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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.

Predicting Adverse Outcomes in Heart Failure Patients Using Different Frailty Status Measures