Why the study?
Does a heart failure risk status (HFRS) algorithm improve risk stratification for cardiovascular hospitalization in patients with a cardiac resynchronization therapy defibrillator?
Does a heart failure risk status (HFRS) algorithm improve risk stratification for cardiovascular hospitalization in patients with a cardiac resynchronization therapy defibrillator?
An automated heart failure risk status algorithm using CRT-D diagnostics can effectively stratify patients at high risk for near-term cardiovascular and heart failure hospitalizations, potentially aiding in the triage of remote monitoring alerts.
May aid triage of remote CRT-D monitoring alerts; leaves open whether acting on this automated risk.
Aims: Cardiac resynchronization therapy defibrillators (CRT-D) are able to monitor various parameters that may be combined by an automatic algorithm to provide a heart failure risk status (HFRS). We sought to validate the HFRS for stratifying patient risk, evaluate its association with heart failure (HF) symptoms, and investigate its utility for triage of automatic alerts. Methods and results: Data from 722 patients included in the MORE-CARE trial were analysed in a post hoc analysis. A high HFRS was associated with a significantly increased risk of admission over the next 30 days with a relative risk for cardiovascular hospitalization (CVH) of 4.5 (95% CI: 3.1-6.6, P < 0.001), of HF hospitalization of 6.3 (95% CI: 3.9-10.2, P < 0.001) and of non-HF related CVH of 3.5 (95% CI: 2.0-6.9, P < 0.001). The negative predictive value of low or medium HFRS for these admissions was ≥98%. A high HFRS was associated with an increased risk of HF symptoms. Of all the automatic remote monitoring alerts generated during the study, only 10% had a high HFRS. Conclusion: The HFRS is able to risk-stratify CRT-D patients, which is potentially useful for managing automatic remote monitoring alerts, by focusing attention on the minority of high-risk patients. Clinical Trial Registration: The trial was registered at www.clinicaltrials.gov under number NCT00885677.
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Burri et al. (2017) studied this question.
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