Prevalence of Frailty in Patients Referred to the Kidney Transplant Waitlist

Abstract

Background: Comparisons between frailty assessment tools for waitlist candidates are a recognized priority area for kidney transplantation. We compared the prevalence of frailty using three established tools in a cohort of waitlist candidates. Methods: Waitlist candidates were prospectively enrolled from 2016-2020 across five centers. Frailty was measured using the Frailty Phenotype (FP, as well as a 37 variable Frailty Index (FI), and the Clinical Frailty Scale (CFS). The FI and CFS were dichotomized using established cut-offs. Agreement was compared using kappa coefficients. Area under the receiver operator characteristic curves were generated to compare the FI and CFS (treated as continuous measures) to the FP. Unadjusted associations between each frailty measure and time to death or waitlist withdrawal were determined using an unadjusted Cox proportional hazards model. Results: Of 542 enrolled patients, 64% were male, 80% were white, and the mean age was 54+/-14. The prevalence of frailty by the FP was 16%. The mean FI score was 0.23+/-0.14 and the prevalence of frailty was 38% (score of >0.25). The median CFS score was 3 (IQR 2,3), and the prevalence was 15% (score of ≥4). Kappa values comparing the FP to the FI (0.438) and CFS (0.272) showed fair to moderate agreement. Area under the ROC curve for the FP and FI/CFS were 0.86 (good) and 0.69 (poor) respectively. Frailty by the CFS (HR 2.10; 95% CI (1.04, 4.24) and FI (HR 1.79; 95% CI 1.00,3.21) was associated with death or permanent withdrawal. The association between frailty by the FP and death/withdrawal was not statistically significant (HR 1.78; CI 0.786, 3.71). Conclusion: Frailty prevalence varies by measurement tool used, and agreement between these measurements is fair to moderate. This has implications for determining the optimal frailty screening tool for use in those being evaluated for kidney transplant.

Prevalence of frailty and cognitive impairment in older transplant candidates - a preview to the Kidney Transplantation in Older People (KTOP): impact of frailty on outcomes study

“…The estimate of cognitive impairment reported here is therefore still likely to be reliable, as there is little to suggest that cognitive impairment should be higher in those people who do not speak fluent English. Similarly, the use of only a single tool to assess frailty (EFS) and cognition (MoCA) may limit our results, as prior studies have demonstrated disparity in detection of these syndromes when multiple tools are used [ 18 , 40 ]. Multiple assessments for frailty and cognition were not used to avoid placing a high burden of questionnaires on the participants, and instead maximise their engagement across all other study questionnaires.…”

Is It Time to Integrate Frailty Assessment in Onconephrology?

“…Variables need to have characteristic properties; they must be associated with health status, their prevalence must increase with age, they cannot saturate too early, they must consider a range of systems, and the items must be the same if being evaluated serially on the same population. Although less well studied in kidney disease, higher severity of frailty using an FI approach is associated with morbidity and mortality in dialysis and for those waiting for a kidney transplant [ 32 , 33 ]. While more biologically representative of the construct of frailty, FIs may be cumbersome, especially if data to develop them are lacking or hard to acquire.…”

“…However, while pragmatic tools based on clinical impression (such as the CFS) allow more efficiency and easier incorporation into clinical care, they are subjective. Interestingly, it has been shown that clinical impressions of frailty (either by patients or providers) do not always demonstrate a high level of agreement with objective measures [ 11 , 33 , 37 , 38 ].…”

“…While each has its own strengths and limitations, perhaps even more emphasis should be placed on using multiple tools that capture different aspects of frailty. It has been shown that there is limited overlap in the proportions of patients identified as being frail when measured using different tools, although each independently predicts poor health outcomes [ 33 , 37 ]. However, while the use of multiple tools may ensure a more global picture of frailty, it is limited by issues of pragmatism and practicality.…”

“…In studies of both kidney disease and cancer, cognitive impairment has been shown to have a direct impact on treatment (dialysis, transplant, and chemotherapy) outcomes and may underlie the reason not to pursue treatment. Although most frailty measures focus solely on physical frailty, the FI (being broadly aimed at capturing impairments in multiple health domains) often does include some metric of cognitive impairment, if included as one of the domains [ 31 , 33 ].…”