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我们从应用于重症监护的网络荟萃分析中学到了什么?

What have we learned from network meta-analyses applied to critical care?

机构信息

Intensive Care Unit, HM Sanchinarro University Hospital, Madrid, Spain.

Department of Emergency Medicine, HM Sanchinarro University Hospital, Madrid, Spain.

出版信息

Minerva Anestesiol. 2019 Apr;85(4):433-442. doi: 10.23736/S0375-9393.19.13267-1. Epub 2019 Feb 7.

Abstract

It is widely accepted in modern medicine that medical decisions must be supported by scientific evidence. Identifying the best intervention when several options are available constitute a great challenge for every clinician. Traditional meta-analysis (TMA) allows summarizing evidence from studies that compare the same two interventions for one event (head to head studies or direct comparisons). Network meta-analysis (NMA) is a relatively new procedure that allows to compare multiple interventions for one event, even when non-head to head studies have been conducted (indirect evidence). Other advantages of NMA include increasing the accuracy of the results and ranking all the interventions according to their effectiveness. These features are of paramount importance as: 1) they summarize information from events (e.g. diseases or outcomes) that has more than two possible interventions (e.g. treatments or procedures); 2) they strengthen the level of guideline recommendations; and 3) they identify new hypotheses based on indirect comparison. As this is a narrative review, all manuscripts have been selected from PubMed according to our best knowledge with the aim to illustrate different features, options or applications of NMA in critical care. First, we provide a description of the usefulness, interpretation, assumptions and main plots related to NMAs. Second, we analyzed some examples of NMAs related to critical care medicine. Third, we include a pragmatic approach about how results from NMAs can improve the clinical practice as well an R script with a database to conduct an NMAs and reproduce figures and tables that have been shown here. As a conclusion, NMA is an established, robust, objective and reproducible statistic technique that has been applied to several critical care areas. Clinical practice guidelines have started to include NMA evidence to support their recommendations. In future years, it seems highly probable that this technique will increase it applicability in almost all areas of critical care medicine.

摘要

在现代医学中,人们普遍认为医疗决策必须以科学证据为依据。当有多种选择时,确定最佳干预措施对每个临床医生来说都是一项巨大的挑战。传统的荟萃分析(TMA)允许总结比较两种相同干预措施用于同一事件的研究证据(头对头研究或直接比较)。网络荟萃分析(NMA)是一种相对较新的程序,它允许比较用于同一事件的多种干预措施,即使进行了非头对头研究(间接证据)。NMA 的其他优点包括提高结果的准确性并根据有效性对所有干预措施进行排名。这些功能至关重要,因为:1)它们从具有两个以上可能干预措施(例如治疗或程序)的事件(例如疾病或结局)中汇总信息;2)它们增强了指南推荐的级别;3)它们基于间接比较确定新的假设。由于这是一篇叙述性综述,根据我们的最佳知识,从 PubMed 中选择了所有的手稿,旨在说明 NMA 在危重病医学中的不同特征、选项或应用。首先,我们提供了 NMA 的有用性、解释、假设和主要情节的描述。其次,我们分析了一些与危重病医学相关的 NMA 示例。第三,我们包括了如何通过 NMA 改善临床实践的实用方法,以及一个 R 脚本和一个数据库,以进行 NMA 并重现这里显示的图形和表格。总之,NMA 是一种成熟、稳健、客观和可重复的统计技术,已应用于多个危重病领域。临床实践指南已开始纳入 NMA 证据以支持其建议。在未来几年,这项技术似乎极有可能在危重病医学的几乎所有领域增加其适用性。

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