Remote haemodynamic-guided care for patients with chronic heart failure: a meta-analysis of completed trials

Eur J Heart Fail. 2017 Mar;19(3):426-433. doi: 10.1002/ejhf.638. Epub 2016 Sep 16.

Abstract

Aims: Haemodynamic-guided heart failure (HF) management using directly measured cardiac filling pressures in symptomatic patients is now recommended in the European Society of Cardiology (ESC) Heart Failure Guidelines [Class IIb(B)]. This meta-analysis evaluates all data from completed clinical trials evaluating this approach in patients with HF.

Methods and results: All trials evaluating the impact of HF management based on haemodynamic monitoring using implantable devices were reviewed using standard search engine methods. PRISMA methods were used to evaluate and screen publications that included an evaluation of an effect on HF hospitalizations. All publications meeting the inclusion criteria were included, and the outcomes data were evaluated using standard meta-analysis methodology. Of 317 publications initially identified, five trials involving 1296 patients with chronic HF met the criteria used in this meta-analysis. Studies included prospective controlled designs, as well as observational studies with historical control. Heterogeneity testing failed to demonstrate instability of analysis due to differences between trials. When compiled, outcomes from these trials favoured remote haemodynamic monitoring with a significant 38% reduction in HF hospitalizations (hazard ratio 0.62, 95% confidence interval 0.50-0.78, P < 0.001).

Conclusions: Haemodynamic-guided HF management using permanently implanted sensors and frequent filling pressure evaluation is superior to traditional clinical management strategies in reducing long-term HF hospitalization risk in symptomatic patients.

Keywords: Haemodynamic monitoring; Heart failure; Hospitalizations; Meta-analysis.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chronic Disease
  • Clinical Trials as Topic
  • Disease Management
  • Heart Failure / therapy*
  • Hemodynamics*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Monitoring, Ambulatory*
  • Proportional Hazards Models