%0 Journal Article
%T Longitudinal trajectories of frailty are associated with short-term mortality in older people: A joint latent class models analysis using two UK primary care databases.
%A Elhussein L
%A Robinson DE
%A Delmestri A
%A Clegg A
%A Prieto-Alhambra D
%A Silman A
%A Strauss VY
%J J Clin Epidemiol
%V 0
%N 0
%D 2024 Jun 26
%M 38942178
%F 7.407
%R 10.1016/j.jclinepi.2024.111442
%X <B>OBJECTIVE: </B>Frailty is a dynamic health state that changes over time. Our hypothesis was that there are identifiable subgroups of the older population that have specific patterns of deterioration. The objective of this study was to evaluate the application of joint latent class model (JLCM) in identifying trajectories of frailty progression over time and their group-specific risk of death in older people.<BR><B>METHODS: </B>The primary care records of UK patients, aged over 65 as of January 1st 2010, included in the CPRD: GOLD and AURUM databases, were analysed and linked to mortality data. Electronic frailty index (eFI) scores were calculated at baseline and annually in subsequent years (2010-2013). JLCM was used to divide the population into clusters with different trajectories and associated mortality hazard ratios (HR). The model was built in GOLD and validated in AURUM.<BR><B>RESULTS: </B>Five trajectory clusters were identified and characterised based on baseline and speed of progression: low-slow, low-moderate, low-rapid, high-slow and high-rapid. The high-rapid cluster had the highest average starting eFI score; 7.9, while low-rapid cluster had the steepest rate of eFI progression; 1.7. Taking the low-slow cluster as reference, low-rapid and high-rapid had the highest HRs: 3.73 (95%CI 3.71 to 3.76) and 3.63 (3.57 to 3.69), respectively. Good validation was found in the AURUM population.<BR><B>CONCLUSIONS: </B>Our research found that there are vulnerable subgroups of the older population who are currently frail or have rapid frailty progression. Such groups may be targeted for greater healthcare monitoring.