Journal article
The statistical fragility of the distal fibula fracture literature: A systematic review of randomized controlled trials
Injury, v 54(6), pp 1809-1814
01 Jun 2023
PMID: 36964035
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
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Details
- Title
- The statistical fragility of the distal fibula fracture literature: A systematic review of randomized controlled trials
- Creators
- Hassan Mian - University of Minnesota Medical SchoolMichael Megafu - AT Still University Kirksville College of Osteopathic Medicine, United StatesEmmanuel Megafu - City University of New York, York College, United StatesSulabh Singhal - Drexel UniversityNicholas G. Richardson - Mount Sinai Health SystemPaul Tornetta - Boston UniversityRobert L. Parisien - Mount Sinai Health System
- Publication Details
- Injury, v 54(6), pp 1809-1814
- Publisher
- Elsevier
- Number of pages
- 6
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- General Internal Medicine
- Web of Science ID
- WOS:001003370500001
- Scopus ID
- 2-s2.0-85150754881
- Other Identifier
- 991022207068004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Critical Care Medicine
- Emergency Medicine
- Orthopedics
- Surgery