Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease (Jul 2019)
Incremental Value of Implantable Cardiac Device Diagnostic Variables Over Clinical Parameters to Predict Mortality in Patients With Mild to Moderate Heart Failure
Abstract
Background Heart failure remains a leading cause of morbidity and mortality. Clinical prediction models provide suboptimal estimates of mortality in this population. We sought to determine the incremental value of implantable device diagnostics over clinical prediction models for mortality. Methods and Results RAFT (Resynchronization/Defibrillation for Ambulatory Heart Failure Trial) patients with implanted devices capable of device diagnostic monitoring were included, and demographic and clinical parameters were used to compute Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) heart failure risk scores. Patients were classified according to MAGGIC score into low (0–16), intermediate (17–24), or high (>24) risk groups. Mortality was evaluated from 6 months postimplant in accordance with the RAFT protocol. In a subset of 1036 patients, multivariable analysis revealed that intermediate and high MAGGIC scores, fluid index, atrial fibrillation, and low activity flags were independent predictors of mortality. A device‐integrated diagnostic parameter that included a fluid index flag and either a positive atrial fibrillation flag or a positive activity flag was able to significantly differentiate higher from lower risk for mortality in the intermediate MAGGIC cohort. The effect was more pronounced in the high‐risk MAGGIC cohort, in which device‐integrated diagnostic–positive patients had a shorter time to death than those who were device‐integrated diagnostic negative. Conclusions Device diagnostics using a combination of fluid index trends, atrial fibrillation burden, and patient activity provide significant incremental prognostic value over clinical heart failure prediction scores in higher‐risk patients. This suggests that combining clinical and device diagnostic parameters may lead to models with better predictive power. Whether this risk is modifiable with early medical intervention would warrant further studies. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00251251.
Keywords