Prediction of Worsening Heart Failure Events and All-Cause Mortality Using an Individualized Risk Stratification Strategy
Michael R. Zile, Jodi Koehler, Shantanu Sarkar, Javed Butler
Abstract
AIMS: This study aimed to examine the clinical utility of a multisensor, remote, ambulatory diagnostic risk score, TriageHF™, in a real-world, unselected, large patient sample to predict heart failure events (HFEs) and all-cause mortality. METHODS AND RESULTS: database who had Medtronic implantable cardiac defibrillator device from 2007 to 2016. Patients were categorized into three risk groups based on probability for having an HFE within 6 months (low risk <5.4%, medium risk ≥5.4 < 20%, and high risk ≥20%). Data were analysed using three strategies: (i) scheduled monthly data download; (ii) alert-triggered data download; and (iii) daily data download. Study population consisted of 22 901 patients followed for 1.8 ± 1.3 years. Using monthly downloads, HFE risk over 30 days incrementally increased across risk categories (odds ratio: 2.8, 95% confidence interval: 2.5-3.2 for HFE, P < 0.001, low vs. medium risk, and odds ratio: 9.2, 95% confidence interval: 8.1-10.3, P < 0.001, medium vs. high risk). Findings were similar using the other two analytic strategies. Using a receiver operating characteristic curve analysis, sensitivity for predicting HFE over 30 days using high-risk score was 47% (alert triggered) and 51% (daily download) vs. 0.5 per patient year unexplained detection rate. TriageHF risk score also predicted all-cause mortality risk over 4 years. All-cause mortality risk was 14% in low risk, 20% in medium risk, and 38% in high risk. CONCLUSIONS: TriageHF risk score provides a multisensor remote, ambulatory diagnostic method that predicts both HFEs and all-cause mortality.