Few studies have directly compared the ability of the most commonly used models of frailty to predict mortality among community-dwelling individuals. Here, we used a frailty index (FI), frailty phenotype (FP), and FRAIL scale (FS) to predict mortality in the EMAS. Participants were aged 40-79 years (n=2929) at baseline and 6.6% (n=193) died over a median 4.3 years of follow-up. The FI was generated from 39 deficits, including self-reported health, morbidities, functional performance and psychological assessments. The FP and FS consisted of five phenotypic criteria and both categorized individuals as robust when they had 0 criteria, prefrail as 1-2 criteria and frail as 3+ criteria. The mean FI increased linearly with age (r(2)=0.21) and in Cox regression models adjusted for age, center, smoking and partner status the hazard ratio (HR) for death for each unit increase of the FI was 1.49. Men who were prefrail or frail by either the FP or FS definitions, had a significantly increased risk of death compared to their robust counterparts. Compared to robust men, those who were FP frail at baseline had a HR for death of 3.84, while those who were FS frail had a HR of 3.87. All three frailty models significantly predicted future mortality among community-dwelling, middle-aged and older European men after adjusting for potential confounders. Our data suggest that the choice of frailty model may not be of paramount importance when predicting future risk of death, enabling flexibility in the approach used.
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http://dx.doi.org/10.1016/j.archger.2013.06.010 | DOI Listing |
Int J Nurs Stud Adv
June 2025
Oregon Health & Science University School of Nursing, Portland, OR, USA.
Background: Many adults with heart failure (HF) are physically frail and have worse outcomes. While the biological profile of physical frailty in HF has been examined, the behavioral profile remains unstudied. Physical frailty may impact self-care behaviors, particularly symptom monitoring and management (SMM), which in turn results in adverse outcomes.
View Article and Find Full Text PDFJ Appl Stat
May 2024
Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, CA, Canada.
Survival analysis often involves modeling hazard functions while considering frailty to account for unobserved cluster-level factors in clustered survival data. Shared frailty models have gained popularity for this purpose, but assessing covariate functional form in these models presents unique challenges. Martingale and deviance residuals are commonly used for visually assessing covariate functional form against continuous covariates.
View Article and Find Full Text PDFJ Appl Stat
May 2024
Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, São Paulo, Brazil.
Survival data analysis often uses the Cox proportional hazards (PH) model. This model is widely applied due to its straightforward interpretation of the hazard ratio under the assumption that the hazard rates for two subjects remain constant over time. However, in several randomized clinical trials with long-term survival data comparing two new treatments, it is frequently observed that Kaplan-Meier plots exhibit crossing survival curves.
View Article and Find Full Text PDFIntroduction: Physical Activity (PA) and its links to frailty, quality of life (QoL), and other comorbidities in older Ugandans living with HIV remain under-explored.
Methods: We analyzed data from three annual assessments of older people living with HIV (PLWH) and age- and sex-similar people not living with HIV (PnLWH). We fitted linear generalized estimating equations (GEE) regression models to estimate the correlates of PA, including demographics, frailty, QoL, HIV, and other comorbidities.
J Clin Nurs
January 2025
School of Nursing and Rehabilitation, Shandong University, Jinan, Shandong, China.
Aim: This study aimed to identify the heterogeneous trajectories of frailty and determine the predictors of distinct trajectories in patients with heart failure.
Design: A longitudinal study.
Methods: A total of 253 patients with heart failure were recruited at the cardiology department of a tertiary hospital between February and December 2023.
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