Background: Frailty can be measured in relation to the accumulation of deficits using a frailty index. A frailty index can be developed from most ageing databases. Our objective is to systematically describe a standard procedure for constructing a frailty index.

OBJECTIVES To investigate how changes in frailty status and mortality risk relate to baseline frailty state, mobility performance, age and sex. SETTING The Yale Precipitating Events Project, a cohort study based in New Haven CT. PARTICIPANTS 754 community-dwelling people, aged 70+ years at baseline followed-up at 18, 36 and 54 months. METHODS Frailty status, assessed at 18-month intervals, was defined by a frailty index, as the number of deficits in 36 health variables. Mobility was defined as the time in seconds on the rapid gait test, where participants walked back and forth over a 20-ft course as quickly as possible. Multi-state transition probabilities were calculated with baseline frailty, mobility, age and sex estimated by Poisson and logistic regressions in survivors and those who died, respectively. RESULTS In multivariable analyses, baseline frailty status and age were significantly associated with changes in frailty status and the risk of death, while mobility was significantly associated with the former, but not with mortality. At all values of the frailty index, compared to those with poor mobility, participants with better mobility were more likely to remain stable or to improve. For example, at 54 months, 20.6% (95% confidence interval (CI) =16–25.2) of participants with poor mobility had the same or fewer deficits compared to 32.4% (95% CI=27.9–36.9) of those with better mobility. CONCLUSION A multi-state transition model effectively measured the probability of changes in frailty status and in the risk of death. Mobility, age and baseline frailty were significant factors in frailty state transitions.

Background the Clinical Frailty Scale (CFS) was originally developed to summarise a Comprehensive Geriatric Assessment and yield a care plan. Especially since COVID-19, the CFS is being used widely by health care professionals without training in frailty care as a resource allocation tool and for care rationing. CFS scoring by inexperienced raters might not always reflect expert judgement. For these raters, we developed a new classification tree to assist with routine CFS scoring. Here, we test that tree against clinical scoring. Objective/Methods we examined agreement between the CFS classification tree and CFS scoring by novice raters (clerks/residents), and the CFS classification tree and CFS scoring by experienced raters (geriatricians) in 115 older adults (mean age 78.0 ± 7.3; 47% females) from a single centre. Results the intraclass correlation coefficient (ICC) for the CFS classification tree was 0.833 (95% CI: 0.768–0.882) when compared with the geriatricians’ CFS scoring. In 93%, the classification tree rating was the same or differed by at most one level with the expert geriatrician ratings. The ICC was 0.805 (0.685–0.883) when CFS scores from the classification tree were compared with the clerk/resident scores; 88.5% of the ratings were the same or ±1 level. Conclusions a classification tree for scoring the CFS can help with reliable scoring by relatively inexperienced raters. Though an incomplete remedy, a classification tree is a useful support to decision-making and could be used to aid routine scoring of the CFS.

Aging occurs as a series of small steps, first causing cellular damage and then affecting tissues and organs. This is also true in the brain. Frailty, a state of increased risk due to accelerated deficit accumulation, is robustly a risk factor for cognitive impairment. Community-based autopsy studies show that frail individuals have brains that show multiple deficits without necessarily demonstrating cognitive impairment. These facts cast a new light on the growing number of risk factors for cognitive impairment, suggesting that, on a population basis, most health deficits can be associated with late-life cognitive impairment. The systems mechanism by which things that are bad for the body are likely to be bad for the brain can be understood like this: the burden of health deficits anywhere indicates impaired ability to withstand or repair endogenous and environmental damage. This in turn makes additional damage more likely. If true, this suggests that a life course approach to preventing cognitive impairment is desirable. Furthermore, conducting studies in highly selected, younger, healthier individuals to provide ‘proof of concept’ information is now common. This strategy might exclude the very circumstances that are required for disease expression in the people in whom dementia chiefly occurs (that is, older adults who are often in poor health).