Efendi Defi, Cheng Adam, Wanda Dessie, Furukawa Toshi A, Petropoulou Maria, Efthimiou Orestis, Chen Kee-Hsin
Department of Pediatric Nursing, Faculty of Nursing, Universitas Indonesia, Depok, Indonesia.
Neonatal Intensive Care Unit, Universitas Indonesia Hospital, Depok, Indonesia.
BMJ Open. 2025 Jul 25;15(7):e094869. doi: 10.1136/bmjopen-2024-094869.
The necessity of enhancing resuscitation training has been encouraged by The International Liaison Committee on Resuscitation and the American Heart Association to reduce mortality, disability and healthcare costs. Resuscitation training is a complicated approach that encompasses various components and their mixture. It is essential to identify the most effective of these components and their combinations, to measure the corresponding effect size and to understand which participant groups may enjoy the greatest advantage.
We will systematically search 12 databases and two clinical trial registries for randomised controlled trials (RCTs) that examine different resuscitation training methods from inception to April 2025. The analysis will be carried out using the standard network meta-analysis and component network meta-analysis models. Resuscitation skills of staff will be the primary outcome of this analysis. Paired reviewers will independently screen and extract data. A consensus will be sought with the principal investigators to resolve any disagreements that cannot be achieved through regular meetings. Each intervention in each RCT will be decomposed according to its constituent components, such as delivery method, interactivity, teamwork, digitalisation and type of simulator. The analysis will be conducted using the frequentist and bayesian approach in the R environment. RoB V.2.0 and Confidence in Network Meta-Analysis will, respectively, be used to assess the risk of bias and the certainty of the evidence.
As we will use only aggregated secondary data without individual identities, ethical approval is not required. Results of this review will be shared through a peer-reviewed publication and presentation of papers at any relevant conferences.
CRD42024532878.
国际复苏联合委员会和美国心脏协会鼓励加强复苏培训，以降低死亡率、残疾率和医疗成本。复苏培训是一种复杂的方法，涵盖各种组成部分及其组合。确定这些组成部分中最有效的部分及其组合、测量相应的效应大小以及了解哪些参与者群体可能受益最大至关重要。
我们将系统检索12个数据库和两个临床试验注册库，以查找从开始到2025年4月期间检验不同复苏培训方法的随机对照试验（RCT）。分析将使用标准网络荟萃分析和成分网络荟萃分析模型进行。工作人员的复苏技能将是该分析的主要结果。配对的评审员将独立筛选和提取数据。将与主要研究者寻求共识，以解决通过定期会议无法达成的任何分歧。每个RCT中的每项干预措施将根据其组成部分进行分解，例如授课方式、互动性、团队合作、数字化和模拟器类型。分析将在R环境中使用频率学派和贝叶斯方法进行。将分别使用RoB V.2.0和网络荟萃分析的可信度来评估偏倚风险和证据的确定性。
由于我们仅使用无个人身份信息的汇总二级数据，因此无需伦理批准。本综述的结果将通过同行评审出版物以及在任何相关会议上发表论文来分享。
PROSPERO注册号：CRD42024532878。
