Hamstring tendon autograft better than bone patellartendon bone autograft in ACL reconstruction A cumulative meta-analysis and clinically relevant sensitivity analysis applied to a previously published analysis
Bibliographic record
Abstract
BACKGROUND: Current debate on treatment options for anterior cruciate ligament (ACL) reconstruction complicate the choice between hamstring and bone-patellar tendon-bone autografts. We hypothesized a priori that cumulative meta-analysis (a form of sensitivity analysis) might show that the evidence for reduction of morbidity by hamstring grafts could have been reached at an earlier time. Furthermore, we hypothesized a priori that modern state-of-the-art hamstring graft fixation technique would give similar results regarding stability as bone-patellar tendon-bone autografts. METHODS: We performed a cumulative meta-analysis and sensitivity analysis based on femoral graft fixation techniques to compare hamstring autograft and bone-patellar tendon-bone autografts in ACL reconstruction derived from a previously published meta-analysis. RESULTS: Cumulatively, that hamstring autograft reduces anterior knee pain had already reached statistical significance in 2001 (relative risk 0.49 (95%CI: 0.32-0.76; p = 0.001, I2 = 0%)). The modern endobutton hamstring graft fixation technique (2 studies) yielded similar stability in the Lachman test as bone-patellar tendon-bone grafts, with a relative risk of 1.1 (95%CI: 0.82-1.5; p = 0.6, I2 = 0%). Exclusion of the endobutton group explains the increased laxity in the hamstring graft group. INTERPRETATION: Cumulative meta-analysis strengthens the evidence for reduced morbidity using hamstring tendon autograft for anterior cruciate ligament reconstruction. Sensitivity analysis focusing on state-of-the-art hamstring graft fixation techniques further weakens the evidence that bone-patellar tendon-bone autografts provide better stability.
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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 | 0.045 | 0.074 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.085 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".