Key result
CV RCT frailty indices comprise ~47% cardiometabolic deficits, underrepresenting physical function vs observational studies.
Why the study?
Cumulative deficit frailty indices from RCTs are increasingly used to evaluate findings in frailty, but some have been criticized for including too narrow a range of deficits.
Do frailty indices applied to cardiovascular RCTs measure the same range and type of deficits as those in observational studies?
Do frailty indices applied to cardiovascular RCTs measure the same range and type of deficits as those in observational studies?
Frailty indices used in cardiovascular RCTs focus heavily on cardiometabolic deficits rather than physical function, suggesting they may not adequately capture the broad physiological vulnerability of frailty seen in clinical practice.
Answers are grounded in this paper and cite their sources.
May limit applicability of cardiovascular RCT frailty findings; leaves open whether broader deficit inclusion improves clinical capture.
Background Cumulative deficit frailty indices (FI) from randomised controlled trials (RCT) are increasingly used to assess whether trial findings are applicable to people living with frailty. However, some applications of the frailty index have been criticised for including to narrow a range of deficits. The aim of this analysis is to examine the range and type of deficits included in these frailty indices and compared these to those from observational studies. Methods We identified 19 RCTs assessing treatment effect modification using the FI, as well as 18 observational studies assessing mortality risk associated with frailty, from recent systematic reviews. We extracted the FI deficits included from each study. We compared the number of deficits, data sources (e.g. medical history, physical measurements, questionnaires) and physiological domain (e.g. cardiometabolic, neuro-cognitive, physical function) of the deficits from each source. Results The number of deficits was similar between RCT frailty indices (median 41 deficits, interquartile range [IQR] 35–50) and observational studies (median 35, interquartile range 31–45). Broadly similar data sources were used to identify deficits. However, in RCTs of cardiovascular conditions, cardiometabolic deficits made up a greater proportion of deficits (median 47% of included deficits, IQR 38%–51%, compared to 19%, 14%–24%, in observational studies). Cardiovascular RCTs included fewer physical function measures (median 4% [3%–9%], compared to 16% in other RCTs of other conditions [13%–17%], 17% in observational [13%–23%]). Conclusion In many cardiovascular RCTs, FIs focus on cardiometabolic deficits rather than measures of function. It cannot be assumed that these FIs adequately capture the broad physiological vulnerability that characterises frailty in clinical practice. We need to establish if such indices adequately capture risk of outcomes of importance to people living with frailty if such studies are to inform care. Until then, caution is required when assessing applicability of trials to people living with frailty.
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Bousetta et al. (2026) studied this question. Frailty indices in cardiovascular RCTs overrepresent cardiometabolic deficits (47%) and underrepresent physical function versus observational studies, limiting frailty capture.
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