Faculty, Staff and Student Publications
Publication Date
3-1-2023
Journal
The American Journal of Cardiology
Abstract
Frailty is associated with adverse outcomes in heart failure (HF). A parsimonious frailty index (FI) that predicts outcomes of older, multimorbid patients with HF could be a useful resource for clinicians. A retrospective study of veterans hospitalized from October 2015 to October 2018 with HF, aged ≥50 years, and discharged home developed a 10-item parsimonious FI using machine learning from diagnostic codes, laboratory results, vital signs, and ejection fraction (EF) from outpatient encounters. An unsupervised clustering technique identified 5 FI strata: severely frail, moderately frail, mildly frail, prefrail, and robust. We report hazard ratios (HRs) of mortality, adjusting for age, gender, race, and EF and odds ratios (ORs) for 30-day and 1-year emergency department visits and all-cause hospitalizations after discharge. We identified 37,431 veterans (age, 73 ± 10 years; co-morbidity index, 5 ± 3; 43.5% with EF ≤40%). All frailty groups had a higher mortality than the robust group: severely frail (HR 2.63, 95% confidence interval [CI] 2.42 to 2.86), moderately frail (HR 2.04, 95% CI 1.87 to 2.22), mildly frail (HR 1.60, 95% CI 1.47 to 1.74), and prefrail (HR 1.18, 95% CI: 1.07 to 1.29). The associations between frailty and mortality remained unchanged in the stratified analysis by age or EF. The combined (severely, moderately, and mildly) frail group had higher odds of 30-day emergency visits (OR 1.62, 95% CI 1.43 to 1.83), all-cause readmission (OR, 1.75, 95% CI 1.52 to 2.02), 1-year emergency visits (OR 1.70, 95% CI 1.53 to 1.89), rehospitalization (OR 2.18, 95% CI 1.97 to 2.41) than the robust group. In conclusion, a 10-item FI is associated with postdischarge outcomes among patients discharged home after a hospitalization for HF. A parsimonious FI may aid clinical prediction at the point of care.
Keywords
Aged, Humans, Adult, Middle Aged, Aged, 80 and over, Frailty, Frail Elderly, Retrospective Studies, Aftercare, Patient Discharge, Heart Failure, Hospitalization, Machine Learning, Geriatric Assessment, congestive heart failure, Frailty index, accumulation of deficit, machine learning
DOI
10.1016/j.amjcard.2022.11.044
PMID
36566620
PMCID
PMC9951585
PubMedCentral® Posted Date
3-1-2023
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes