Comparative effectiveness of ehealth self-management interventions for patients with heart failure: A Bayesian network meta-analysis.
meta_analysis · Level I
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- Record sourced from PubMed, PMID 38613991.
- Also identified by DOI 10.1016/j.pec.2024.108277.
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Abstract
This study evaluated the effectiveness of electronic self-management support interventions in reducing all-cause mortality, cardiovascular mortality, readmission rates, and HF-related readmission in heart failure patients. Following the PRISMA-P guidelines and PRISMS taxonomy, we searched Pubmed, Cochrane Library, and Embase for RCTs and trials of electronic health technologies for heart failure interventions. Develop support programs in advance for education, monitoring, reminders, or a combination of these to screen and categorize studies. The Cochrane ROB2 tool was used to assess the risk of bias. The monitoring interventions may improve all-cause mortality (OR 0.77, 95% CI 0.63 to 0.93) and cardiovascular mortality (OR 0.75, 95% CI 0.61 to 0.93) compared to usual care. Reminder interventions were associated with significantly reducing readmission rates (OR 0.07, 95% CI 0.00 to 0.94). Mixed interventions were most effective in reducing HF-related readmission rates (OR 0.75, 95% CI 0.56 to 0.99). Electronic self-management interventions, particularly monitoring and reminders, can potentially improve outcomes of heart failure patients, including reducing all-cause mortality, cardiovascular mortality, and readmission rates. The eHealth model and the combination of self-management are significant for long-term intervention in patients with HF to improve their quality of life and prognosis.
Medical subject headings
- Heart Failure
- Telemedicine
- Self-Management
- Bayes Theorem