RESUMO
OBJECTIVES: A number of small-scale, single-country studies have suggested that muscular weakness may be a biomarker for cognitive health, mild cognitive impairment (MCI), and dementia. However, multinational, representative studies are lacking, particularly from low- and middle-income countries (LMICs). Thus, we assessed the association between muscular strength (measured by maximal handgrip) and MCI in six LMICs (China, Ghana, India, Mexico, Russia, and South Africa), using nationally representative data. METHODS: Cross-sectional, community-based data on individuals aged 50 years or older from the World Health Organization's Study on Global Ageing and Adult Health were analyzed. MCI was defined according to the National Institute on Aging-Alzheimer's Association criteria. Weak handgrip strength was defined as less than 30 kg for men and less than 20 kg for women using the average value of two handgrip measurements of the dominant hand. Multivariable logistic regression analysis was conducted to assess the association between muscular strength and MCI. RESULTS: A total of 32 715 participants were included (mean age 62 ± SD 15.6 y and 51.7% female). The prevalence of MCI and weak handgrip strength was 15.3% (95% CI, 14.4%-16.3%) and 46.5% (95% CI, 43.6%-49.5%), respectively. After adjustment for potential confounders, weak handgrip strength was associated with 1.41 (95% CI, 1.23-1.61) times higher odds for MCI. The corresponding figures for those aged 50 to 64 years and 65 years or older were 1.35 (95% CI, 1.14-1.60) and 1.54 (95% CI, 1.27-1.86), respectively. CONCLUSIONS: Muscular weakness may provide a clinically useful indicator of MCI risk. Increasing our understanding of the connection between muscular and cognitive function could ultimately lead to the development and broader implementation of resistance training interventions targeting both physical and cognitive health.
Assuntos
Disfunção Cognitiva , Força da Mão , Idoso , China , Cognição , Disfunção Cognitiva/classificação , Disfunção Cognitiva/diagnóstico , Estudos Transversais , Demência , Países em Desenvolvimento , Feminino , Gana , Humanos , Índia , Masculino , México , Pessoa de Meia-Idade , Prevalência , Medição de Risco , Federação Russa , África do SulRESUMO
BACKGROUND: Evidence has shown heterogeneity of cognitive function among patients with bipolar disorder (BD). Our study aims to replicate recent findings of cognitive subgroups, as well as we assessed subjective cognitive difficulties and functioning in each cluster. METHODS: Hierarchical cluster analysis was conducted to examine whether there were distinct neurocognitive subgroups based on neurocognitive battery. Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) and Functioning Assessment Short Test (FAST) were used to assess subjective cognitive difficulties and functional impairment. RESULTS: We found three distinct subgroups: a first cluster with intact cognition (nâ¯=â¯30, 43.5%), a second cluster with selective cognitive impairment (nâ¯=â¯23, 33.3%), and a third cluster with globally cognitive impairment (nâ¯=â¯16, 23.3%). The intact group had more years of education (pâ¯<â¯.001) and higher estimated IQ (pâ¯<â¯.001) than globally and selectively impaired subgroups. Additionally, they were younger (pâ¯=â¯.011), had an earlier age at bipolar diagnosis (pâ¯<â¯.037) and earlier age of first hospitalization (pâ¯<â¯.035) compared to individuals with globally cognitive impairment. LIMITATIONS: This is a cross-sectional design with a small sample including only patients from a tertiary hospital. CONCLUSION: Our results give support to the existence of a continuum of severity from patients without impairment to those with poor cognitive functioning. Patients in the intact group seem to have higher cognitive reserve than other two groups. However, they also experienced cognitive complaints and some degree of functional impairment. These findings suggest the importance of using a combo of instruments (e.g., objective and subjective cognitive measures plus functioning instruments) for a complete assessment of patients with BD.
Assuntos
Transtorno Bipolar/psicologia , Disfunção Cognitiva/diagnóstico , Adulto , Análise por Conglomerados , Disfunção Cognitiva/classificação , Disfunção Cognitiva/complicações , Reserva Cognitiva , Estudos Transversais , Feminino , Hospitalização , Humanos , Masculino , Pessoa de Meia-Idade , Centros de Atenção TerciáriaRESUMO
OBJECTIVES: Cognitive dysfunction is a key feature of major depressive (MDD) and bipolar (BD) disorders. However, rather than a single cognitive profile corresponding to each diagnostic categories, recent studies have identified significant intra- and cross-diagnostic variability in patterns of cognitive impairment. The goal of this study was to contribute to the literature on cognitive heterogeneity in mood disorders by identifying cognitive subprofiles in a population of patients with MDD, BD type I, BD type II, and healthy adults. METHODS: Participants completed a neuropsychological battery; scores were converted into Z-scores using normative data and submitted to hierarchical cluster analysis. RESULTS: Three distinct neuropsychological clusters were identified: (1) a large cluster containing mostly control participants, as well as some patients with BD and MDD, who performed at above-average levels on all neuropsychological domains; (2) a cluster containing some patients from all diagnostic groups, as well as healthy controls, who performed worse than cluster 1 on most tasks, and showed impairments in motor inhibition and verbal fluency; (3) a cluster containing mostly patients with mood disorders with severe impairments in verbal inhibition and cognitive flexibility. CONCLUSIONS: These findings revealed multiple cognitive profiles within diagnostic categories, as well as significant cross-diagnostic overlap, highlighting the importance of developing more specific treatment approaches which consider patients' demographic and cognitive profiles in addition to their diagnosis. (JINS, 2017, 23, 584-593).
Assuntos
Transtorno Bipolar/fisiopatologia , Disfunção Cognitiva/classificação , Disfunção Cognitiva/fisiopatologia , Transtorno Depressivo Maior/fisiopatologia , Adulto , Transtorno Bipolar/complicações , Análise por Conglomerados , Disfunção Cognitiva/etiologia , Transtorno Depressivo Maior/complicações , Feminino , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
BACKGROUND: Neuroimaging techniques combined with computational neuroanatomy have been playing a role in the investigation of healthy aging and Alzheimer's disease (AD). The definition of normative rules for brain features is a crucial step to establish typical and atypical aging trajectories. OBJECTIVE: To introduce an unsupervised pattern recognition method; to define multivariate normative rules of neuroanatomical measures; and to propose a brain abnormality index. METHODS: This study was based on a machine learning approach (one class classification or novelty detection) to neuroanatomical measures (brain regions, volume, and cortical thickness) extracted from the Alzheimer's Disease Neuroimaging Initiative (ADNI)'s database. We applied a ν-One-Class Support Vector Machine (ν-OC-SVM) trained with data from healthy subjects to build an abnormality index, which was compared with subjects diagnosed with mild cognitive impairment and AD. RESULTS: The method was able to classify AD subjects as outliers with an accuracy of 84.3% at a false alarm rate of 32.5%. The proposed brain abnormality index was found to be significantly associated with group diagnosis, clinical data, biomarkers, and future conversion to AD. CONCLUSION: These results suggest that one-class classification may be a promising approach to help in the detection of disease conditions. Our findings support a framework considering the continuum of brain abnormalities from healthy aging to AD, which is correlated with cognitive impairment and biomarkers measurements.