How statistically fragile are randomized controlled trials comparing quadriceps tendon autografts with hamstring or bone‐patellar tendon‐bone autografts in anterior cruciate ligament reconstruction?
Bibliographic record
Abstract
PURPOSE: To determine the statistical fragility of randomized controlled trials (RCTs) which compare the use of quadriceps tendon (QT) autografts to either hamstring tendon (HT) or bone-patellar tendon-bone (BPTB) autografts in anterior cruciate ligament reconstruction (ACLR). METHODS: A search was conducted across PubMed, MEDLINE and EMBASE databases for RCTs comparing QT autografts to HT or BPTB autografts in ACLR from inception to 21 April 2024. Studies that reported ≥1 statistically significant continuous outcome, statistically significant dichotomous outcome and/or nonsignificant dichotomous outcome were included for analysis. The fragility index (FI), continuous fragility index (CFI) and reverse fragility index (RFI) were calculated for significant dichotomous outcomes, significant continuous outcomes and nonsignificant dichotomous outcomes, respectively. RESULTS: A total of 11 RCTs comprising 716 patients were included. The mean sample size was 65.8 patients. The median FI among nine outcomes from four studies was 1.0 (interquartile range [IQR], 0.5; 95% confidence interval [CI], 0.6-1.4; range 0.5-1.5). The number of patients lost to follow-up at the final follow-up period was more than the study-specific FI in three (75%) studies. The median CFI among 30 outcomes from six studies was 4.9 (IQR, 10.1, 95% CI, 3.9-8.2; range 0-18.2). The number of patients lost to follow-up at the final follow-up period was more than the study-specific CFI in four (66.7%) studies. The median RFI among 10 outcomes from five studies was 5.0 (IQR, 3.5; 95% CI, 3.4-6.6; range 1.0-9.0). The number of patients lost to follow-up at the final follow-up period was more than the study-specific RFI in four (80%) studies. CONCLUSION: This systematic review revealed that regardless of the metric used, RCTs comparing QT autografts to HT or BPTB autograft options in ACLR are statistically fragile. While the indices of statistical fragility evaluated in this study are important metrics of robustness to consider, their application in research and clinical practice needs to be further elucidated. LEVEL OF EVIDENCE: Level I.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.263 | 0.623 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".