The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study

Yuan, Manqiong; Xu, Chuanhai; Fang, Ya

doi:10.1186/s12877-022-03220-2

Cited by 16 publications

(19 citation statements)

References 55 publications

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“…It is worth noting that some models only included a few easy-to-obtain predictors with excellent performance ( Yang and Zhang, 2021 ; Chen et al, 2022 ). Age, education, depression, and chronic diseases were the robust predictors consistent with previous findings ( Yuan et al, 2022 ). Physical exercise was also a robust predictor.…”

Section: Discussionsupporting

confidence: 90%

Prediction model for cognitive frailty in older adults: A systematic review and critical appraisal

Huang

Zeng

et al. 2023

Front. Aging Neurosci.

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BackgroundSeveral prediction models for cognitive frailty (CF) in older adults have been developed. However, the existing models have varied in predictors and performances, and the methodological quality still needs to be determined.ObjectivesWe aimed to summarize and critically appraise the reported multivariable prediction models in older adults with CF.MethodsPubMed, Embase, Cochrane Library, Web of Science, Scopus, PsycINFO, CINAHL, China National Knowledge Infrastructure, and Wanfang Databases were searched from the inception to March 1, 2022. Included models were descriptively summarized and critically appraised by the Prediction Model Risk of Bias Assessment Tool (PROBAST).ResultsA total of 1,535 articles were screened, of which seven were included in the review, describing the development of eight models. Most models were developed in China (n = 4, 50.0%). The most common predictors were age (n = 8, 100%) and depression (n = 4, 50.0%). Seven models reported discrimination by the C-index or area under the receiver operating curve (AUC) ranging from 0.71 to 0.97, and four models reported the calibration using the Hosmer–Lemeshow test and calibration plot. All models were rated as high risk of bias. Two models were validated externally.ConclusionThere are a few prediction models for CF. As a result of methodological shortcomings, incomplete presentation, and lack of external validation, the models’ usefulness still needs to be determined. In the future, models with better prediction performance and methodological quality should be developed and validated externally.Systematic review registrationwww.crd.york.ac.uk/prospero, identifier CRD42022323591.

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Section: Discussionsupporting

confidence: 90%

Prediction model for cognitive frailty in older adults: A systematic review and critical appraisal

Huang

Zeng

et al. 2023

Front. Aging Neurosci.

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“…), or whether CF determined the likelihood of remaining in a rural environment with increasing age. Yuan et al (2022) considered directionality in a longitudinal study. Rurality increased likelihood of transition to CF from an initial PF state, although no mechanistic pathway was suggested.…”

Section: Habitatmentioning

confidence: 99%

Understanding exogenous factors and biological mechanisms for cognitive frailty: a multidisciplinary scoping review

Holland,

Dravecz,

Owens

et al. 2024

Preprint

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Cognitive frailty (CF) is the conjunction of cognitive impairment without dementia and physical frailty. While predictors of each element are well-researched, mechanisms of their co-occurrence have not been integrated, particularly in terms of relationships between social, psychological, and biological factors. This interdisciplinary scoping review set out to categorise a heterogenous multidisciplinary literature to identify potential pathways and mechanisms of CF, and research gaps. Studies were included if they used the definition of CF OR focused on conjunction of cognitive impairment and frailty, AND excluded studies on specific disease populations, interventions, epidemiology or prediction of mortality. Searches used Web of Science, PubMed and Science Direct. Search terms included "cognitive frailty" OR (("cognitive decline" OR "cognitive impairment") AND (frail*)), with terms to elicit mechanisms, predictors, causes, pathways and risk factors. To ensure inclusion of animal and cell models, keywords such as "behavioural" or "cognitive decline" or "senescence", were added. 206 papers were included. Descriptive analysis provided high-level categorisation of determinants from social and environmental through psychological to biological. Patterns distinguishing CF from Alzheimer's disease were identified and social and psychological moderators and mediators of underlying biological and physiological changes and of trajectories of CF development were suggested as foci for further research.

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“…In CHARLS, mental status questions included serial subtraction of 7 from 100 (up to 5 times), date (month, day, year), day of the week, season, and intersecting pentagon copying test, for a total of 11 points. Total cognitive scores are calculated as the sum of the scores of episodic memory and mental intactness and ranged from 0 to 21, with higher scores indicating better cognitive function [27].…”

Section: Cognitive Functionmentioning

confidence: 99%

Association between Grandparenting and Cognitive Function in Middle-Aged and Older Chinese: the mediation role of Children’s Intergenerational Support—A nationally representative cohort study

Hou

Luo

Yang

et al. 2023

Preprint

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Objectives As the world’s population increases in age, the number of people suffering from cognitive impairment and dementia has increased dramatically. This study aims to investigate the association between grandparenting and cognitive function in middle-aged and older Chinese and explore the mediating effects of children’s intergenerational support on grandparenting and cognitive function. Methods This study used data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 5882 participants were recruited at the baseline survey in 2011, and 1230 participants completed the follow-up survey over 7 years. The CHARLS included the surveys on grandparenting and cognitive assessments. Grandparenting was categorized as yes and no. Cognitive function was measured by episodic memory and mental intactness. The association between grandparenting and cognitive function was analyzed in cross-sectional and 7-year follow-up models. Finally, the bootstrap method tests the mediating effect of children’s intergenerational support. Results Both cross-sectional and longitudinal studies presented that grandparenting was positively related to increase the cognitive function in middle-aged and older Chinese (B = 0.231, p < 0.05; B = 0.217, p < 0.05). Children’s emotional support and economic support played intermediary roles between grandparenting and cognitive function. Conclusion The findings emphasize the importance for policymakers to consider the impact of intergenerational care and family support when implementing new policies related to social services for middle-aged and older Chinese.

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The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study

Cited by 16 publications

References 55 publications

Prediction model for cognitive frailty in older adults: A systematic review and critical appraisal

Prediction model for cognitive frailty in older adults: A systematic review and critical appraisal

Understanding exogenous factors and biological mechanisms for cognitive frailty: a multidisciplinary scoping review

Association between Grandparenting and Cognitive Function in Middle-Aged and Older Chinese: the mediation role of Children’s Intergenerational Support—A nationally representative cohort study

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