Femoral tunnel length does not impact outcomes following ACL reconstruction using a single‐bundle quadriceps tendon autograft: A systematic review
Bibliographic record
Abstract
PURPOSE: To determine whether femoral tunnel length (FTL) affects clinical or functional outcomes following primary Anterior cruciate ligament reconstruction (ACLR) with single-bundle quadriceps tendon autograft, both with and without a patellar bone block. METHODS: An electronic search of MEDLINE, EMBASE, and Cochrane databases was carried out via OVID. Data pertaining to study characteristics, patient demographics, surgical techniques, femoral tunnel length, and subjective/objective clinical outcomes was abstracted. Studies were stratified into two groups based on FTL; a short femoral tunnel (S-FT) group of ≤25 mm, and a long femoral tunnel (L-FT) group of >25 mm. There was a high degree of heterogeneity between studies, prohibiting meta-analysis. RESULTS: Seven studies comprising 368 total patients with a mean age of 30.3 years (range: 23.4-34 years) were included for analysis. The S-FT group included 126 patients and the L-FT group 242 patients. Both groups demonstrated statistically significant postoperative improvements across both subjective and objective clinical and functional outcomes. Average complication rates were 11.9% (range: 0%-29%) in the S-FT group and 4.5% (range: 1%-14%) in the L-FT group. Ranges of re-rupture rates were 0%-2% and 0%-3% for the S-FT and L-FT groups, respectively (n.s.). CONCLUSION: Both S-FT and L-FT groups demonstrated comparable postoperative outcomes following primary ACLR with single bundle quadriceps tendon autograft. There were slightly superior, although non-significant, outcomes reported with short femoral tunnel length, however, this may have been confounded by the variation in surgical technique used. 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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".