No difference in patient reported outcomes, laxity, and failure rate after revision ACL reconstruction with quadriceps tendon compared to hamstring tendon graft: a systematic review and meta‐analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to synthesize and quantitatively assess the outcomes of ACL Revision using a quadriceps tendon (QT) graft and to compare them with those of ACL Revisions performed with hamstring tendons (HT) graft. METHODS: A comprehensive search based on the PRISMA protocol was performed across PubMed, Scopus, Embase, and Cochrane Library from inception until February 2022. Clinical studies reporting the outcomes of ACL Revision with QT autograft were included. Subjective and Objective IKDC, Tegner activity level, Lysholm knee score, KOOS score, VAS for pain, knee laxity (KT-1000/2000 arthrometer, Lachman test, and pivot-shift test), and graft failure were assessed. A systematic review and meta-analysis were performed and a quality assessment of the included studies was carried out with the MINORS score. RESULTS: Seven studies met the selection criteria and were included in the systematic review for the qualitative synthesis of data. A pooled mean of all the variables was provided for the 7 studies, while 3 studies included a control group of ACL Revision with HT and were included in a meta-analysis. A total of 420 participants with a mean age of 28.9 ± 10.5 years and a mean postoperative follow-up of 39.3 ± 16.4 months were assessed. Of these, 277 patients underwent ACL Revision with QT and 143 patients underwent ACL Revision with HT. In the QT group, average graft failure was 9.8% compared to 17.4% in the HT group. KOOS Sport and pivot-shift test showed better postoperative outcomes in QT than HT, although it was not statistically significant (p = 0.052). CONCLUSION: The QT autograft was associated with an improved trend of rotatory laxity, PROMs and failure rate compared to HT autograft after revision ACL reconstruction. The QT autograft for revision ACL reconstruction is supported by the current literature. It is a viable graft that should be considered for both primary and revision ACL reconstruction. LEVEL OF EVIDENCE: Level IV.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".