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Zhai L, Yang Y, Zhang J, Hou W, Yang Y, Ding D, Li C, Zhu Y. Association between cognitive dysfunction and diabetes in patients over 65 years old: a cross-sectional study using propensity score matching. J Rehabil Med 2024; 56:jrm18372. [PMID: 38380813 PMCID: PMC10896218 DOI: 10.2340/jrm.v56.18372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 01/15/2024] [Indexed: 02/22/2024] Open
Abstract
OBJECTIVES To investigate the association between diabetes and cognitive dysfunction in the elderly population, and examine the impact of cognitive dysfunction on level of activities of daily living (ADL) in patients with diabetes. METHODS Data analysis was conducted on 2,951 individuals aged over 65 years from the Chinese Longitudinal Healthy Longevity Survey cohort. Propensity score matching was utilized to mitigate selection bias. Multivariate binary logistic regression was performed to analyse the association between diabetes and cognitive dysfunction in the study subjects. In addition, the relationship between ADL and cognitive function in patients with diabetes was analysed using the Wilcoxon rank-sum test. RESULTS A significant association (p = 0.017) was found between diabetes and the occurrence of cognitive dysfunction in older adults. Subgroup analyses revealed that diabetes patients with cognitive dysfunction exhibited a worse ADL dependence compared with those without cognitive dysfunction (p < 0.001). CONCLUSION These findings indicate that diabetes is associated with cognitive dysfunction in older adults. Meanwhile, there is an association between cognitive impairment and ADL level in subjects with diabetes. As such, healthcare professionals should pay close attention to the occurrence of cognitive dysfunction and ADL decline during diagnosis and treatment, and proactive prevention and intervention strategies should be implemented.
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Affiliation(s)
- Liwen Zhai
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Yao Yang
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Jun Zhang
- Department of Rehabilitation Medicine, Hainan Cancer Hospital, Haikou, Hainan, China
| | - Weiqian Hou
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Yujie Yang
- School of Rehabilitation Sciences and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Dongfang Ding
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Conghui Li
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China; Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhu
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China.
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García-Bermúdez MY, Vohra R, Freude K, van Wijngaarden P, Martin K, Thomsen MS, Aldana BI, Kolko M. Potential Retinal Biomarkers in Alzheimer's Disease. Int J Mol Sci 2023; 24:15834. [PMID: 37958816 PMCID: PMC10649108 DOI: 10.3390/ijms242115834] [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: 09/01/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
Alzheimer's disease (AD) represents a major diagnostic challenge, as early detection is crucial for effective intervention. This review examines the diagnostic challenges facing current AD evaluations and explores the emerging field of retinal alterations as early indicators. Recognizing the potential of the retina as a noninvasive window to the brain, we emphasize the importance of identifying retinal biomarkers in the early stages of AD. However, the examination of AD is not without its challenges, as the similarities shared with other retinal diseases introduce complexity in the search for AD-specific markers. In this review, we address the relevance of using the retina for the early diagnosis of AD and the complex challenges associated with the search for AD-specific retinal biomarkers. We provide a comprehensive overview of the current landscape and highlight avenues for progress in AD diagnosis by retinal examination.
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Affiliation(s)
| | - Rupali Vohra
- Eye Translational Research Unit, Department of Drug Design and Pharmacology, University of Copenhagen, 2100 Copenhagen, Denmark
- Department of Ophthalmology, Copenhagen University Hospital, Rigshospitalet, 2600 Glostrup, Denmark
| | - Kristine Freude
- Group of Stem Cell Models and Embryology, Department of Veterinary and Animal Sciences, University of Copenhagen, 1870 Frederiksberg, Denmark
| | - Peter van Wijngaarden
- Center for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC 3002, Australia
- Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Keith Martin
- Center for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC 3002, Australia
- Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, VIC 3010, Australia
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Maj Schneider Thomsen
- Neurobiology Research and Drug Delivery, Department of Health, Science and Technology, Aalborg University, 9220 Aalborg, Denmark
| | - Blanca Irene Aldana
- Neurometabolism Research Group, Department of Drug Design and Pharmacology, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Miriam Kolko
- Eye Translational Research Unit, Department of Drug Design and Pharmacology, University of Copenhagen, 2100 Copenhagen, Denmark
- Department of Ophthalmology, Copenhagen University Hospital, Rigshospitalet, 2600 Glostrup, Denmark
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Ciudin A, Simó R. New methods for the diagnosis and monitoring of cognitive function in patients with type 2 diabetes. Front Endocrinol (Lausanne) 2022; 13:1024794. [PMID: 36531450 PMCID: PMC9751391 DOI: 10.3389/fendo.2022.1024794] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 11/04/2022] [Indexed: 12/02/2022] Open
Abstract
The presence of type 2 diabetes acts as an accelerator of cognitive impairment (mild cognitive impairment and later dementia), with a significant impact on the management of the disease and its complications. Therefore, it is recommended to perform an annual evaluation of cognitive function in patients with diabetes older than 65 years. Current guidelines still recommend the use of the Minimental State Evaluation Test (MMSE) as screening test, but it has a modest sensitivity and specificity for identifying mild cognitive impairment. This represents an important gap because patients with mild cognitive impairment are at risk of progressing to dementia. The neurocognitive diagnosis is based on complex neuropsychological tests, which require specifically trained personnel and are time consuming, making its routine incorporation into daily clinical practice unfeasible. Therefore, at present there are no reliable biomarkers to identify patients with type 2 diabetes at increased risk of developing cognitive impairment. Since the brain and the retina have a common embryological origin, our Research Group, has worked over the last 10 years evaluating the usefulness of the retina as a "window" to the brain. We provided evidence that retinal microperimetry is a simple, feasible and useful tool for screening and monitoring cognitive function in patients with type 2 diabetes. We propose a review of actual tests recommended for screening of cognitive impairment as well as an update of new emerging methods, such as retinal microperimetry.
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Affiliation(s)
- Andreea Ciudin
- Endocrinology and Nutrition Department, Hospital Universitari Vall d’Hebron, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain
- Universitat Autónoma de Barcelona, Department of Human Physiology and Inmunology, Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDem), Instituto de Salud Carlos III, Madrid, Spain
| | - Rafael Simó
- Endocrinology and Nutrition Department, Hospital Universitari Vall d’Hebron, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDem), Instituto de Salud Carlos III, Madrid, Spain
- Universitat Autónoma de Barcelona, Department of Medicine, Barcelona, Spain
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4
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Huang CY, Lin YC, Lu YC, Chen CI. Application of Grey Relational Analysis to Predict Dementia Tendency by Cognitive Function, Sleep Disturbances, and Health Conditions of Diabetic Patients. Brain Sci 2022; 12:brainsci12121642. [PMID: 36552102 PMCID: PMC9775556 DOI: 10.3390/brainsci12121642] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/23/2022] [Accepted: 11/25/2022] [Indexed: 12/05/2022] Open
Abstract
Background: The number of elderly diabetic patients has been increasing recently, and these patients have a higher morbidity of dementia than those without diabetes. Diabetes is associated with an increased risk for the development of dementia in elderly individuals, which is a serious health problem. Objectives: The primary aim was to examine whether diabetes is a risk factor for dementia among elderly individuals. The secondary aim was to apply grey theory to integrate the results and how they relate to cognitive impairments in elderly diabetic patients and to predict which participants are at high risk of developing dementia. Methods: Two hundred and twenty patients aged 50 years or older who were diagnosed with diabetes mellitus were recruited. Information on demographics, disease characteristics, activities of daily living, Mini Mental State Examination, sleep quality, depressive symptoms, and health-related quality of life was collected via questionnaires. The grey relational analysis approach was applied to evaluate the relationship between the results and health outcomes. Results: A total of 13.6% of participants had cognitive disturbances, of whom 1.4% had severe cognitive dysfunction. However, with regard to sleep disorders, 56.4% had sleep disturbances of varying degrees from light to severe. Further investigation is needed to address this problem. A higher prevalence of sleep disturbances among diabetic patients translates to a higher degree of depressive symptoms and a worse physical and mental health-related quality of life. Furthermore, based on the grey relational analysis, the grey relation coefficient varies from 0.6217~0.7540. Among the subjects, Participant 101 had the highest value, suggesting a need for immediate medical care. In this study, we observed that 20% of the total participants, for whom the grey relation coefficient was 0.6730, needed further and immediate medical care.
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Affiliation(s)
- Chiung-Yu Huang
- Nursing Department, I-Shou University, Kaohsiung 82445, Taiwan
| | - Yu-Ching Lin
- Department of Family Medicine and Physical Examination, E-Da Hospital, Kaohsiung 82445, Taiwan
| | - Yung-Chuan Lu
- College of Medicine, School of Medicine for International Students, I-Shou University, Kaohsiung 82445, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, E-Da Hospital, Kaohsiung 82445, Taiwan
| | - Chun-I Chen
- Management College, I-Shou University, Kaohsiung 82445, Taiwan
- Correspondence:
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Reuben A, Moffitt TE, Abraham WC, Ambler A, Elliott ML, Hariri AR, Harrington H, Hogan S, Houts RM, Ireland D, Knodt AR, Leung J, Pearson A, Poulton R, Purdy SC, Ramrakha S, Rasmussen LJH, Sugden K, Thorne PR, Williams B, Wilson G, Caspi A. Improving risk indexes for Alzheimer's disease and related dementias for use in midlife. Brain Commun 2022; 4:fcac223. [PMID: 36213312 PMCID: PMC9535507 DOI: 10.1093/braincomms/fcac223] [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: 02/28/2022] [Revised: 06/01/2022] [Accepted: 09/01/2022] [Indexed: 11/07/2022] Open
Abstract
Knowledge of a person’s risk for Alzheimer’s disease and related dementias (ADRDs) is required to triage candidates for preventive interventions, surveillance, and treatment trials. ADRD risk indexes exist for this purpose, but each includes only a subset of known risk factors. Information missing from published indexes could improve risk prediction. In the Dunedin Study of a population-representative New Zealand-based birth cohort followed to midlife (N = 938, 49.5% female), we compared associations of four leading risk indexes with midlife antecedents of ADRD against a novel benchmark index comprised of nearly all known ADRD risk factors, the Dunedin ADRD Risk Benchmark (DunedinARB). Existing indexes included the Cardiovascular Risk Factors, Aging, and Dementia index (CAIDE), LIfestyle for BRAin health index (LIBRA), Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), and risks selected by the Lancet Commission on Dementia. The Dunedin benchmark was comprised of 48 separate indicators of risk organized into 10 conceptually distinct risk domains. Midlife antecedents of ADRD treated as outcome measures included age-45 measures of brain structural integrity [magnetic resonance imaging-assessed: (i) machine-learning-algorithm-estimated brain age, (ii) log-transformed volume of white matter hyperintensities, and (iii) mean grey matter volume of the hippocampus] and measures of brain functional integrity [(i) objective cognitive function assessed via the Wechsler Adult Intelligence Scale-IV, (ii) subjective problems in everyday cognitive function, and (iii) objective cognitive decline measured as residualized change in cognitive scores from childhood to midlife on matched Weschler Intelligence scales]. All indexes were quantitatively distributed and proved informative about midlife antecedents of ADRD, including algorithm-estimated brain age (β's from 0.16 to 0.22), white matter hyperintensities volume (β's from 0.16 to 0.19), hippocampal volume (β's from −0.08 to −0.11), tested cognitive deficits (β's from −0.36 to −0.49), everyday cognitive problems (β's from 0.14 to 0.38), and longitudinal cognitive decline (β's from −0.18 to −0.26). Existing indexes compared favourably to the comprehensive benchmark in their association with the brain structural integrity measures but were outperformed in their association with the functional integrity measures, particularly subjective cognitive problems and tested cognitive decline. Results indicated that existing indexes could be improved with targeted additions, particularly of measures assessing socioeconomic status, physical and sensory function, epigenetic aging, and subjective overall health. Existing premorbid ADRD risk indexes perform well in identifying linear gradients of risk among members of the general population at midlife, even when they include only a small subset of potential risk factors. They could be improved, however, with targeted additions to more holistically capture the different facets of risk for this multiply determined, age-related disease.
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Affiliation(s)
- Aaron Reuben
- Correspondence to: Aaron Reuben Department of Psychology and Neuroscience Duke University, Durham, NC 27708, USA E-mail:
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA,Center for Genomic and Computational Biology, Duke University, Durham, NC, USA,Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA,King’s College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, London, UK,PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
| | - Wickliffe C Abraham
- Brain Health Research Centre, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Antony Ambler
- King’s College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, London, UK
| | - Maxwell L Elliott
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Honalee Harrington
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Sean Hogan
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Renate M Houts
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Joan Leung
- School of Psychology, The University of Auckland, Auckland, New Zealand
| | - Amber Pearson
- Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA,Department of Public Health, University of Otago, Wellington, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Suzanne C Purdy
- Center for Brain Research, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Line J H Rasmussen
- Department of Clinical Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Peter R Thorne
- Center for Brain Research, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand,Faculty of Medical and Health Sciences, Department of Physiology, The University of Auckland, Auckland, New Zealand,Section of Audiology, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Benjamin Williams
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Graham Wilson
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand,Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA,Center for Genomic and Computational Biology, Duke University, Durham, NC, USA,Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA,King’s College London, Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, London, UK,PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
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Borgnakke WS, Poudel P. Diabetes and Oral Health: Summary of Current Scientific Evidence for Why Transdisciplinary Collaboration Is Needed. FRONTIERS IN DENTAL MEDICINE 2021. [DOI: 10.3389/fdmed.2021.709831] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
This Perspective provides a brief summary of the scientific evidence for the often two-way links between hyperglycemia, including manifest diabetes mellitus (DM), and oral health. It delivers in a nutshell examples of current scientific evidence for the following oral manifestations of hyperglycemia, along with any available evidence for effect in the opposite direction: periodontal diseases, caries/periapical periodontitis, tooth loss, peri-implantitis, dry mouth (xerostomia/hyposalivation), dysbiosis in the oral microbiome, candidiasis, taste disturbances, burning mouth syndrome, cancer, traumatic ulcers, infections of oral wounds, delayed wound healing, melanin pigmentation, fissured tongue, benign migratory glossitis (geographic tongue), temporomandibular disorders, and osteonecrosis of the jaw. Evidence for effects on quality of life will also be reported. This condensed overview delivers the rationale and sets the stage for the urgent need for delivery of oral and general health care in patient-centered transdisciplinary collaboration for early detection and management of both hyperglycemia and oral diseases to improve quality of life.
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