CIED-based remote monitoring in heart failure using the HeartLogic™ algorithm: Which patients benefit most?

ABSTRACT

BACKGROUND & AIMS: Early identification of worsening HF enables timely adjustments to prevent hospitalization. Recent studies show the HeartLogic™ algorithm detects congestion and reduces HF events. However, it is unclear which patients benefit most. Therefore, this study aims to identify and characterize HF patients who benefit most from CIED-based remote monitoring with HeartLogic™. METHODS: In this multicenter retrospective study, patients with a CIED and HeartLogic™ algorithm under structured follow-up were included. Patients were classified as having "substantial benefit" or "no benefit" from monitoring. RESULTS: In total, 242 patients were included (male n = 190, 79%, median age 61 years [IQR 61-77]). Median follow-up was 1.2 years [IQR 1.1-2.7]. Among 378 alerts, 266 were true positive (70%) and 112 false positive (30%). Of the 242 patients, 69 (29%) were classified as having "substantial benefit", while 173 (71%) had "no benefit" from HeartLogic™ monitoring. Univariate and multivariate analysis showed that patients with "substantial benefit" had higher NYHA functional class (OR 2.64, P = 0.004), higher NT-ProBNP (OR 1.02, P = 0.003), higher serum creatinine (OR 1.10, P < 0.001), lower LVEF (OR 1.19, P = 0.004), more severe mitral regurgitation (OR 2.16, P = 0.006), higher right ventricular end diastolic volume (OR 1.05, P = 0.040), higher pulmonary artery pressures (OR 1.19, P = 0.003), and were more likely to use loop diuretics (OR 2.79, P = 0.001). Among patients with "substantial benefit," the positive predictive value (PPV) of HeartLogic™ to detect congestion was 92%. CONCLUSION: The utilization of CIED-based HeartLogic™ driven HF care demonstrated pronounced efficacy, predominantly in patients exhibiting characteristics of HF at a more advanced disease stage.