with overweight or obesity and metabolic syndrome. Using a validated, semiquantitative 143-item food frequency questionnaire completed at baseline, the dietary pattern adherence scores were calculated. An extensive neuropsychological test battery was administered at baseline and 2-year follow-up. Multivariable-adjusted linear regression models were used to assess associations between 2-year changes in cognitive function z-scores across tertiles of baseline adherence to the a priori dietary patterns. Results: Adherence to the Mediterranean diet at baseline was associated with 2-year changes in the general cognitive screening Mini-Mental State Examination (MMSE, β: 0.070; 95% CI: 0.014, 0.175, P-trend = 0.011), and two executive function-related assessments: the Trail Making Tests Part A (TMT-A, β: -0.054; 95% CI: -0.110, - 0.002, P-trend = 0.047) and Part B (TMT-B, β: -0.079; 95% CI: -0.134, -0.024, P-trend = 0.004). Adherence to the MIND diet was associated with the backward recall Digit Span Test assessment of working memory (DST-B, β: 0.058; 95% CI: 0.002, 0.114, P-trend = 0.045). However, higher adherence to the DASH dietary pattern was not associated with better cognitive function over a period of 2 years. Conclusion: In older Spanish individuals with overweight or obesity and at high cardiovascular disease risk, higher baseline adherence to the Mediterranean dietary pattern may be associated with better cognitive performance than lower adherence over a period of 2 years.
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Affiliation(s)
- Stephanie K. Nishi
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada
- Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
| | - Carlos Gómez-Martínez
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Miguel Ángel Martínez-González
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Emilio Ros
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Dolores Corella
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Olga Castañer
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), Barcelona, Spain
| | - J. Alfredo Martínez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
- Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Ángel M. Alonso-Gómez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Jesús Vioque
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Dora Romaguera
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - José López-Miranda
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Ramon Estruch
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Francisco J. Tinahones
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Lapetra
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - J. Luís Serra-Majem
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
| | - Aurora Bueno-Cavanillas
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs, GRANADA, Granada, Spain
| | - Josep A. Tur
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Research Group on Community Nutrition and Oxidative Stress, University of Balearic Islands, Palma de Mallorca, Spain
| | - Vicente Martín Sánchez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Institute of Biomedicine (IBIOMED), University of León, León, Spain
| | - Xavier Pintó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
| | - Miguel Delgado-Rodríguez
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Division of Preventive Medicine, Faculty of Medicine, University of Jaén, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Josep Vidal
- CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Institut d’ Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Clotilde Vázquez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autonoma, Madrid, Spain
| | - Lidia Daimiel
- Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Cristina Razquin
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Oscar Coltell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Computer Languages and Systems, Universitat Jaume I, Castellon, Spain
| | - Nerea Becerra-Tomás
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Rafael De La Torre Fornell
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Integrative Pharmacology and Systems Neurosciences, Instituto Hospital del Mar de Investigaciones Médicas (IMIM), Barcelona, Spain
| | - Itziar Abete
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Carolina Sorto-Sanchez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Francisco Javier Barón-López
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- EpiPHAAN Research Group, School of Health Sciences, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Antonio José Signes-Pastor
- CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante, Universidad Miguel Hernández (ISABIAL-UMH), Alicante, Spain
| | - Jadwiga Konieczna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - Antonio Garcia-Rios
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Rosa Casas
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Internal Medicine, Institut d’Investigacions Biomédiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Ana Maria Gomez-Perez
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - José Manuel Santos-Lozano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Ana García-Arellano
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Endocrinology, Virgen de la Victoria Hospital, Instituto de Investigación Biomédica de Málaga (IBIMA), University of Málaga, Málaga, Spain
| | - Patricia Guillem-Saiz
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Jiaqi Ni
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | | | - M. Ángeles Zulet
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, IdiSNA, Pamplona, Spain
| | - Jessica Vaquero-Luna
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Estefanía Toledo
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Montserrat Fitó
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d’Investigació Médica (IMIM), Barcelona, Spain
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, and Hospital Universitari San Joan de Reus, Unitat de Nutrició Humana, Reus, Spain
- Institut d’Investigació Sanitária Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Nutrition Unit, University Hospital of Sant Joan de Reus, Reus, Spain
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25
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Chan JYC, Bat BKK, Wong A, Chan TK, Huo Z, Yip BHK, Kowk TCY, Tsoi KKF. Evaluation of Digital Drawing Tests and Paper-and-Pencil Drawing Tests for the Screening of Mild Cognitive Impairment and Dementia: A Systematic Review and Meta-analysis of Diagnostic Studies. Neuropsychol Rev 2021; 32:566-576. [PMID: 34657249 PMCID: PMC9381608 DOI: 10.1007/s11065-021-09523-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 08/09/2021] [Indexed: 11/23/2022]
Abstract
Digital drawing tests have been proposed for cognitive screening over the past decade. However, the diagnostic performance is still to clarify. The objective of this study was to evaluate the diagnostic performance among different types of digital and paper-and-pencil drawing tests in the screening of mild cognitive impairment (MCI) and dementia. Diagnostic studies evaluating digital or paper-and-pencil drawing tests for the screening of MCI or dementia were identified from OVID databases, included Embase, MEDLINE, CINAHL, and PsycINFO. Studies evaluated any type of drawing tests for the screening of MCI or dementia and compared with healthy controls. This study was performed according to PRISMA and the guidelines proposed by the Cochrane Diagnostic Test Accuracy Working Group. A bivariate random-effects model was used to compare the diagnostic performance of these drawing tests and presented with a summary receiver-operating characteristic curve. The primary outcome was the diagnostic performance of clock drawing test (CDT). Other types of drawing tests were the secondary outcomes. A total of 90 studies with 22,567 participants were included. In the screening of MCI, the pooled sensitivity and specificity of the digital CDT was 0.86 (95% CI = 0.75 to 0.92) and 0.92 (95% CI = 0.69 to 0.98), respectively. For the paper-and-pencil CDT, the pooled sensitivity and specificity of brief scoring method was 0.63 (95% CI = 0.49 to 0.75) and 0.77 (95% CI = 0.68 to 0.84), and detailed scoring method was 0.63 (95% CI = 0.56 to 0.71) and 0.72 (95% CI = 0.65 to 0.78). In the screening of dementia, the pooled sensitivity and specificity of the digital CDT was 0.83 (95% CI = 0.72 to 0.90) and 0.87 (95% CI = 0.79 to 0.92). The performances of the digital and paper-and-pencil pentagon drawing tests were comparable in the screening of dementia. The digital CDT demonstrated better diagnostic performance than paper-and-pencil CDT for MCI. Other types of digital drawing tests showed comparable performance with paper-and-pencil formats. Therefore, digital drawing tests can be used as an alternative tool for the screening of MCI and dementia.
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Affiliation(s)
- Joyce Y C Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Baker K K Bat
- Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, China
| | - Adrian Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Tak Kit Chan
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Zhaohua Huo
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Benjamin H K Yip
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Timothy C Y Kowk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Kelvin K F Tsoi
- Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, China. .,JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
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26
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Halaas NB, Henjum K, Blennow K, Dakhil S, Idland AV, Nilsson LN, Sederevicius D, Vidal-Piñeiro D, Walhovd KB, Wyller TB, Zetterberg H, Watne LO, Fjell AM. CSF sTREM2 and Tau Work Together in Predicting Increased Temporal Lobe Atrophy in Older Adults. Cereb Cortex 2021; 30:2295-2306. [PMID: 31812991 DOI: 10.1093/cercor/bhz240] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 08/23/2019] [Accepted: 09/17/2019] [Indexed: 11/13/2022] Open
Abstract
Neuroinflammation may be a key factor in brain atrophy in aging and age-related neurodegenerative disease. The objective of this study was to test the association between microglial expression of soluble Triggering Receptor Expressed on Myeloid Cells 2 (sTREM2), as a measure of neuroinflammation, and brain atrophy in cognitively unimpaired older adults. Brain magnetic resonance imagings (MRIs) and cerebrospinal fluid (CSF) sTREM2, total tau (t-tau), phosphorylated181 tau (p-tau), and Aβ42 were analyzed in 115 cognitively unimpaired older adults, classified according to the A/T/(N)-framework. MRIs were repeated after 2 (n = 95) and 4 (n = 62) years. High baseline sTREM2 was associated with accelerated cortical thinning in the temporal cortex of the left hemisphere, as well as bilateral hippocampal atrophy, independently of age, Aβ42, and tau. sTREM2-related atrophy only marginally increased with biomarker positivity across the AD continuum (A-T- #x2292; A+T- #x2292; A+T+) but was significantly stronger in participants with a high level of p-tau (T+). sTREM2-related cortical thinning correlated significantly with areas of high microglial-specific gene expression in the Allen Human Brain Atlas. In conclusion, increased CSF sTREM2 was associated with accelerated cortical and hippocampal atrophy in cognitively unimpaired older participants, particularly in individuals with tau pathology. This suggests a link between neuroinflammation, neurodegeneration, and amyloid-independent tauopathy.
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Affiliation(s)
- Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway
| | - Kristi Henjum
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway.,Department of Pharmacology, Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, 431 41 Mölndal, Sweden
| | - Shams Dakhil
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway
| | - Ane-Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway
| | - Lars Ng Nilsson
- Department of Pharmacology, Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway.,Oslo University Hospital, 0424 Oslo, Norway
| | - Donatas Sederevicius
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Didac Vidal-Piñeiro
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
| | - Kristine B Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Torgeir Brunn Wyller
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, 0450 Oslo, Norway
| | - Henrik Zetterberg
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 431 41 Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 80 Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, WC1N 3BG London, UK.,UK Dementia Research Institute at UCL, WC1E 6BT London, UK
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Anders M Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
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27
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Park I, Lee U. Automatic, Qualitative Scoring of the Clock Drawing Test (CDT) Based on U-Net, CNN and Mobile Sensor Data. SENSORS (BASEL, SWITZERLAND) 2021; 21:5239. [PMID: 34372476 PMCID: PMC8348723 DOI: 10.3390/s21155239] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/26/2021] [Accepted: 07/29/2021] [Indexed: 12/17/2022]
Abstract
The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular screening tool for cognitive functions. In spite of its qualitative capabilities in diagnosis of neurological diseases, the assessment of the CDT has depended on quantitative methods as well as manual paper based methods. Furthermore, due to the impact of the advancement of mobile smart devices imbedding several sensors and deep learning algorithms, the necessity of a standardized, qualitative, and automatic scoring system for CDT has been increased. This study presents a mobile phone application, mCDT, for the CDT and suggests a novel, automatic and qualitative scoring method using mobile sensor data and deep learning algorithms: CNN, a convolutional network, U-Net, a convolutional network for biomedical image segmentation, and the MNIST (Modified National Institute of Standards and Technology) database. To obtain DeepC, a trained model for segmenting a contour image from a hand drawn clock image, U-Net was trained with 159 CDT hand-drawn images at 128 × 128 resolution, obtained via mCDT. To construct DeepH, a trained model for segmenting the hands in a clock image, U-Net was trained with the same 159 CDT 128 × 128 resolution images. For obtaining DeepN, a trained model for classifying the digit images from a hand drawn clock image, CNN was trained with the MNIST database. Using DeepC, DeepH and DeepN with the sensor data, parameters of contour (0-3 points), numbers (0-4 points), hands (0-5 points), and the center (0-1 points) were scored for a total of 13 points. From 219 subjects, performance testing was completed with images and sensor data obtained via mCDT. For an objective performance analysis, all the images were scored and crosschecked by two clinical experts in CDT scaling. Performance test analysis derived a sensitivity, specificity, accuracy and precision for the contour parameter of 89.33, 92.68, 89.95 and 98.15%, for the hands parameter of 80.21, 95.93, 89.04 and 93.90%, for the numbers parameter of 83.87, 95.31, 87.21 and 97.74%, and for the center parameter of 98.42, 86.21, 96.80 and 97.91%, respectively. From these results, the mCDT application and its scoring system provide utility in differentiating dementia disease subtypes, being valuable in clinical practice and for studies in the field.
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Affiliation(s)
| | - Unjoo Lee
- Department of Electronic Engineering, Hallym University, Chuncheon 24252, Korea;
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28
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Bouati N, Drevet S, Zerhouni N, Bioteau C, Mitha N, Gavazzi G. Cognitive Screening Tool for Geriatrics: A Retrospective Observational Study on the Correlation of the Scores in 30-Point Clock Face Test and MMSE. Indian J Psychol Med 2021; 43:306-311. [PMID: 34385723 PMCID: PMC8327860 DOI: 10.1177/0253717620961335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Over the past 30 years, the clock drawing test (CDT) has generated considerable interest due to its usefulness in the early detection of cognitive impairments, particularly those seen in neurodegenerative dementias (including Alzheimer's disease), vascular dementia, and mixed dementia. The present study aimed to determine whether the results of the "30-Point Clock Face Test" (CFT-30), a standardized version of the CDT that uses a 30-point scale, correlate with those of the Mini-Mental State Examination (MMSE). METHODS This is a retrospective, observational study. All patients hospitalized in a Hospital-University Clinic Geriatrics Unit (Grenoble Alpes University Hospital, Grenoble, France), from January 1, 2017, to December 31, 2018, were included. Patient data and scores were retrieved from hospital archives, and the results of the two tests of interest, MMSE and the CFT-30, were analyzed. RESULTS We included 214 patients aged ≥75 years. The mean ± SD age was 86.4 ± 5.6 years, and 68.7% were female. A strongly positive, significant correlation was seen between the CFT-30 and MMSE (r = 0.73, P < 0.001) scores. The total scores obtained by these two tests were identical (t = 1.22, P = 0.22). CONCLUSION CFT-30 is a good complement to the tools usually used in the investigation of cognitive impairments in older people. In addition to its metrological qualities, the standardized and normalized CFT-30 is extremely simple and very fast to use.
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Affiliation(s)
- Noureddine Bouati
- Hospital-University Clinic Geriatrics Unit, Grenoble Alpes University Hospital, Grenoble, France
| | - Sabine Drevet
- Hospital-University Clinic Geriatrics Unit, Grenoble Alpes University Hospital, Grenoble, France.,OrthoGeriatric Unit, Grenoble Alpes University Hospital, Grenoble, France.,Clinic of Geriatric Medicine, Grenoble Alpes University, Grenoble, France
| | - Nabil Zerhouni
- Hospital-University Clinic Geriatrics Unit, Grenoble Alpes University Hospital, Grenoble, France
| | - Catherine Bioteau
- OrthoGeriatric Unit, Grenoble Alpes University Hospital, Grenoble, France
| | - Nathalie Mitha
- Hospital-University Clinic Geriatrics Unit, Grenoble Alpes University Hospital, Grenoble, France
| | - Gaëtan Gavazzi
- Hospital-University Clinic Geriatrics Unit, Grenoble Alpes University Hospital, Grenoble, France.,Research and Studies Group of the Inflammatory Process (GREPI) EA 7408, Grenoble Alpes University, Grenoble, France
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29
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Paz-Graniel I, Babio N, Becerra-Tomás N, Toledo E, Camacho-Barcia L, Corella D, Castañer-Niño O, Romaguera D, Vioque J, Alonso-Gómez ÁM, Wärnberg J, Martínez JA, Serra-Majem L, Estruch R, Tinahones FJ, Fernandez-Aranda F, Lapetra J, Pintó X, Tur JA, García-Rios A, Bueno-Cavanillas A, Gaforio JJ, Matía-Martín P, Daimiel L, Sánchez VM, Vidal J, Prieto-Sanchez L, Ros E, Razquin C, Mestres C, Sorli JV, Cuenca-Royo AM, Rios A, Torres-Collado L, Vaquero-Luna J, Pérez-Farinós N, Zulet MA, Sanchez-Villegas A, Casas R, Bernal-Lopez MR, Santos-Lozano JM, Corbella X, Mateos D, Buil-Cosiales P, Jiménez-Murcia S, Fernandez-Carrion R, Forcano-Gamazo L, López M, Sempere-Pascual MÁ, Moreno-Rodriguez A, Gea A, de la Torre-Fornell R, Salas-Salvadó J. Association between coffee consumption and total dietary caffeine intake with cognitive functioning: cross-sectional assessment in an elderly Mediterranean population. Eur J Nutr 2020; 60:2381-2396. [PMID: 33125576 DOI: 10.1007/s00394-020-02415-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 10/13/2020] [Indexed: 01/25/2023]
Abstract
PURPOSE Coffee is rich in compounds such as polyphenols, caffeine, diterpenes, melanoidins and trigonelline, which can stimulate brain activity. Therefore, the possible association of coffee consumption with cognition is of considerable research interest. In this paper, we assess the association of coffee consumption and total dietary caffeine intake with the risk of poor cognitive functioning in a population of elderly overweight/obese adults with metabolic syndrome (MetS). METHODS PREDIMED-plus study participants who completed the Mini-Mental State Examination test (MMSE) (n = 6427; mean age = 65 ± 5 years) or a battery of neuropsychological tests were included in this cross-sectional analysis. Coffee consumption and total dietary caffeine intake were assessed at baseline using a food frequency questionnaire. Logistic regression models were fitted to evaluate the association between total, caffeinated and decaffeinated coffee consumption or total dietary caffeine intake and cognitive impairment. RESULTS Total coffee consumers and caffeinated coffee consumers had better cognitive functioning than non-consumers when measured by the MMSE and after adjusting for potential confounders (OR 0.63; 95% CI 0.44-0.90 and OR 0.56; 95% CI 0.38-0.83, respectively). Results were similar when cognitive performance was measured using the Clock Drawing Test (CDT) and Trail Making Test B (TMT-B). These associations were not observed for decaffeinated coffee consumption. Participants in the highest tertile of total dietary caffeine intake had lower odds of poor cognitive functioning than those in the reference tertile when screened by the MMSE (OR 0.64; 95% CI 0.47-0.87) or other neurophysiological tests evaluating a variety of cognitive domains (i.e., CDT and TMT-A). CONCLUSIONS Coffee consumption and total dietary caffeine intake were associated with better cognitive functioning as measured by various neuropsychological tests in a Mediterranean cohort of elderly individuals with MetS. TRIAL REGISTRATION ISRCTN89898870. Registration date: July 24, 2014.
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Affiliation(s)
- Indira Paz-Graniel
- Department of Biochemistry and Biotechnology, Human Nutrition Unit, Rovira i Virgili University, Reus, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain
| | - Nancy Babio
- Department of Biochemistry and Biotechnology, Human Nutrition Unit, Rovira i Virgili University, Reus, Spain. .,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. .,CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.
| | - Nerea Becerra-Tomás
- Department of Biochemistry and Biotechnology, Human Nutrition Unit, Rovira i Virgili University, Reus, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010, Valencia, Spain
| | - Estefania Toledo
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain
| | - Lucia Camacho-Barcia
- Department of Biochemistry and Biotechnology, Human Nutrition Unit, Rovira i Virgili University, Reus, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.,CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain
| | - Dolores Corella
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Olga Castañer-Niño
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Dora Romaguera
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Jesús Vioque
- CIBER Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid, Spain.,ISABIAL-UMH, Miguel Hernandez University, Alicante, Spain
| | - Ángel M Alonso-Gómez
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Julia Wärnberg
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Nursing, School of Health Sciences, University of Málaga-Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain
| | - J Alfredo Martínez
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Nutrition, Food Science and Physiology, IDISNA, University of Navarra, Pamplona, Spain.,Nutritional Genomics and Epigenomics Group, IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Luís Serra-Majem
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Research Institute of Biomedical and Health Sciences (IUIBS), Preventive Medicine Service, Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, University of Las Palmas de Gran Canaria, Las Palmas, Spain
| | - Ramon Estruch
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, University of Barcelona, Barcelona, Spain
| | - Francisco J Tinahones
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Endocrinology. Biomedical Research Institute of Malaga (IBIMA), Virgen de la Victoria Hospital, University of Málaga, Málaga, Spain
| | - Fernando Fernandez-Aranda
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain
| | - José Lapetra
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Research Unit, Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain
| | - Xavier Pintó
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Lipids and Vascular Risk Unit, Internal Medicine, Bellvitge University Hospital, Hospitalet de Llobregat, Barcelona, Spain
| | - Josep A Tur
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, Palma, Spain.,Research Group on Community Nutrition and Oxidative Stress, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Antonio García-Rios
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Aurora Bueno-Cavanillas
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain.,Department of Preventive Medicine, University of Granada, Granada, Spain
| | - José J Gaforio
- CIBER Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid, Spain.,Departamento de Ciencias de La Salud, Centro de Estudios Avanzados en Olivar y Aceites de Oliva, Universidad de Jaén, Jaén, Spain
| | - Pilar Matía-Martín
- Department of Endocrinology and Nutrition, Health Research Institute of the San Carlos Clinical Hospital (IdISSC), Madrid, Spain
| | - Lidia Daimiel
- Nutritional Genomics and Epigenomics Group , IMDEA Food, CEI UAM + CSIC, Madrid, Spain
| | - Vicente Martín Sánchez
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Institute of Biomedicine (IBIOMED), University of León, León, Spain
| | - Josep Vidal
- CIBER Diabetes and Associated Metabolic Diseases (CIBERDEM), Carlos III Health Institute (ISCIII), Madrid, Spain.,Department of Endocrinology, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clínic, University of Barcelona, Barcelona, Spain
| | | | - Emilio Ros
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Lipid Clinic, Department of Endocrinology and Nutrition, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Cristina Razquin
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain
| | - Cristina Mestres
- Joan XXIII University Hospital, Tarragona, Spain.,Horts de Miró Health Center, Reus, Spain
| | - José V Sorli
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Aida M Cuenca-Royo
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Integrative Pharmacology and Systems Neurosciences (FINS), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Angel Rios
- Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, Palma, Spain
| | - Laura Torres-Collado
- CIBER Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid, Spain.,ISABIAL-UMH, Miguel Hernandez University, Alicante, Spain
| | - Jessica Vaquero-Luna
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Napoleon Pérez-Farinós
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Public Health, School of Medicine, University of Malaga-Biomedical Research Institute of Malaga (IBIMA), Málaga, Spain
| | - M Angeles Zulet
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Nutrition, Food Science and Physiology, IDISNA, University of Navarra, Pamplona, Spain.,Centre for Nutrition Research, Faculty of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Almudena Sanchez-Villegas
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Research Institute of Biomedical and Health Sciences (IUIBS), Preventive Medicine Service, Centro Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, University of Las Palmas de Gran Canaria, Las Palmas, Spain
| | - Rosa Casas
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, University of Barcelona, Barcelona, Spain
| | - M Rosa Bernal-Lopez
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Regional University Hospital of Malaga, Internal Medicine Department , Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain
| | - José Manuel Santos-Lozano
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Research Unit, Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain
| | - Xavier Corbella
- Lipids and Vascular Risk Unit, Internal Medicine, Bellvitge University Hospital, Hospitalet de Llobregat, Barcelona, Spain.,Medicine and Health Science Faculty, Universitat Internacional de Catalunya, Barcelona, Spain
| | - David Mateos
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,CIBER Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid, Spain.,Research Group on Community Nutrition and Oxidative Stress, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Pilar Buil-Cosiales
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain
| | - Susana Jiménez-Murcia
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain
| | - Rebeca Fernandez-Carrion
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Laura Forcano-Gamazo
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Integrative Pharmacology and Systems Neurosciences (FINS), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Meritxell López
- Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases, Palma, Spain
| | | | - Anai Moreno-Rodriguez
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
| | - Alfredo Gea
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Department of Preventive Medicine and Public Health, IdiSNA, University of Navarra, Pamplona, Spain
| | - Rafael de la Torre-Fornell
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain.,Integrative Pharmacology and Systems Neurosciences (FINS), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Jordi Salas-Salvadó
- Department of Biochemistry and Biotechnology, Human Nutrition Unit, Rovira i Virgili University, Reus, Spain. .,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain. .,CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, Madrid, Spain. .,The Sant Joan University Hospital, Human Nutrition Unit, Reus, Spain.
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Cova I, Mele F, Zerini F, Maggiore L, Cucumo V, Brambilla M, Rosa S, Bertora P, Salvadori E, Pomati S, Pantoni L. Neuropsychological screening in the acute phase of cerebrovascular diseases. Acta Neurol Scand 2020; 142:377-384. [PMID: 32687600 DOI: 10.1111/ane.13319] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 06/19/2020] [Accepted: 07/15/2020] [Indexed: 02/01/2023]
Abstract
INTRODUCTION Cognitive impairment is a common and disabling consequence of stroke. Its prevalence, the best way to screen for it in the acute setting, and its relation with premorbid status have not been thoroughly clarified. MATERIALS AND METHODS Ischemic and hemorrhagic stroke patients admitted to our stroke unit underwent a baseline assessment that included a clinical and neuroimaging assessment, two cognitive tests (clock-drawing test, CDT; Montreal Cognitive Assessment-Basic, MoCA-B) and measures of premorbid function (including the Clinical Dementia Rating Scale). A follow-up examination was repeated 3-4 months after the acute event. RESULTS Two hundred and twenty-three patients (52.5% women, mean age ± SD 75.8 years ± 12.3) were evaluated. Prestroke cognitive impairment was present in 91 patients (40.8%). At follow-up, the prevalence of cognitive impairment was 49%, while its incidence among patients who did not have any prestroke cognitive impairment was 38.8%. Of the originally admitted 223 patients (71 were lost to follow-up), only 60 (26.9%) were still cognitively intact at follow-up. On regression analysis, age and baseline CDT were associated with worsening of cognitive status at follow-up. In patients without cognitive impairment at baseline, a cutoff of 23 for MoCA-B and of 8.7 for CDT scores predicted the diagnosis of post-stroke cognitive impairment with sufficient accuracy. DISCUSSION AND CONCLUSION Prestroke and post-stroke cognitive impairment affect a large proportion of patients with stroke. Our findings suggest that a neuropsychological screening during the acute phase might be predictive of the development of post-stroke cognitive impairment.
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Affiliation(s)
- Ilaria Cova
- Neurology Unit Luigi Sacco University Hospital Milan Italy
| | - Francesco Mele
- Neurology Unit Luigi Sacco University Hospital Milan Italy
| | - Federica Zerini
- “Luigi Sacco” Department of Biomedical and Clinical Sciences University of Milan Milan Italy
| | - Laura Maggiore
- Neurology Unit Luigi Sacco University Hospital Milan Italy
| | | | | | - Silvia Rosa
- Neurology Unit Luigi Sacco University Hospital Milan Italy
| | - Pierluigi Bertora
- “Luigi Sacco” Department of Biomedical and Clinical Sciences University of Milan Milan Italy
| | | | - Simone Pomati
- Neurology Unit Luigi Sacco University Hospital Milan Italy
| | - Leonardo Pantoni
- “Luigi Sacco” Department of Biomedical and Clinical Sciences University of Milan Milan Italy
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Saito H, Yamashita M, Endo Y, Mizukami A, Yoshioka K, Hashimoto T, Koseki S, Shimode Y, Kitai T, Maekawa E, Kasai T, Kamiya K, Matsue Y. Cognitive impairment measured by Mini-Cog provides additive prognostic information in elderly patients with heart failure. J Cardiol 2020; 76:350-356. [PMID: 32624300 DOI: 10.1016/j.jjcc.2020.06.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 05/31/2020] [Accepted: 06/07/2020] [Indexed: 12/12/2022]
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Comparison of Performance on the Clock Drawing Test Using Three Different Scales in Dialysis Patients. Behav Neurol 2020; 2020:7963837. [PMID: 33029255 PMCID: PMC7527901 DOI: 10.1155/2020/7963837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 09/08/2020] [Accepted: 09/09/2020] [Indexed: 01/26/2023] Open
Abstract
Background The clock drawing test (CDT) is frequently used to detect changes in cognition. Multiple scales of varying length have been published to assess performance. The aim of this study is to compare the CDT performance measured by three scales among a sample of nondemented patients on renal dialysis and identify the variables that affect performance. Methodology. This is a cross-sectional study performed at the dialysis unit at King Saud University Medical City. Eighty-nine dialysis patients performed the CDT. The CDT was scored by the methods of Rouleau et al. (RCS 10-point), Babins et al. (BCS 18-point), and the MoCA (MCS 3-point). Regression models were used to determine influencing demographic and dialysis variables. Scores were then correlated, and a combined factor analysis of scale components was done. Results Females represented 44.6%, the mean (SD) age was 49.99 (15.49) years, and education duration was 10.29 (5.5) years. Dialysis vintage was 55.81 (62.91) months. The scores for the MCS, RCS, and BCS were 2.18 (1.08), 6.67 (3.07), and 11.8 (5.5), respectively, with significant correlation (P < 0.0001). In all scales, increasing age was associated with a lower score (each P < 0.0001). The scores increased with increasing education (each P < 0.0001). Diabetics had a lower score on both the BCS and MCS by 2.56 (SE 1.2) (P = 0.035) and 0.71 (P = 0.003) points, respectively. However, only age and years of education were significant in the multivariable analysis. In factor analysis, two shared factors appeared between the three scales: hand and number placement and the clock face. Conclusion Age and education influence the performance on the CDT, and factors diverged into executive and visuospatial components. The MCS is likely to yield useful information but should be interpreted as part of the MoCA.
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Rendina A, Drongitis D, Donizetti A, Fucci L, Milan G, Tripodi F, Giustezza F, Postiglione A, Pappatà S, Ferrari R, Bossù P, Angiolillo A, di Costanzo A, Caiazzo M, Vitale E. CD33 and SIGLECL1 Immunoglobulin Superfamily Involved in Dementia. J Neuropathol Exp Neurol 2020; 79:891-901. [PMID: 32647856 DOI: 10.1093/jnen/nlaa055] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/19/2020] [Accepted: 05/25/2020] [Indexed: 11/13/2022] Open
Abstract
Sialic acid-binding immunoglobulin-type lectins, which are predominantly expressed in immune cells, represent a family of immunomodulatory receptors with inhibitory and activating signals, in both healthy and disease states. Genetic factors are important in all forms of dementia, especially in early onset dementia. CD33 was recently recognized as a genetic risk factor for Alzheimer disease (AD). Here, we present a 2-generation family with 4 members, the father and the 3 siblings, characterized by an early form of unusual dementia exhibiting a behavioral variant close to behavioral variant frontotemporal dementia phenotype and severe forms of memory loss suggestive of AD. We analyzed the CD33 gene in this family and identified 10 single nucleotide polymorphisms (SNPs) in a linkage disequilibrium block associated with the disease. We also identified a tag SNP, rs2455069-A>G, in CD33 exon 2 that could be involved with dementia risk. Additionally, we excluded the presence of C9orf72 expansion mutations and other mutations previously associated with sporadic FTD and AD. The tag SNP association was also analyzed in selected sporadic AD patients from the same Southern Italy region. We demonstrate that CD33 and SIGLECL1 have a significantly increased level of expression in these patients.
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Affiliation(s)
- Antonella Rendina
- From the Institute of Biochemistry and Cell Biology (IBBC), National Research Council of Italy (CNR), Naples, Italy
| | - Denise Drongitis
- Department of Biology, University of Naples Federico II, Naples, Italy.,Institute of Genetics and Biophysics (IGB), National Research Council of Italy (CNR), Naples, Italy
| | - Aldo Donizetti
- Department of Biology, University of Naples Federico II, Naples, Italy
| | - Laura Fucci
- Department of Biology, University of Naples Federico II, Naples, Italy
| | | | | | | | - Alfredo Postiglione
- Department of Internal Medicine & Surgery, University of Naples "Federico II", Naples, Italy
| | - Sabina Pappatà
- Institute of Bioimaging and Biostructures, CNR, Naples, Italy
| | - Raffaele Ferrari
- Department of Neurodegenerative Disease, University College London, London, UK
| | - Paola Bossù
- Clinical and Behavioral Neurology, IRCCS Fondazione Santa Lucia, Rome
| | - Antonella Angiolillo
- Centro Ricerca e Formazione in Medicina dell'Invecchiamento (CeRMI), Università degli Studi del Molise, Ospedale Cardarelli, Campobasso, Italy
| | - Alfonso di Costanzo
- Centro Ricerca e Formazione in Medicina dell'Invecchiamento (CeRMI), Università degli Studi del Molise, Ospedale Cardarelli, Campobasso, Italy
| | - Massimiliano Caiazzo
- Department of Pharmaceutics Utrecht, Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands.,Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy
| | - Emilia Vitale
- From the Institute of Biochemistry and Cell Biology (IBBC), National Research Council of Italy (CNR), Naples, Italy
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Ghavidel F, Fadardi JS, Gatto NM, Sedaghat F, Tabibi Z. Feasibility of using a computer-assisted working memory training program for healthy older women. Cogn Process 2020; 21:383-390. [DOI: 10.1007/s10339-020-00975-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 03/25/2020] [Indexed: 02/07/2023]
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Automatic, Qualitative Scoring of the Interlocking Pentagon Drawing Test (PDT) based on U-Net and Mobile Sensor Data. SENSORS 2020; 20:s20051283. [PMID: 32120879 PMCID: PMC7085787 DOI: 10.3390/s20051283] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 02/20/2020] [Accepted: 02/25/2020] [Indexed: 01/22/2023]
Abstract
We implemented a mobile phone application of the pentagon drawing test (PDT), called mPDT, with a novel, automatic, and qualitative scoring method for the application based on U-Net (a convolutional network for biomedical image segmentation) coupled with mobile sensor data obtained with the mPDT. For the scoring protocol, the U-Net was trained with 199 PDT hand-drawn images of 512 × 512 resolution obtained via the mPDT in order to generate a trained model, Deep5, for segmenting a drawn right or left pentagon. The U-Net was also trained with 199 images of 512 × 512 resolution to attain the trained model, DeepLock, for segmenting an interlocking figure. Here, the epochs were iterated until the accuracy was greater than 98% and saturated. The mobile senor data primarily consisted of x and y coordinates, timestamps, and touch-events of all the samples with a 20 ms sampling period. The velocities were then calculated using the primary sensor data. With Deep5, DeepLock, and the sensor data, four parameters were extracted. These included the number of angles (0–4 points), distance/intersection between the two drawn figures (0–4 points), closure/opening of the drawn figure contours (0–2 points), and tremors detected (0–1 points). The parameters gave a scaling of 11 points in total. The performance evaluation for the mPDT included 230 images from subjects and their associated sensor data. The results of the performance test indicated, respectively, a sensitivity, specificity, accuracy, and precision of 97.53%, 92.62%, 94.35%, and 87.78% for the number of angles parameter; 93.10%, 97.90%, 96.09%, and 96.43% for the distance/intersection parameter; 94.03%, 90.63%, 92.61%, and 93.33% for the closure/opening parameter; and 100.00%, 100.00%, 100.00%, and 100.00% for the detected tremor parameter. These results suggest that the mPDT is very robust in differentiating dementia disease subtypes and is able to contribute to clinical practice and field studies.
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Abstract
Background & objectives: There is a paucity of literature on the cognitive profiles of vascular dementia (VaD) in India. The current study was undertaken to investigate the pattern of cognitive deficits in patients with VaD. Methods: Fifty patients fulfilling the Diagnostic and Statistical Manual of Mental Disorders-IV criteria of dementia and National Institute of Neurological Disorders and Stroke - Association Internationale pour la Recherche et l'Enseignement en Neurosciences criteria for VaD were assessed using Mini Mental State Examination, Kolkata Cognitive Screening Battery and other relevant tests including magnetic resonance imaging of brain. Results: Twenty patients had small vessel dementia, whereas the least common was haemorrhagic dementia in four patients. In patients with small vessel dementia, apart from memory, all patients had problem in attention and executive function, whereas 12 patients had visuoconstructional deficit and eight patients had language problem. In a total of 12 patients with large vessel dementia, apart from memory, executive dysfunction and visuoconstructional deficit were noted in 10 patients, whereas attention deficit was noted in eight patients. Attention was found to be more involved in small-vessel dementia than large-vessel dementia though all had memory impairment (P<0.01). Interpretation & conclusions: Small vessel dementia was the commonest subtype of VaD in our study. Memory, attention and executive functions were predominantly affected in patients with VaD. Attention was significantly more involved in small vessel dementia than large vessel dementia. Further studies with large sample size need to be done in different regions of the country.
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Affiliation(s)
| | - Jacky Ganguly
- Department of Neurology, Medical College, Kolkata, India
| | - Sandip Pal
- Department of Neurology, Medical College, Kolkata, India
| | - Malay Ghosal
- Department of Psychiatry, Medical College, Kolkata, India
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Tripathi RK, Verma Y, Srivastava A, Shukla TS, Usman K, Ali W, Tiwari SC. Usefulness of clock-drawing test in Indian older adults with diabetes mellitus. Indian J Psychiatry 2020; 62:59-65. [PMID: 32001932 PMCID: PMC6964444 DOI: 10.4103/psychiatry.indianjpsychiatry_62_18] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 10/17/2019] [Accepted: 11/04/2019] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Clock-drawing test (CDT) is a simple, quick, and bedside cognitive screening test which measures different cognitive domains but has some limitations. The aim of this study was to examine the usefulness of CDT for Indian older adult based on a part of an ICMR-funded research project, New Delhi, India. MATERIALS AND METHODS Sample comprised seventy participants (38 controls and 32 cases) aged 60 years and above included according to the inclusion/exclusion criteria in a consecutive series. Participants, who gave written informed consent, residing permanently in the area of Chowk, Lucknow, constituted the study sample. Semistructured sociodemographic details and medical history pro forma, socioeconomic status scale, General Health Questionnaire-12 (GHQ-12), CDT, and Hindi cognitive screening test (HCST) were administered. Biochemical investigations were carried out, and blood glucose level (fasting ≤100 mg/dl and postprandial ≤140 mg/dl) was considered for having diabetes mellitus (DM). The participants were categorized into two groups: (1) case: participants with DM only and (2) control: participants without discernible abnormality of physical illness and GHQ negative. Data were analyzed using percentages, t-test, the Chi-square test, sensitivity, and specificity. RESULTS About 71.05% participants in control and 81.25% in the case group have cognitive impairment on CDT. Significantly higher illiterates (P < 0.05) were found to be significantly more cognitively impaired on HCST. CDT has a high level of sensitivity (0.71) and low specificity (0.23) when compared with HCST. CONCLUSION CDT had screening bias to Indian older adults as a higher number of literates (almost double) and illiterates (four times) were found to be cognitively impaired compared to on HCST. Usefulness of CDT to screen Indian older adults for cognitive impairment is debatable.
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Affiliation(s)
- Rakesh Kumar Tripathi
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Yashi Verma
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Anamika Srivastava
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Tanu Shree Shukla
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Kauser Usman
- Department of Medicine, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Wahid Ali
- Department of Pathology, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Sarvada Chandra Tiwari
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
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Raman P, Khy Ching Y, Sivagurunathan PD, Ramli N, Mohd. Khalid KH. The Association Between Visual Field Reliability Indices and Cognitive Impairment in Glaucoma Patients. J Glaucoma 2019; 28:685-690. [DOI: 10.1097/ijg.0000000000001269] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Hwang AB, Boes S, Nyffeler T, Schuepfer G. Validity of screening instruments for the detection of dementia and mild cognitive impairment in hospital inpatients: A systematic review of diagnostic accuracy studies. PLoS One 2019; 14:e0219569. [PMID: 31344048 PMCID: PMC6657852 DOI: 10.1371/journal.pone.0219569] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 06/26/2019] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION As the population ages, Alzheimer's disease and other subtypes of dementia are becoming increasingly prevalent. However, in recent years, diagnosis has often been delayed or not made at all. Thus, improving the rate of diagnosis has become an integral part of national dementia strategies. Although screening for dementia remains controversial, the case is strong for screening for dementia and other forms of cognitive impairment in hospital inpatients. For this reason, the objective of this systematic review was to provide clinicians, who wish to implement screening, an up-to-date choice of cognitive tests with the most extensive evidence base for the use in elective hospital inpatients. METHODS For this systematic review, PubMed, PsycINFO and Cochrane Library were searched by using a multi-concept search strategy. The databases were accessed on April 10, 2019. All cross-sectional studies that utilized brief, multi-domain cognitive tests as index test and a reference standard diagnosis of dementia or mild cognitive impairment as comparator were included. Only studies conducted in the hospital setting, sampling from unselected, elective inpatients older than 64 were considered. RESULTS Six studies met the inclusion criteria, with a total of 2112 participants. Diagnostic accuracy data for the Six-Item Cognitive Impairment Test, Cognitive Performance Scale, Clock-Drawing Test, Mini-Mental Status Examination, and Time & Change test were extracted and descriptively analyzed. Clinical and methodological heterogeneity between the studies precluded performing a meta-analysis. DISCUSSION This review found only a small number of instruments and was not able to recommend a single best instrument for use in a hospital setting. Although it was not possible to estimate the pooled operating characteristics, the included description of instrument characteristics, the descriptive analysis of performance measures, and the critical evaluation of the reporting studies may contribute to clinician's choice of the screening instrument that fits best their purpose.
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Affiliation(s)
- Aljoscha Benjamin Hwang
- Clinic for Neurology and Neurorehabilitation, Cantonal Hospital Lucerne, Lucerne, Switzerland
- Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland
| | - Stefan Boes
- Department of Health Sciences and Health Policy, University of Lucerne, Lucerne, Switzerland
| | - Thomas Nyffeler
- Clinic for Neurology and Neurorehabilitation, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | - Guido Schuepfer
- Staff Medicine, Cantonal Hospital Lucerne, Lucerne, Switzerland
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Supasitthumrong T, Herrmann N, Tunvirachaisakul C, Shulman K. Clock drawing and neuroanatomical correlates: A systematic review. Int J Geriatr Psychiatry 2019; 34:223-232. [PMID: 30370637 DOI: 10.1002/gps.5013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 10/05/2018] [Indexed: 01/19/2023]
Abstract
OBJECTIVE The popular clock drawing test (CDT) is easy to administer, acceptable to patients, and has excellent psychometric properties. Although it has been used primarily as a cognitive screening test, many studies have attempted to establish the CDT's ability to localize specific brain lesions or pathology. This systematic review aimed to summarize the evidence on the neuroanatomical correlates of the CDT. METHODS Using PRISMA guidelines, the authors systematically reviewed the evidence on neuroanatomical correlates of clock drawing by a systematic search in six databases (Pubmed, CINHL, PsychINFO, HealthStar, Embase, and Web of Science) until January 2018. Studies were included if they reported CDT correlations with anatomical brain lesions documented by neuroimaging. RESULTS Forty-five papers met inclusion criteria. Thirty-one studies identified distinct areas of neuroanatomical correlates of CDT utilizing different scoring methods and imaging techniques. Nine articles reported on the degree of white matter hyperintensities that correlated with lower scores on CDT and the severity of cognitive deficits. Five articles focused on postacute cerebrovascular accidents correlated with CDT performance. A variety of different anatomical lesions, located in all areas of the brain, were associated with abnormalities on the CDT. CONCLUSIONS The CDT, regardless of scoring method and population studied, was not associated with any consistent, specific brain localization. This systematic review supports the use of the CDT as a cognitive screening test rather than a method of localizing brain lesions.
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Affiliation(s)
- Thitiporn Supasitthumrong
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Nathan Herrmann
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Hurvitz Brain Sciences Research Program, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | | | - Kenneth Shulman
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Hurvitz Brain Sciences Research Program, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Duro D, Freitas S, Tábuas-Pereira M, Santiago B, Botelho MA, Santana I. Discriminative capacity and construct validity of the Clock Drawing Test in Mild Cognitive Impairment and Alzheimer's disease. Clin Neuropsychol 2018; 33:1159-1174. [PMID: 30422076 DOI: 10.1080/13854046.2018.1532022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Objectives: The aim of this study was to analyze the psychometric and diagnostic properties of the Clock Drawing Test (CDT), scored according to the Babins, Rouleau, and Cahn scoring systems, for Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) screening, and develop corresponding cutoff scores. Additionally, we assessed the construct validity of the CDT through exploratory and confirmatory factor analysis. Methods: We developed a cross-sectional study of ambulatory MCI and AD patients, divided in two clinical groups (450 MCI and 250 mild AD patients) and a normal control group (N = 400). All participants were assessed with the CDT, Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) for convergent validity. Results: The selected scoring systems presented adequate validity and reliability values. The proposed cutoff scores showed 60 to 65% sensitivity and 58 to 62% specificity to identify MCI patients. The corresponding values for AD were 84 to 90% sensitivity and 76 to 78% specificity. Exploratory and confirmatory factor analysis revealed that the Babins scoring system had good construct validity and allowed us to propose a three-factor model for this system. Conclusions: Our results confirmed the complexity of the CDT and support it as a cognitive screening instrument particularly sensitive to AD. The use of the CDT with MCI patients should be interpreted with more caution due to the lower sensitivity and specificity for milder forms of cognitive impairment.
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Affiliation(s)
- Diana Duro
- Neurology Department, Centro Hospitalar e Universitário de Coimbra , Coimbra , Portugal.,Faculty of Medicine, University of Coimbra , Coimbra , Portugal.,Center for Research in Neuropsychology and Cognitive and Behavioral Intervention, University of Coimbra , Coimbra , Portugal
| | - Sandra Freitas
- Center for Research in Neuropsychology and Cognitive and Behavioral Intervention, University of Coimbra , Coimbra , Portugal.,Center for Neuroscience and Cell Biology, University of Coimbra , Coimbra , Portugal
| | - Miguel Tábuas-Pereira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra , Coimbra , Portugal.,Faculty of Medicine, University of Coimbra , Coimbra , Portugal
| | - Beatriz Santiago
- Neurology Department, Centro Hospitalar e Universitário de Coimbra , Coimbra , Portugal
| | | | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra , Coimbra , Portugal.,Faculty of Medicine, University of Coimbra , Coimbra , Portugal
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de Noronha ÍFC, Barreto SDS, Ortiz KZ. The influence of education on performance of adults on the Clock Drawing Test. Dement Neuropsychol 2018; 12:61-67. [PMID: 29682235 PMCID: PMC5901251 DOI: 10.1590/1980-57642018dn12-010009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The Clock Drawing Test (CDT) is an important instrument for screening individuals suspected of having cognitive impairment.
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Affiliation(s)
| | - Simone Dos Santos Barreto
- Adjoined Professor. Department of Specific Training in Speech, Language and Hearing Sciences - Universidade Federal Fluminense, RJ, Brazil
| | - Karin Zazo Ortiz
- Associate Professor. Department of Speech, Language and Hearing Sciences - Universidade Federal de São Paulo
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Palsetia D, Rao GP, Tiwari SC, Lodha P, De Sousa A. The Clock Drawing Test versus Mini-mental Status Examination as a Screening Tool for Dementia: A Clinical Comparison. Indian J Psychol Med 2018; 40:1-10. [PMID: 29403122 PMCID: PMC5795671 DOI: 10.4103/ijpsym.ijpsym_244_17] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
There is a growing incidence of dementia patients in the community, and with this growth, there is need for rapid, valid, and easily administrable tests for the screening of dementia and mild cognitive impairment in the community. This review looks at the two most commonly used tests in dementia screening, namely, the clock drawing test (CDT) and the mini-mental status examination (MMSE). Both these tests have been used in dementia screening over the past three decades and have been the subject of scrutiny of various studies, reviews, and meta-analysis. Both these tests are analyzed on their ability to assess dementia and screen for it in the community, general practice and general hospital settings. The methods of administration and scoring of each test are discussed, and their advantages and disadvantages are explained. There is also a direct comparison made between the MMSE and CDT in dementia screening. Future research needs with these tests are also elucidated.
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Affiliation(s)
- Delnaz Palsetia
- Department of Psychiatry, Asha Hospital, Hyderabad, Telangana, India
| | - G. Prasad Rao
- Department of Psychiatry, Asha Hospital, Hyderabad, Telangana, India
| | - Sarvada C. Tiwari
- Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India
| | - Pragya Lodha
- Department of Research Assistant, Desousa Foundation, Mumbai, Maharashtra, India
| | - Avinash De Sousa
- Department of Psychiatry, Lokmanya Tilak Municipal Medical College, Mumbai, Maharashtra, India
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The Persian Version of the "Life Satisfaction Scale": Construct Validity and Test-Re-Test Reliability among Iranian Older Adults. J Cross Cult Gerontol 2017; 33:121-134. [PMID: 29230605 PMCID: PMC5845598 DOI: 10.1007/s10823-017-9340-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
After forward-backward translation, the LSS was administered to 334 Persian speaking, cognitively healthy elderly aged 60 years and over recruited through convenience sampling. To analyze the validity of the model’s constructs and the relationships between the constructs, a confirmatory factor analysis followed by PLS analysis was performed. The Construct validity was further investigated by calculating the correlations between the LSS and the “Short Form Health Survey” (SF-36) subscales measuring similar and dissimilar constructs. The LSS was re-administered to 50 participants a month later to assess the reliability. For the eight-factor model of the life satisfaction construct, adequate goodness of fit between the hypothesized model and the model derived from the sample data was attained (positive and statistically significant beta coefficients, good R-squares and acceptable GoF). Construct validity was supported by convergent and discriminant validity, and correlations between the LSS and SF-36 subscales. Minimum Intraclass Correlation Coefficient level of 0.60 was exceeded by all subscales. Minimum level of reliability indices (Cronbach’s α, composite reliability and indicator reliability) was exceeded by all subscales. The Persian-version of the Life Satisfaction Scale is a reliable and valid instrument, with psychometric properties which are consistent with the original version.
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Boston Naming Test (BNT) original, Brazilian adapted version and short forms: normative data for illiterate and low-educated older adults. Int Psychogeriatr 2017; 29:825-833. [PMID: 27876103 DOI: 10.1017/s1041610216001952] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND The aims of this study were (1) to describe and compare the performance of illiterate and low-educated older adults, without evidence of cognitive impairment, on different versions of the Boston Naming Test (BNT) original, Brazilian adapted, abbreviated 30-item (even and odd) and 15-item from the CERAD (Consortium to Establish a Registry for Alzheimer's Disease) battery; (2) to compare performance on the original versus adapted versions of the BNT. METHODS A total of 180 healthy older adults (60 years or older) were stratified according to educational level (0, 1-2, and 3-4 years), and age (60-69, 70-79, and ≥ 80 years). The protocol comprised the following instruments: Mini-Mental State Examination (MMSE), Brief Cognitive Screening Battery (BCSB), Functional Activities Questionnaire (FAQ), Geriatric Depression Scale (GDS), and the BNT. RESULTS The illiterate participants had poorer performance than the educated participants. The performance of the two educated groups was similar on all versions of the BNT. A higher number of correct responses were observed on the adapted BNT than on the original BNT in all three education groups. CONCLUSIONS The adapted BNT appears to be the most suitable for use in the low-educated Brazilian population. The present study provided normative data for low-educated elderly on several different versions of the BNT, which may be helpful in diagnosing naming deficits among elderly in these strata of the population.
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Spenciere B, Alves H, Charchat-Fichman H. Scoring systems for the Clock Drawing Test: A historical review. Dement Neuropsychol 2017; 11:6-14. [PMID: 29213488 PMCID: PMC5619209 DOI: 10.1590/1980-57642016dn11-010003] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The Clock Drawing Test (CDT) is a simple neuropsychological screening instrument
that is well accepted by patients and has solid psychometric properties. Several
different CDT scoring methods have been developed, but no consensus has been
reached regarding which scoring method is the most accurate. This article
reviews the literature on these scoring systems and the changes they have
undergone over the years. Historically, different types of scoring systems
emerged. Initially, the focus was on screening for dementia, and the methods
were both quantitative and semi-quantitative. Later, the need for an early
diagnosis called for a scoring system that can detect subtle errors, especially
those related to executive function. Therefore, qualitative analyses began to be
used for both differential and early diagnoses of dementia. A widely used
qualitative method was proposed by Rouleau et al. (1992). Tracing the historical
path of these scoring methods is important for developing additional scoring
systems and furthering dementia prevention research.
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Affiliation(s)
- Bárbara Spenciere
- BsC, Department of Psychology, Pontifical Catholic University of Rio de Janeiro RJ - Brazil
| | - Heloisa Alves
- PhD, Department of Psychology, Pontifical Catholic University of Rio de Janeiro RJ - Brazil
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Grima R, Franklin S. Usefulness of investigating error profiles in diagnosis of naming impairments. INTERNATIONAL JOURNAL OF LANGUAGE & COMMUNICATION DISORDERS 2017; 52:214-226. [PMID: 27349587 DOI: 10.1111/1460-6984.12266] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 04/12/2016] [Indexed: 06/06/2023]
Abstract
BACKGROUND Word-retrieval difficulties are commonly experienced by people with aphasia (PwA) and also by typically ageing persons. Differentiation between true naming impairments and naming difficulties found in healthy persons may, therefore, be challenging. AIMS To investigate the extent to which the Maltese adaptation of the Boston Naming Test (BNT) can identify people with lexical retrieval difficulties and to differentiate them from people with unimpaired word finding. METHODS & PROCEDURES Naming performance of a group of PwA was compared with the performance of a control group. Performance on the Maltese adaptation of the BNT was investigated in terms of scores, range of scores and error profiles of the two groups. OUTCOMES & RESULTS All PwA scored below the mean score of the controls, indicating that persons who scored above the mean score may be considered as unimpaired. However, a number of the controls obtained very low scores that overlapped with the scores obtained by the PwA. This indicated that scores alone cannot be used to differentiate between impaired and unimpaired people. Some types of errors were only produced by people with impaired naming, and did not appear at all in error profiles of unimpaired individuals. CONCLUSIONS & IMPLICATIONS Mild-moderate anomic impairments may be missed if naming impairment is assessed and diagnosed using a cut-off score. In order to differentiate between people with impaired and unimpaired naming, it is necessary to look at error profiles, apart from the number of errors, as the presence of atypical errors may be an important indicator of naming impairments.
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Affiliation(s)
- Ritienne Grima
- Department of Communication Therapy, Faculty of Health Sciences, University of Malta, L-Imsida, Malta
| | - Sue Franklin
- Department of Clinical Therapies, Faculty of Education and Health Sciences, University of Limerick, Limerick, Ireland
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Tanjani PT, Azadbakht M, Garmaroudi G, Sahaf R, Fekrizadeh Z. Validity and Reliability of Health Promoting Lifestyle Profile II in the Iranian Elderly. Int J Prev Med 2016; 7:74. [PMID: 27280010 PMCID: PMC4882969 DOI: 10.4103/2008-7802.182731] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2015] [Accepted: 02/02/2016] [Indexed: 11/23/2022] Open
Abstract
Background: With increasing age, the prevalence of chronic diseases increases. Since health-promoting behaviors (HPB) are considered a basic way of preventing diseases, especially chronic diseases, it is important to assess HPB. This study examines the validity and reliability of the Health Promoting Lifestyle Profile II (HPLP-II). Methods: This is a cross-sectional study which is conducted on 502 elderly individuals aged 60 and over in Tehran, Iran. In order to determine the validity, content and construct validity were used. The content validity index (CVI) was used to assess the content validity and to assess construct validity, confirmatory factor analysis (CFA), and item-total correlations were employed. For reliability, test-retest analysis was used, and the internal consistency of the HPLP-II was confirmed by Cronbach's alpha. For data analysis, SPSS-18 and Amos-7 software was used. Results: The mean age of the subjects was 66.3 ± 5.3 years. The CVI for the revised HPLP-II and all its subscales was higher than 0.82. The CFA confirmed a six-factor model aligned with the original HPLP-II. Pearson correlation coefficients between the revised HPLP-II and their items were in range of 0.27–0.65. Cronbach's alpha of the revised HPLP-II was obtained as 0.78 and for their subscales were in the range of 0.67–0.84. Intraclass correlation coefficient was obtained 0.79 (95% confidence interval: 0.59–0.86, P < 0.001). Conclusions: The Iranian HPLP-II scale is an appropriate tool for assessing HPBs of the Iranian elderly.
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Affiliation(s)
- Parisa Taheri Tanjani
- Department of Internal Medicine, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mojtaba Azadbakht
- Department of Gerontology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Gholamreza Garmaroudi
- Department of Health Promotion and Education, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Robab Sahaf
- Department of Gerontology, School of Rehabilitation, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Zohreh Fekrizadeh
- Department of Health Promotion and Education, School of Public Health, Arak University of Medical Sciences, Arak, Iran
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de Paula JJ, Bicalho MA, Ávila RT, Cintra MTG, Diniz BS, Romano-Silva MA, Malloy-Diniz LF. A Reanalysis of Cognitive-Functional Performance in Older Adults: Investigating the Interaction Between Normal Aging, Mild Cognitive Impairment, Mild Alzheimer's Disease Dementia, and Depression. Front Psychol 2016; 6:2061. [PMID: 26858666 PMCID: PMC4727063 DOI: 10.3389/fpsyg.2015.02061] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 12/31/2015] [Indexed: 12/12/2022] Open
Abstract
Depressive symptoms are associated with cognitive-functional impairment in normal aging older adults (NA). However, less is known about this effect on people with mild Cognitive Impairment (MCI) and mild Alzheimer's disease dementia (AD). We investigated this relationship along with the NA-MCI-AD continuum by reanalyzing a previously published dataset. Participants (N = 274) underwent comprehensive neuropsychological assessment including measures of Executive Function, Language/Semantic Memory, Episodic Memory, Visuospatial Abilities, Activities of Daily Living (ADL), and the Geriatric Depression Scale. MANOVA, logistic regression and chi-square tests were performed to assess the association between depression and cognitive-functional performance in each group. In the NA group, depressed participants had a lower performance compared to non-depressed participants in all cognitive and functional domains. However, the same pattern was not observed in the MCI group or in AD. The results suggest a progressive loss of association between depression and worse cognitive-functional performance along the NA-MCI-AD continuum.
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Affiliation(s)
- Jonas J de Paula
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Department of Psychology, Faculdade de Ciências Médicas de Minas GeraisBelo Horizonte, Brazil
| | - Maria A Bicalho
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Department of Internal Medicine, Faculdade de Medicina, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Reference Center for Geriatrics Instituto Jenny de Andrade Faria, Universidade Federal de Minas GeraisBelo Horizonte, Brazil
| | - Rafaela T Ávila
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Reference Center for Geriatrics Instituto Jenny de Andrade Faria, Universidade Federal de Minas GeraisBelo Horizonte, Brazil
| | - Marco T G Cintra
- Reference Center for Geriatrics Instituto Jenny de Andrade Faria, Universidade Federal de Minas Gerais Belo Horizonte, Brazil
| | - Breno S Diniz
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Department of Mental Health, Faculdade de Medicina, Universidade Federal de Minas GeraisBelo Horizonte, Brazil
| | - Marco A Romano-Silva
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Department of Mental Health, Faculdade de Medicina, Universidade Federal de Minas GeraisBelo Horizonte, Brazil
| | - Leandro F Malloy-Diniz
- Faculdade de Medicina, Instituto Nacional de Ciência e Tecnologia de Medicina Molecular, Universidade Federal de Minas GeraisBelo Horizonte, Brazil; Department of Mental Health, Faculdade de Medicina, Universidade Federal de Minas GeraisBelo Horizonte, Brazil
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Beckert M, Loureiro F, Menta C, Mello EF, Nogueira EL, von Gunten A, Gomes I. Performance of low-educated elders with depression on Addenbrooke's Cognitive Examination-Revised (ace-r) test. Dement Neuropsychol 2016; 10:19-25. [PMID: 29213426 PMCID: PMC5674909 DOI: 10.1590/s1980-57642016dn10100004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Along with cognitive disorders, depression has been a concern for mental health services due to its highly debilitating effect on the functioning and quality of life of the elderly. However, there is still little understanding of the cognitive alterations resulting from depression or of the difficult differential diagnosis with mild cognitive impairment (MCI). It is known that performance on cognitive tests is strongly influenced by education but few studies have been conducted involving low-educated populations. Objective To evaluate the performance of elders with low education and no dementia on Addenbrooke's Cognitive Examination-Revised (ACE-R) test and its cognitive domains, and compare patients with Current Major Depressive Episode (CMDE) against those without depressive symptoms. Methods A retrospective, cross-sectional analytical study was conducted based on medical files of patients treated at the Cerebral Aging Clinic of the Hospital São Lucas of the PUCRS. The study included 116 individuals with low education (< 8 years of education) aged between 60 and 84 (69.6 ± 6.4) years, with MCDE (N = 41) and controls (N = 75). Results No significant difference was observed between control and MCDE groups in median scores on the ACE-R, Mini-Mental State Examination, and the five cognitive domains. There was also no difference between the groups on separate analyses of results on the clock drawing test, the categorical verbal and phonological fluency test, and the naming test. Conclusion The results of this study showed that depressive symptoms did not influence scores on the ACE-R tests conducted in elders with low education.
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Affiliation(s)
- Michele Beckert
- Psychologist, MD, Department of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
| | - Fernanda Loureiro
- Speech Therapist, MD, PhD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
| | - Caroline Menta
- Psychiatrist, MD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
| | - Elisa Fasolin Mello
- Psychiatrist, MD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
| | - Eduardo L Nogueira
- Psychiatrist, MD, PhD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
| | - Armin von Gunten
- Psychiatrist, MD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil, and Old-Age Psychiatric Service, Department of Psychiatry, Lausanne University Hospital, Switzerland
| | - Irênio Gomes
- Neurologist, MD, PhD, Institute of Geriatrics and Gerontology, Pontifical Catholic University of Rio Grande do Sul, RS, Brazil
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