Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol.
Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol.
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DOI：
10.1136/bmjopen-2022-067260
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发表时间：
2023-03-13
期刊：
影响因子：
2.9
通讯作者：
中科院分区：
文献类型：
--
作者：
目前已经发表了数十种心脏手术后心房颤动的多变量预测模型，但没有一种被纳入常规的临床实践。这种缺乏采用的原因之一是由于模型开发中的方法缺陷而导致的模型性能较差。此外，对这些现有模型的外部验证很少，以评估它们的重复性和可移植性。这项系统综述的目的是批判性地评估提出AFAC模型开发和/或验证的论文的方法和偏差的风险。我们将通过在PubMed、Embase和Web of Science上的搜索，确定从最初到2021年12月31日期间开发和/或验证AFACS多变量预测模型的研究。成对的审查员将独立提取模型业绩衡量标准、评估方法质量并使用摘录表格评估纳入研究的偏差风险，摘录表格改编自《预测建模研究系统回顾的关键评估和数据提取》核对表和预测模型偏差风险评估工具。提取的信息将通过叙事综合和描述性统计进行报告。这项系统性审查将只包括已公布的汇总数据，因此不会使用受保护的健康信息。研究结果将通过同行评议的出版物和科学会议报告进行传播。此外，这篇综述将找出过去AFACS预测模型开发和验证方法中的弱点，以便后续研究能够改进先前的实践，并产生临床上有用的风险评估工具。CRD42019127329。
Dozens of multivariable prediction models for atrial fibrillation after cardiac surgery (AFACS) have been published, but none have been incorporated into regular clinical practice. One of the reasons for this lack of adoption is poor model performance due to methodological weaknesses in model development. In addition, there has been little external validation of these existing models to evaluate their reproducibility and transportability. The aim of this systematic review is to critically appraise the methodology and risk of bias of papers presenting the development and/or validation of models for AFACS. We will identify studies that present the development and/or validation of a multivariable prediction model for AFACS through searches of PubMed, Embase and Web of Science from inception to 31 December 2021. Pairs of reviewers will independently extract model performance measures, assess methodological quality and assess risk of bias of included studies using extraction forms adapted from a combination of the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and the Prediction Model Risk of Bias Assessment Tool. Extracted information will be reported by narrative synthesis and descriptive statistics. This systemic review will only include published aggregate data, so no protected health information will be used. Study findings will be disseminated through peer-reviewed publications and scientific conference presentations. Further, this review will identify weaknesses in past AFACS prediction model development and validation methodology so that subsequent studies can improve upon prior practices and produce a clinically useful risk estimation tool. CRD42019127329.
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影响因子：
6
作者：
Shen, Jeanne;Lall, Shelly;Zheng, Victoria;Buckley, Patricia;Damiano, Ralph J., Jr.;Schuessler, Richard B.
通讯作者：
Schuessler, Richard B.
影响因子：
2.7
作者：
Churyla, Andrei;Desai, Anand;McCarthy, Patrick
通讯作者：
McCarthy, Patrick
DOI：
10.1136/bmj.b2535
发表时间：
2009-07-21
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Moher D;Liberati A;Tetzlaff J;Altman DG;PRISMA Group
通讯作者：
PRISMA Group
影响因子：
9
作者：
Almassi, GH;Schowalter, T;Hammermeister, KE
通讯作者：
Hammermeister, KE
影响因子：
--
作者：
Lee, Randall J;Hanke, Thorsten
通讯作者：
Hanke, Thorsten