Heart failure management guided by remote multiparameter monitoring: A meta-analysis

BACKGROUND: Several implant-based remote monitoring strategies are currently tested to optimize heart failure (HF) management by anticipating clinical decompensation and preventing hospitalization. Among these solutions, the modern implantable cardioverter-defibrillator and cardiac resynchronization therapy devices have been equipped with sensors allowing continuous monitoring of multiple preclinical markers of worsening HF, including factors of autonomic adaptation, patient activity, and intrathoracic impedance. OBJECTIVES: We aimed to assess whether implant-based multiparameter remote monitoring strategy for guided HF management improves clinical outcomes when compared to standard clinical care. METHODS: A systematic literature research for randomized controlled trials (RCTs) comparing multiparameter-guided HF management versus standard of care was performed on PubMed, Embase, and CENTRAL databases. Incidence rate ratios (IRRs) and associated 95% confidence intervals (CIs) were calculated using the Poisson regression model with random study effects. The primary outcome was a composite of all-cause death and HF hospitalization events, whereas secondary endpoints included the individual components of the primary outcome. RESULTS: Our meta-analysis included 6 RCTs, amounting to a total of 4869 patients with an average follow-up time of 18 months. Compared with standard clinical management, the multiparameter-guided strategy reduced the risk of the primary composite outcome (IRR 0.83, 95%CI 0.71-0.99), driven by statistically significant effect on both HF hospitalization events (IRR 0.75, 95%CI 0.61-0.93) and all-cause death (IRR 0.80, 95%CI 0.66-0.96). CONCLUSION: Implant-based multiparameter remote monitoring strategy for guided HF management is associated with significant benefit on clinical outcomes compared to standard clinical care, providing a benefit on both hospitalization events and all-cause death.