Development and validation of cognitive ageing risk score (CARS) for early detection of subtle cognitive deficits in older people

Fung, Ada Wai Tung; Lee, Allen Ting Chun; Ma, Suk Ling; Lam, Linda Chiu Wa · 2024 · Crossref

DOI: 10.1186/s12877-024-04879-5

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Summary

This study addresses the challenge of early dementia detection in primary care, particularly within the Chinese older population, where existing risk models often fail to account for psychosocial factors and lifestyle characteristics specific to this demographic. The authors aimed to develop and validate the Cognitive Ageing Risk Score (CARS), a tool designed to estimate dementia risk based on a cluster of biopsychosocial risk factors. Additionally, the study sought to evaluate whether combining CARS with cognitive screening could better detect subtle, early cognitive deficits than screening alone. The research utilized two longitudinal cohorts of community-dwelling older adults. The development cohort consisted of 289 cognitively normal individuals followed for approximately six years, during which 24.9% converted to dementia. The validation cohort included 383 non-demented adults followed for roughly five years, with an 18.3% conversion rate. Risk factors were assessed through comprehensive evaluations of vascular health (hypertension, diabetes, hyperlipidemia), psychosocial status (loneliness, mental health), behavioral habits (physical exercise types, sleep quality), and genetic markers (ApoE4 status). The CARS was constructed using logistic regression coefficients derived from baseline differences between converters and non-converters. Two models were tested: Model 1 included vascular, psychosocial, and lifestyle factors, while Model 2 added ApoE4 status. The results identified significant risk factors including older age, male gender, lower education, poorly controlled diabetes, prolonged sleep latency, loneliness, fewer mind-body or light exercises, and ApoE4 carrier status. In the development cohort, Model 1 achieved an area under the curve (AUC) of 82.5%, with a cutoff score of -1.3 yielding 83.9% sensitivity and 75.4% specificity. Model 2, incorporating genetic risk, improved the AUC to 86.5%. In the validation cohort, CARS maintained significant predictive value with an AUC of 71.1%. Furthermore, combining CARS with computerized cognitive screening revealed that early cognitive deficits were specifically characterized by impaired retention and attention, distinguishing high-risk individuals from those with normal aging. The study concludes that CARS is a valid tool for assessing dementia risk in older Chinese adults, effectively integrating vascular, psychosocial, and lifestyle risks. The findings suggest that CARS can be used independently for risk stratification or in conjunction with cognitive screening to identify specific early deficits. This approach supports a shift in primary care from reactive diagnostic testing to proactive, personalized lifestyle interventions. The authors advocate for integrating such risk algorithms into smart healthcare systems to facilitate early detection and targeted prevention strategies for dementia.

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• cognitive impairment