Oklahoma State University Center for Health Sciences, Dept. of Institutional Research, United States of America.
Oklahoma State University Medical Center, Internal Medicine, United States of America.
Am J Emerg Med. 2019 Dec;37(12):2229-2238. doi: 10.1016/j.ajem.2019.03.038. Epub 2019 Mar 28.
The fragility index (FI) is calculated by iteratively changing one outcome "event" to a "non-event" within a trial until the associated p-value exceeds 0.05.
To investigate the FI and fragility quotient (FQ) of trial endpoints referenced in the ACCF/AHA/SCAI guidelines in the management of ST-elevation myocardial infarctions. Secondarily, we assess the post-hoc power and risk of bias for these specific outcomes and whether differences exist between adequately and inadequately powered studies on fragility measures.
All citations referenced in the guideline were screened for inclusion criteria. The FI and FQ for all included trials were then calculated. The Cochrane 'risk of bias' Tool 2.0 was used to evaluate the likelihood and sources of bias in the included trials.
Forty-two randomized controlled trials were included for assessment. The median FI was 10 with a FQ of 0.0055. Seven trials were at a high risk of bias, all due to bias in the randomization process. Fifteen trials were found to be underpowered. Adequately powered studies had higher FIs and FQs compared to underpowered studies.
Our findings support the use of FI and FQ analyses with power analyses in future methodology of randomized control trials. With understanding and reporting of FI and FQ, evidence of studies can be readily available and quickly eliminate some readers' concern for possible study limitations.
脆弱指数(FI)是通过在试验中反复将一个结局“事件”更改为“非事件”来计算的,直到相关的 p 值超过 0.05。
调查 ACCF/AHA/SCAI 指南中提到的 ST 段抬高型心肌梗死管理中试验终点的 FI 和脆弱性分数(FQ)。其次,我们评估这些特定结局的事后效力和偏倚风险,以及在脆弱性测量方面充分和不充分的研究之间是否存在差异。
对指南中引用的所有参考文献进行筛选,以确定是否符合纳入标准。然后计算所有纳入试验的 FI 和 FQ。使用 Cochrane '风险偏倚'工具 2.0 评估纳入试验中偏倚的可能性和来源。
纳入了 42 项随机对照试验进行评估。中位数 FI 为 10,脆弱性分数(FQ)为 0.0055。有 7 项试验存在高偏倚风险,均归因于随机化过程中的偏倚。有 15 项试验发现功率不足。充分的研究与不足的研究相比,FI 和 FQ 更高。
我们的研究结果支持在未来的随机对照试验方法学中使用 FI 和 FQ 分析与效能分析。通过理解和报告 FI 和 FQ,可以随时提供研究证据,并迅速消除一些读者对可能存在的研究局限性的担忧。