Mian Hassan, Megafu Michael, Megafu Emmanuel, Singhal Sulabh, Richardson Nicholas G, Tornetta Paul, Parisien Robert L
University of Minnesota Medical School, United States.
AT Still University Kirksville College of Osteopathic Medicine, United States.
Injury. 2023 Mar 20. doi: 10.1016/j.injury.2023.03.022.
The purpose of this study was to apply both the fragility index (FI) and fragility quotient (FQ) to evaluate the degree of statistical fragility in the distal fibular fracture (DFF) literature. We hypothesized that the dichotomous outcomes within the DFF literature are statistically fragile.
We performed a PubMed search for distal fibular fractures clinical trials from 2000 to 2022 reporting dichotomous outcomes. The FI of each outcome was calculated through the reversal of a single outcome event until significance was reversed. The FQ was calculated by dividing each fragility index by study sample size. The interquartile range (IQR) was also calculated for the FI and FQ.
Of the 1158 articles screened, 23 met the search criteria, with six RCTs included for analysis. Forty-five outcome events with 5 significant (p < 0.05) outcomes and 40 nonsignificant (p ≥ 0.05) outcomes were identified. The overall FI and FQ was 5 (IQR 4-6) and 0.089 (IQR 0.061-0.107), respectively.
The randomized controlled trials in the peer-reviewed distal fibular fracture literature may not be as robust as previously thought, as incorporating statistical analyses solely on a P value threshold is misleading. Standardized reporting of the P value, FI and FQ can help the clinician reliably draw conclusions based on the fragility of outcome measures.
本研究旨在应用脆弱性指数（FI）和脆弱性商数（FQ）来评估腓骨远端骨折（DFF）文献中的统计脆弱程度。我们假设DFF文献中的二分法结果在统计上是脆弱的。
我们在PubMed上搜索了2000年至2022年报告二分法结果的腓骨远端骨折临床试验。通过反转单个结果事件直至显著性反转来计算每个结果的FI。FQ通过将每个脆弱性指数除以研究样本量来计算。还计算了FI和FQ的四分位间距（IQR）。
在筛选的1158篇文章中，23篇符合搜索标准，其中包括6项随机对照试验用于分析。确定了45个结果事件，其中5个为显著（p < 0.05）结果，40个为非显著（p≥0.05）结果。总体FI和FQ分别为5（IQR 4 - 6）和0.089（IQR 0.061 - 0.107）。
同行评审的腓骨远端骨折文献中的随机对照试验可能没有之前认为的那么可靠，因为仅基于P值阈值进行统计分析会产生误导。P值、FI和FQ的标准化报告可以帮助临床医生根据结果测量的脆弱性可靠地得出结论。
