Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
West China Medical School, Sichuan University, Chengdu, China.
PLoS One. 2022 Sep 29;17(9):e0268446. doi: 10.1371/journal.pone.0268446. eCollection 2022.
The objective of this paper is to design a protocol for a systematic review and meta-analysis on the effectiveness of self-management interventions in patients with chronic heart failure.
The protocol is developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered in PROSPERO (CRD42021246973). Base on the population, intervention, comparator, and outcome (PICO) framework, our research questions are: 1) What are the effects of eHealth self-management interventions on patients with chronic heart failure? 2) What factors of interventions might affect outcomes? The process includes: 1) search strategy and inclusion criteria; 2) data extraction; 3) risk of bias assessment and 4) data analysis. Searching process and data extraction will be guided by Cochrane Handbook for Systematic Reviews of Interventions. We will use Cochrane Risk of Bias tool to assess the risk of bias. The data analysis will be performed using Metafor package in R.
This systemic review will synthesize the current evidence and identify gaps. Findings in the meta-analysis will provide guidance for designing a more effective self-management intervention for patients with chronic heart failure in future.
本文旨在设计一项关于慢性心力衰竭患者自我管理干预效果的系统评价和荟萃分析的方案。
本方案遵循系统评价和荟萃分析的首选报告项目（PRISMA）指南制定。该方案已在 PROSPERO（CRD42021246973）中注册。根据人群、干预、对照和结局（PICO）框架，我们的研究问题是：1）电子健康自我管理干预对慢性心力衰竭患者有何影响？2）干预的哪些因素可能影响结局？该过程包括：1）搜索策略和纳入标准；2）数据提取；3）偏倚风险评估和 4）数据分析。搜索过程和数据提取将由 Cochrane 干预系统评价手册指导。我们将使用 Cochrane 偏倚风险工具评估偏倚风险。Metafor 包将用于 R 中的数据分析。
本系统评价将综合现有证据并确定差距。荟萃分析的结果将为未来为慢性心力衰竭患者设计更有效的自我管理干预提供指导。
