Predicting Adverse Outcomes in Heart Failure Patients Using Different Frailty Status Measures
Cheng, Y.; Shao, Y.; Weir, C.R.; Shah, R.U.; Bray, B.E.; Garvin, J.H.; Zeng-Treitler, Q.
Studies in Health Technology and Informatics 245: 327-331
2017
ISSN/ISBN: 1879-8365 PMID: 29295109 Document Number: 694114
Frailty is an important outcome predictor in older patients. We randomly sampled 12,000 veterans with heart failure diagnosed in 2010. The topic modeling method was applied to identify frailty-related topics from the clinical notes in the electronic medical records. The frailty topics were classified into five deficit areas including physical functioning (PF), role-physical (RP), general health (GH), social functioning (SF), and mental health (MH). We experimented with different covariates and four different frailty measures: individual frailty topics, number of distinct frailty topics, a dichotomous deficit category, and the number of distinct deficits, respectively. A total of 8,531 (71.1%) patients had at least one frailty topic. The prevalence of GH, PF, MH, SF, and RP deficits were 89.0%, 61.3%, 56.9%, 40.6%, and 9.5%, respectively. PF deficits (yes/no) and the number of distinct deficits were the most consistent, significant predictors of adverse outcomes of rehosptalization or death.