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Luperdi SC, Correa-Ghisays P, Vila-Francés J, Selva-Vera G, Livianos L, Tabarés-Seisdedos R, Balanzá-Martínez V. Verbal fluency in schizophrenia and bipolar disorder - A longitudinal, family study. J Psychiatr Res 2024; 178:33-40. [PMID: 39121705 DOI: 10.1016/j.jpsychires.2024.07.056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 07/27/2024] [Accepted: 07/29/2024] [Indexed: 08/12/2024]
Abstract
Verbal fluency (VF) has been proposed as a putative neurocognitive endophenotype in schizophrenia (SZ) and bipolar disorder (BD). However, this hypothesis has not been examined using a longitudinal family approach. We conducted a five-group, comparative study. The sample comprised 323 adult participants, including 81 BD patients, 47 unaffected relatives of BD BD-Rel), 76 SZ patients, 40 unaffected relatives of SZ (SZ-Rel), and 79 genetically unrelated healthy controls (HC). All subjects were assessed twice with semantic VF (sem-VF) and phonological VF (ph-VF) tests over a 2-year follow-up period. ANCOVAs controlling for age and years of education were used to compare performance across groups. Patients with SZ and BD and their unaffected relatives showed sem-VF and ph-VF deficits at baseline, which persisted over time (all, p < 0.05). Moreover, BD-Rel showed an intermediate performance between SZ and HC. A repeated-measures ANOVA revealed no significant differences in the between-group trajectories comparison (p > 0.05). Our findings support that VF may represent a neurocognitive endophenotype for SZ and BD. Further longitudinal, family studies are warranted to confirm this preliminary evidence.
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Affiliation(s)
- Sussy C Luperdi
- Program in Medicine, University of Valencia, Avda Blasco Ibanez, 15, 46010, Valencia, Spain; Department of Psychiatry, Virgen de Los Lirios Hospital, Polígono de Caramanchel, s/n, 03804, Alcoi, Alicante, Spain
| | - Patricia Correa-Ghisays
- Faculty of Psychology, University of Valencia, Avda Blasco Ibañez, 21, 46010, Valencia, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0, 28029, Madrid, Spain; INCLIVA Health Research Institute, C. de Menéndez y Pelayo, 4, 46010, Valencia, Spain
| | - Joan Vila-Francés
- IDAL - Intelligent Data Analysis Laboratory, University of Valencia, Avda de La Universitat s/n, 46100, Burjassot, Valencia, Spain
| | - Gabriel Selva-Vera
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0, 28029, Madrid, Spain; INCLIVA Health Research Institute, C. de Menéndez y Pelayo, 4, 46010, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Avda Blasco Ibáñez, 15, 46010, Valencia, Spain; Department of Psychiatry, University Clinical Hospital of Valencia, Avda Blasco Ibanez, 15, 46010, Valencia, Spain
| | - Lorenzo Livianos
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Avda Blasco Ibáñez, 15, 46010, Valencia, Spain; Department of Psychiatry, La Fe University and Polytechnic Hospital, Avda de Fernando Abril Martorell, 106, 46026, Valencia, Spain; Biomedical Research Networking Centre for Public Health (CIBERESP-Grupo 17), Instituto de Salud Carlos III, Avda. Monforte de Lemos, 3-5. Pabellón 11. Planta 0, 28029, Madrid, Spain
| | - Rafael Tabarés-Seisdedos
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0, 28029, Madrid, Spain; INCLIVA Health Research Institute, C. de Menéndez y Pelayo, 4, 46010, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Avda Blasco Ibáñez, 15, 46010, Valencia, Spain
| | - Vicent Balanzá-Martínez
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0, 28029, Madrid, Spain; INCLIVA Health Research Institute, C. de Menéndez y Pelayo, 4, 46010, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Avda Blasco Ibáñez, 15, 46010, Valencia, Spain; VALSME (VALencia Salut Mental i Estigma) Research Group, University of Valencia, Valencia, Spain.
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Ringin E, Dunstan DW, Meyer D, McIntyre RS, Owen N, Berk M, Hallgren M, Rossell SL, Van Rheenen TE. Relative associations of behavioral and physiological risks for cardiometabolic disease with cognition in bipolar disorder during mid and later-life: findings from the UK biobank. Psychol Med 2024:1-11. [PMID: 38563285 DOI: 10.1017/s0033291724000722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life. METHODS Data from the UK Biobank were available for 966 participants with BD, aged between 40 and 69 years. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; (1) health risk behaviors (physical activity, sedentary behavior, smoking, and sleep) and (2) physiological risk factors, stratified into (2a) anthropometric and clinical risk (handgrip strength, body composition, and blood pressure), and (2b) cardiometabolic disease risk biomarkers (CRP, lipid profile, and HbA1c). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models. RESULTS In the final combined model, lower mentally active and higher passive sedentary behavior, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition. CONCLUSIONS Health risk behaviors, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.
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Affiliation(s)
- Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Geelong, Australia
| | - Denny Meyer
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Roger S McIntyre
- Department of Psychiatry and Pharmacology, University of Toronto, Toronto, Canada
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Michael Berk
- Deakin University, The Institute for Mental and Physical Health and Clinical Translation, Barwon Health, Geelong, VIC, Australia
- Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Orygen Youth Health, Melbourne, Australia
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Susan L Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- St Vincent's Mental Health, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
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Ahern E, White J, Slattery E. Change in Cognitive Function over the Course of Major Depressive Disorder: A Systematic Review and Meta-analysis. Neuropsychol Rev 2024:10.1007/s11065-023-09629-9. [PMID: 38315296 DOI: 10.1007/s11065-023-09629-9] [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: 04/21/2023] [Accepted: 11/29/2023] [Indexed: 02/07/2024]
Abstract
Major depressive disorder (MDD) is associated with significant cognitive deficits during the acute and remitted stages. The aim of this systematic review and meta-analysis was to examine the course of cognitive function whilst considering demographic, treatment, or clinical features of MDD that could moderate the extent of cognitive change. Databases were searched to identify studies that reported on cognitive function in MDD with a ≥12-week test-retest interval. Relevant studies were pooled using random effects modelling to generate an inverse-variance, weighted, mean effect size estimate (Hedges' g) of cognitive change for each cognitive variable and for an overall composite cognitive domain. Of 6898 records, 99 eligible studies were identified from which 69 were meta-analysed, consisting of 4639 MDD patients (agemean = 40.25 years, female% = 64.62%) across 44 cognitive variables. In over 95% of cognitive variables, improvements were either of non-significant, negligible, or of a small magnitude, and when compared to matched healthy controls, the possibility of practice effects could not be precluded. Depressive symptom improvement and the number of previous depressive episodes moderated the extent of cognitive change, demonstrating state- and scar-like features for one-quarter of the cognitive domains. Further longitudinal studies are required to elucidate the MDD cognitive trajectory from initial onset. Findings nonetheless suggest that following pharmacological and non-pharmacological treatment, cognitive change in MDD is typically small, but the capacity for change may be less with episode recurrence. Targeting cognition early in the course of illness may facilitate better prognosis and support a more complete functional recovery.
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Affiliation(s)
- Elayne Ahern
- School of Psychology, Dublin City University, Glasnevin, Dublin 9, Ireland.
- Department of Psychology, University of Limerick, Castletroy, Limerick, V94 T9PX, Ireland.
| | - Jessica White
- School of Psychology, Dublin City University, Glasnevin, Dublin 9, Ireland
- School of Psychology, University College Dublin, Belfield, Dublin 4, Ireland
| | - Eadaoin Slattery
- Department of Applied Social Sciences, Technological University of the Shannon Midwest, Limerick, Ireland
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Wang Y, Ni B, Xiao Y, Lin Y, Zhang Y. A novel nomogram for predicting risk of hypertension in US adults with periodontitis: National Health and Nutrition Examination Survey (NHANES) 2009-2014. Medicine (Baltimore) 2023; 102:e36659. [PMID: 38134101 PMCID: PMC10735070 DOI: 10.1097/md.0000000000036659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
The goal of our study was to create a nomogram to predict the risk of developing hypertension in patients with periodontitis. Our study used data from a total of 3196 subjects from the National Health and Nutrition Examination Survey 2009 to 2014 who had ever been diagnosed with periodontitis. The data set was randomly divided into a training set and a validation set according to a 7:3 ratio. The data from the training set was utilized to build the prediction model, while the validation set were used to validate the model. To identify the risk variables, stepwise regression was used to perform successive univariate and multivariate logistic regression analysis. The predictive ability of the nomogram model was evaluated using receiver operating characteristic curve. Calibration plots were used to assess the consistency of the prediction model. The clinical value of the model was evaluated using decision curve analysis and clinical impact curve. A nomogram for the risk of hypertension in subjects with periodontitis was constructed in accordance with the 8 predictors identified in this study. The areas under the receiver operating characteristic curve values for the training set and validation set were 0.922 (95% confidence interval: 0.911-0.933) and 0.918 (95% confidence interval: 0.900-0.935), respectively, indicating excellent discrimination. The decision curve analysis and clinical impact curve suggested that the model has significant clinical applications, and the calibration plots of the training set and validation set demonstrated good consistency. The nomogram can effectively predict the risk of hypertension in patients with periodontitis and help clinicians make better clinical decisions.
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Affiliation(s)
- Yicheng Wang
- Department of Cardiovascular Medicine, Affiliated Fuzhou First Hospital of Fujian Medical University, Fuzhou, Fujian, China
- The Third Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Cardiovascular Disease Research Institute of Fuzhou City, Fuzhou, Fujian, China
| | - Binghang Ni
- Department of Cardiovascular Medicine, Affiliated Fuzhou First Hospital of Fujian Medical University, Fuzhou, Fujian, China
- The Third Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Cardiovascular Disease Research Institute of Fuzhou City, Fuzhou, Fujian, China
| | - Yuan Xiao
- Department of Cardiovascular Medicine, Affiliated Fuzhou First Hospital of Fujian Medical University, Fuzhou, Fujian, China
- The Third Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Cardiovascular Disease Research Institute of Fuzhou City, Fuzhou, Fujian, China
| | - Yichang Lin
- Department of Cardiovascular Medicine, Affiliated Fuzhou First Hospital of Fujian Medical University, Fuzhou, Fujian, China
- The Third Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Cardiovascular Disease Research Institute of Fuzhou City, Fuzhou, Fujian, China
| | - Yan Zhang
- Department of Cardiovascular Medicine, Affiliated Fuzhou First Hospital of Fujian Medical University, Fuzhou, Fujian, China
- The Third Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China
- The Graduate School of Fujian Medical University, Fuzhou, Fujian, China
- Cardiovascular Disease Research Institute of Fuzhou City, Fuzhou, Fujian, China
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5
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Sánchez-Ortí JV, Correa-Ghisays P, Balanzá-Martínez V, Selva-Vera G, Vila-Francés J, Magdalena-Benedito R, San-Martin C, Victor VM, Escribano-Lopez I, Hernandez-Mijares A, Vivas-Lalinde J, Crespo-Facorro B, Tabarés-Seisdedos R. Inflammation and lipid metabolism as potential biomarkers of memory impairment across type 2 diabetes mellitus and severe mental disorders. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110817. [PMID: 37327846 DOI: 10.1016/j.pnpbp.2023.110817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/20/2023] [Accepted: 06/12/2023] [Indexed: 06/18/2023]
Abstract
INTRODUCTION Neurocognitive impairment is a transdiagnostic feature across several psychiatric and cardiometabolic conditions. The relationship between inflammatory and lipid metabolism biomarkers and memory performance is not fully understood. This study aimed to identify peripheral biomarkers suitable to signal memory decline from a transdiagnostic and longitudinal perspective. METHODS Peripheral blood biomarkers of inflammation, oxidative stress and lipid metabolism were assessed twice over a 1-year period in 165 individuals, including 30 with schizophrenia (SZ), 42 with bipolar disorder (BD), 35 with major depressive disorder (MDD), 30 with type 2 diabetes mellitus (T2DM), and 28 healthy controls (HCs). Participants were stratified by memory performance quartiles, taking as a reference their global memory score (GMS) at baseline, into categories of high memory (H; n = 40), medium to high memory (MH; n = 43), medium to low memory (ML; n = 38) and low memory (L; n = 44). Exploratory and confirmatory factorial analysis, mixed one-way analysis of covariance and discriminatory analyses were performed. RESULTS L group was significantly associated with higher levels of tumor necrosis factor-alpha (TNF-α) and lower levels of apolipoprotein A1 (Apo-A1) compared to those from the MH and H groups (p < 0.05; η2p = 0.06-0.09), with small to moderate effect sizes. Moreover, the combination of interleukin-6 (IL-6), TNF-α, c-reactive protein (CRP), Apo-A1 and Apo-B compounded the transdiagnostic model that best discriminated between groups with different degrees of memory impairment (χ2 = 11.9-49.3, p < 0.05-0.0001). CONCLUSIONS Inflammation and lipid metabolism seem to be associated with memory across T2DM and severe mental illnesses (SMI). A panel of biomarkers may be a useful approach to identify individuals at greater risk of neurocognitive impairment. These findings may have a potential translational utility for early intervention and advance precision medicine in these disorders.
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Affiliation(s)
- Joan Vicent Sánchez-Ortí
- INCLIVA - Health Research Institute, Valencia, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Faculty of Psychology, University of Valencia, Valencia, Spain
| | - Patricia Correa-Ghisays
- INCLIVA - Health Research Institute, Valencia, Spain; Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Faculty of Psychology, University of Valencia, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain.
| | - Vicent Balanzá-Martínez
- INCLIVA - Health Research Institute, Valencia, Spain; Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain; Mental Health Unit of Catarroja, Valencia, Spain.
| | - Gabriel Selva-Vera
- INCLIVA - Health Research Institute, Valencia, Spain; Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
| | - Joan Vila-Francés
- IDAL - Intelligent Data Analysis Laboratory, University of Valencia, Valencia, Spain
| | | | - Constanza San-Martin
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Department of Physiotherapy, University of Valencia, Valencia, Spain
| | - Víctor M Victor
- Service of Endocrinology and Nutrition, University Hospital Dr. Peset, Spain; Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia, Spain; Department of Physiology, University of Valencia, Valencia, Spain
| | | | | | | | - Benedicto Crespo-Facorro
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; Department of Psychiatry, Faculty of Medicine, University of Sevilla, HU Virgen del Rocío IBIS, Spain
| | - Rafael Tabarés-Seisdedos
- INCLIVA - Health Research Institute, Valencia, Spain; Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain; TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
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Examining Factors Associated with Dynapenia/Sarcopenia in Patients with Schizophrenia: A Pilot Case-Control Study. Healthcare (Basel) 2023; 11:healthcare11050684. [PMID: 36900689 PMCID: PMC10000555 DOI: 10.3390/healthcare11050684] [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: 12/30/2022] [Revised: 02/09/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023] Open
Abstract
Sedentary behavior in patients with schizophrenia causes muscle weakness, is associated with a higher risk of metabolic syndrome, and contributes to mortality risk. This pilot case-control study aims to examine the associated factors for dynapenia/sarcopenia in patients with schizophrenia. The participants were 30 healthy individuals (healthy group) and 30 patients with schizophrenia (patient group), who were matched for age and sex. Descriptive statistics, Welch's t-test, cross-tabulations, adjusted residuals, Fisher's exact probability test (extended), and/or odds ratios (ORs) were calculated. In this study, dynapenia was significantly more prevalent in patients with schizophrenia than in healthy individuals. Regarding body water, Pearson's chi-square value was 4.41 (p = 0.04), and significantly more patients with dynapenia were below the normal range. In particular, body water and dynapenia showed a significant association, with an OR = 3.42 and 95% confidence interval [1.06, 11.09]. Notably, compared with participants of the healthy group, patients with schizophrenia were overweight, had less body water, and were at a higher risk for dynapenia. The impedance method and the digital grip dynamometer used in this study were simple and useful tools for evaluating muscle quality. To improve health conditions for patients with schizophrenia, additional attention should be paid to muscle weakness, nutritional status, and physical rehabilitation.
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Yang J, Wang X, Jiang S. Development and validation of a nomogram model for individualized prediction of hypertension risk in patients with type 2 diabetes mellitus. Sci Rep 2023; 13:1298. [PMID: 36690699 PMCID: PMC9870905 DOI: 10.1038/s41598-023-28059-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/12/2023] [Indexed: 01/24/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM) with hypertension (DH) is the most common diabetic comorbidity. Patients with DH have significantly higher rates of cardiovascular disease morbidity and mortality. The objective of this study was to develop and validate a nomogram model for the prediction of an individual's risk of developing DH. A total of 706 T2DM patients who met the criteria were selected and divided into a training set (n = 521) and a validation set (n = 185) according to the discharge time of patients. By using multivariate logistic regression analysis and stepwise regression, the DH nomogram prediction model was created. Calibration curves were used to evaluate the model's accuracy, while decision curve analysis (DCA) and receiver operating characteristic (ROC) curves were used to evaluate the model's clinical applicability and discriminatory power. Age, body mass index (BMI), diabetic nephropathy (DN), and diabetic retinopathy (DR) were all independent risk factors for DH (P < 0.05). Based on independent risk factors identified by multivariate logistic regression, the nomogram model was created. The model produces accurate predictions. If the total nomogram score is greater than 120, there is a 90% or higher chance of developing DH. In the training and validation sets, the model's ROC curves are 0.762 (95% CI 0.720-0.803) and 0.700 (95% CI 0.623-0.777), respectively. The calibration curve demonstrates that there is good agreement between the model's predictions and the actual outcomes. The decision curve analysis findings demonstrated that the nomogram model was clinically helpful throughout a broad threshold probability range. The DH risk prediction nomogram model constructed in this study can help clinicians identify individuals at high risk for DH at an early stage, which is a guideline for personalized prevention and treatments.
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Affiliation(s)
- Jing Yang
- Department of Endocrinology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830017, China
| | - Xuan Wang
- Department of Endocrinology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830017, China
| | - Sheng Jiang
- Department of Endocrinology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830017, China.
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8
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Sánchez-Ortí JV, Balanzá-Martínez V, Correa-Ghisays P, Selva-Vera G, Vila-Francés J, Magdalena-Benedito R, San-Martin C, Victor VM, Escribano-Lopez I, Hernández-Mijares A, Vivas-Lalinde J, Crespo-Facorro B, Tabarés-Seisdedos R. Specific metabolic syndrome components predict cognition and social functioning in people with type 2 diabetes mellitus and severe mental disorders. Acta Psychiatr Scand 2022; 146:215-226. [PMID: 35359023 DOI: 10.1111/acps.13433] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 03/25/2022] [Accepted: 03/29/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Obesity and metabolic diseases such as metabolic syndrome (MetS) are more prevalent in people with type 2 diabetes mellitus (T2DM), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). MetS components might be associated with neurocognitive and functional impairments in these individuals. The predictive and discriminatory validity of MetS and its components regarding those outcomes were assessed from prospective and transdiagnostic perspectives. METHODS Metabolic syndrome components and neurocognitive and social functioning were assessed in 165 subjects, including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 healthy controls (HCs). A posteriori, individuals were classified into two groups. The MetS group consisted of those who met at least three of the following criteria: abdominal obesity (AO), elevated triglycerides (TG), reduced high-density lipoprotein cholesterol (HDL), elevated blood pressure (BP), and elevated fasting glucose (FPG); the remaining participants comprised the No-MetS group. Mixed one-way analysis of covariance and linear and binary logistic regression analyses were performed. RESULTS Cognitive impairment was significantly greater in the MetS group (n = 82) than in the No-MetS group (n = 83), with small effect sizes (p < 0.05; η²p = 0.02 - 0.03). In both groups, the most robust associations between MetS components and neurocognitive and social functioning were observed with TG and FPG (p < 0.05). There was also evidence for a significant relationship between cognition and BP in the MetS group (p < 0.05). The combination of TG, FPG, elevated systolic BP and HDL best classified individuals with greater cognitive impairment (p < 0.001), and TG was the most accurate (p < 0.0001). CONCLUSIONS Specific MetS components are significantly associated with cognitive impairment across somatic and psychiatric disorders. Our findings provide further evidence on the summative effect of MetS components to predict cognition and social functioning and allow the identification of individuals with worse outcomes. Transdiagnostic, lifestyle-based therapeutic interventions targeted at that group hold the potential to improve health outcomes.
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Affiliation(s)
- Joan Vicent Sánchez-Ortí
- INCLIVA - Biomedical Research Institute, Valencia, Spain.,TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Faculty of Psychology, University of Valencia, Valencia, Spain
| | - Vicent Balanzá-Martínez
- INCLIVA - Biomedical Research Institute, Valencia, Spain.,TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain.,Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain.,Mental Health Unit of Catarroja, Valencia, Spain
| | - Patricia Correa-Ghisays
- INCLIVA - Biomedical Research Institute, Valencia, Spain.,TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Faculty of Psychology, University of Valencia, Valencia, Spain.,Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain.,Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
| | - Gabriel Selva-Vera
- INCLIVA - Biomedical Research Institute, Valencia, Spain.,TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain.,Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
| | - Joan Vila-Francés
- IDAL - Intelligent Data Analysis Laboratory, University of Valencia, Valencia, Spain
| | | | - Constanza San-Martin
- TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Department of Physiotherapy, University of Valencia, Valencia, Spain
| | - Víctor M Victor
- Service of Endocrinology and Nutrition, University Hospital Dr. Peset, Valencia, Spain.,Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia, Spain.,Department of Physiology, University of Valencia, Valencia, Spain
| | - Irene Escribano-Lopez
- Service of Endocrinology and Nutrition, University Hospital Dr. Peset, Valencia, Spain
| | | | | | - Benedicto Crespo-Facorro
- TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Department of Psychiatry, Faculty of Medicine, University of Sevilla, HU Virgen del Rocío IBIS, Sevilla, Spain
| | - Rafael Tabarés-Seisdedos
- INCLIVA - Biomedical Research Institute, Valencia, Spain.,TMAP - Evaluation Unit in Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain.,Center for Biomedical Research in Mental Health Network (CIBERSAM), Health Institute, Carlos III, Madrid, Spain.,Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
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9
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Garés-Caballer M, Sánchez-Ortí JV, Correa-Ghisays P, Balanzá-Martínez V, Selva-Vera G, Vila-Francés J, Magdalena-Benedito R, San-Martin C, Victor VM, Escribano-Lopez I, Hernandez-Mijares A, Vivas-Lalinde J, Vieta E, Leza JC, Tabarés-Seisdedos R. Immune-Inflammatory Biomarkers Predict Cognition and Social Functioning in Patients With Type 2 Diabetes Mellitus, Major Depressive Disorder, Bipolar Disorder, and Schizophrenia: A 1-Year Follow-Up Study. Front Neurol 2022; 13:883927. [PMID: 35720107 PMCID: PMC9201031 DOI: 10.3389/fneur.2022.883927] [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: 02/25/2022] [Accepted: 04/19/2022] [Indexed: 11/30/2022] Open
Abstract
Background Systemic, low-grade immune-inflammatory activity, together with social and neurocognitive performance deficits are a transdiagnostic trait of people suffering from type 2 diabetes mellitus (T2DM) and severe mental illnesses (SMIs), such as schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD). We aimed to determine if immune-inflammatory mediators were significantly altered in people with SMIs or T2DM compared with healthy controls (HC) and whether these biomarkers could help predict their cognition and social functioning 1 year after assessment. Methods We performed a prospective, 1-year follow-up cohort study with 165 participants at baseline (TB), including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 HC; and 125 at 1-year follow-up (TY), and determined executive domain (ED), global social functioning score (GSFS), and peripheral blood immune-inflammatory and oxidative stress biomarkers. Results Participants with SMIs and T2DM showed increased peripheral levels of inflammatory markers, such as interleukin-10 (p < 0.01; η2 p = 0.07) and tumor necrosis factor-α (p < 0.05; η2 p = 0.08); and oxidative stress biomarkers, such as reactive oxygen species (ROS) (p < 0.05; η2 p = 0.07) and mitochondrial ROS (p < 0.01; η2 p = 0.08). The different combinations of the exposed biomarkers anticipated 46-57.3% of the total ED and 23.8-35.7% of GSFS for the participants with SMIs. Limitations Participants' treatment, as usual, was continued without no specific interventions; thus, it was difficult to anticipate substantial changes related to the psychopharmacological pattern. Conclusion People with SMIs show significantly increased levels of peripheral immune-inflammatory biomarkers, which may contribute to the neurocognitive and social deficits observed in SMIs, T2DM, and other diseases with systemic immune-inflammatory activation of chronic development. These parameters could help identify the subset of patients who could benefit from immune-inflammatory modulator strategies to ameliorate their functional outcomes.
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Affiliation(s)
- Marta Garés-Caballer
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
| | - Joan Vicent Sánchez-Ortí
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Faculty of Psychology and Speech Therapy, University of Valencia, Valencia, Spain
| | - Patricia Correa-Ghisays
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Faculty of Psychology and Speech Therapy, University of Valencia, Valencia, Spain
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
| | - Vicent Balanzá-Martínez
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
- Mental Health Unit of Catarroja, Valencia, Spain
| | - Gabriel Selva-Vera
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
| | - Joan Vila-Francés
- IDAL—Intelligent Data Analysis Laboratory, University of Valencia, Valencia, Spain
| | | | - Constanza San-Martin
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Department of Physiotherapy, University of Valencia, Valencia, Spain
| | - Victor M. Victor
- Service of Endocrinology and Nutrition, University Hospital Dr. Peset, Valencia, Spain
- Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia, Spain
- Department of Physiology, University of Valencia, Valencia, Spain
| | - Irene Escribano-Lopez
- Service of Endocrinology and Nutrition, University Hospital Dr. Peset, Valencia, Spain
| | | | | | - Eduard Vieta
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
- Barcelona Bipolar and Depressive Disorders Unit, Institute of Neurosciences, Hospital Clínic of Barcelona, University of Barcelona, IDIBAPS, Catalonia, Spain
| | - Juan C. Leza
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
- Department of Pharmacology and Toxicology, Faculty of Medicine, Complutense University of Madrid, Madrid, Spain
| | - Rafael Tabarés-Seisdedos
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
- INCLIVA—Health Research Institute, Valencia, Spain
- TMAP—Evaluation Unit of Personal Autonomy, Dependency and Serious Mental Disorders, University of Valencia, Valencia, Spain
- Center for Biomedical Research in Mental Health Network (CIBERSAM), Institute of Health Carlos III, Madrid, Spain
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10
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Correa-Ghisays P, Sánchez-Ortí JV, Balanzá-Martínez V, Selva-Vera G, Vila-Francés J, Magdalena-Benedito R, Victor VM, Escribano-López I, Hernández-Mijares A, Vivas-Lalinde J, San-Martín C, Crespo-Facorro B, Tabarés-Seisdedos R. Transdiagnostic neurocognitive deficits in patients with type 2 diabetes mellitus, major depressive disorder, bipolar disorder, and schizophrenia: A 1-year follow-up study. J Affect Disord 2022; 300:99-108. [PMID: 34965401 DOI: 10.1016/j.jad.2021.12.074] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 11/05/2021] [Accepted: 12/19/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Neurocognition impairments are critical factors in patients with major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ), and also in those with somatic diseases such as type 2 diabetes mellitus (T2DM). Intriguingly, these severe mental illnesses are associated with an increased co-occurrence of diabetes (direct comorbidity). This study sought to investigate the neurocognition and social functioning across T2DM, MDD, BD, and SZ using a transdiagnostic and longitudinal approach. METHODS A total of 165 participants, including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 healthy controls (HC), were assessed twice at a 1-year interval using a comprehensive, integrated test battery on neuropsychological and social functioning. RESULTS Common neurocognitive impairments in somatic and psychiatric disorders were identified, including deficits in short-term memory and cognitive reserve (p < 0.01, η²p=0.08-0.31). Social functioning impairments were observed in almost all the disorders (p < 0.0001; η²p=0.29-0.49). Transdiagnostic deficits remained stable across the 1-year follow-up (p < 0.001; η²p=0.13-0.43) and could accurately differentiate individuals with somatic and psychiatric disorders (χ² = 48.0, p < 0.0001). LIMITATIONS The initial sample size was small, and high experimental mortality was observed after follow-up for one year. CONCLUSIONS This longitudinal study provides evidence of some possible overlap in neurocognition deficits across somatic and psychiatric diagnostic categories, such as T2DM, MDD, BD, and SZ, which have high comorbidity. This overlap may be a result of shared genetic and environmental etiological factors. The findings open promising avenues for research on transdiagnostic phenotypes of neurocognition in these disorders, in addition to their biological bases.
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Affiliation(s)
- Patricia Correa-Ghisays
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid 28029, Spain; TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; INCLIVA - Health Research Institute, Valencia 46010, Spain; Faculty of Psychology, University of Valencia, Valencia 46010, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Blasco-Ibáñez 17, Valencia 46010, Spain
| | - Joan Vicent Sánchez-Ortí
- TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; INCLIVA - Health Research Institute, Valencia 46010, Spain; Faculty of Psychology, University of Valencia, Valencia 46010, Spain
| | - Vicent Balanzá-Martínez
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid 28029, Spain; TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; INCLIVA - Health Research Institute, Valencia 46010, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Blasco-Ibáñez 17, Valencia 46010, Spain; Unitat de Salut Mental de Catarroja, Valencia 46470, Spain
| | - Gabriel Selva-Vera
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid 28029, Spain; TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; INCLIVA - Health Research Institute, Valencia 46010, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Blasco-Ibáñez 17, Valencia 46010, Spain
| | - Joan Vila-Francés
- IDAL - Intelligent Data Analysis Laboratory, University of Valencia, Valencia 46100, Spain
| | | | - Victor M Victor
- Service of Endocrinology and Nutrition, University Hospital Doctor Peset, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia 46017, Spain; Department of Physiology, University of Valencia, Valencia 46010, Spain
| | - Irene Escribano-López
- Service of Endocrinology and Nutrition, University Hospital Doctor Peset, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia 46017, Spain
| | - Antonio Hernández-Mijares
- Service of Endocrinology and Nutrition, University Hospital Doctor Peset, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Valencia 46017, Spain; Department of Medicine, University of Valencia, Valencia 46010, Spain
| | | | - Constanza San-Martín
- TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; Departament of Physioterapy, University of Valencia, Valencia 46010, Spain
| | - Benedicto Crespo-Facorro
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid 28029, Spain; Hospital Universitario Virgen del Roció-IBIS- University of Sevilla, Sevilla, Spain
| | - Rafael Tabarés-Seisdedos
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid 28029, Spain; TMAP - Unidad de Evaluación en Autonomía Personal, Dependencia y Trastornos Mentales Graves, University of Valencia, Valencia 46010, Spain; INCLIVA - Health Research Institute, Valencia 46010, Spain; Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Blasco-Ibáñez 17, Valencia 46010, Spain.
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11
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Pearson E, Siskind D, Hubbard RE, Gordon EH, Coulson EJ, Warren N. Frailty and severe mental illness: A systematic review and narrative synthesis. J Psychiatr Res 2022; 147:166-175. [PMID: 35051715 DOI: 10.1016/j.jpsychires.2022.01.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/02/2022] [Accepted: 01/06/2022] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Emerging evidence suggests that people with severe mental illness (SMI) have an increased risk of frailty. We conducted a systematic review to investigate the prevalence and correlates of frailty, as well as the efficacy of frailty interventions, in this population. METHODS We searched databases from inception to 21 September 2021 for studies that assessed or intervened for frailty in relation to an SMI diagnosis. A narrative synthesis explored the characteristics and adverse health outcomes associated with frailty and the efficacy of interventions. The prevalence of frailty was investigated, and its relationship with age was analysed by a meta-regression. RESULTS Twenty-five studies involving 2499 patients, primarily older adults, were included in the narrative synthesis. Frailty was associated with higher rates of physical comorbidity, cognitive deficits, falls and mortality among those with SMI. The efficacy of a yoga intervention was investigated in one study, without sustained reductions in frailty. The prevalence of frailty varied between 10.2 and 89.7% and was high in comparison to the general population. CONCLUSIONS The prevalence of frailty was high in those with SMI and ranged widely due to heterogeneity of study populations. Assessing frailty enables the identification of patients who could benefit from interventions and assists in treatment-related decision making. Further research is required to develop appropriate frailty interventions for this population.
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Affiliation(s)
- Ella Pearson
- School of Biomedical Sciences, University of Queensland, Brisbane, Queensland, Australia.
| | - Dan Siskind
- Metro South Addiction and Mental Health Services, Brisbane, Queensland, Australia; School of Clinical Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Ruth E Hubbard
- Centre for Health Services Research, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia; Department of Geriatrics, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Emily H Gordon
- Centre for Health Services Research, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia; Department of Geriatrics, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Elizabeth J Coulson
- School of Biomedical Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Nicola Warren
- Metro South Addiction and Mental Health Services, Brisbane, Queensland, Australia; School of Clinical Medicine, University of Queensland, Brisbane, Queensland, Australia
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