Anterior Cruciate Ligament Reconstruction Using Hamstring Autograft Plus Lateral Extra‐articular Tenodesis and All‐Soft Tissue Quadriceps Alone Have Lower Retear Rate and Pivot‐Shift Grade but Similar Outcome to Hamstring Autograft Alone in High‐Risk Patients
Bibliographic record
Abstract
PURPOSE: To compare the surgical outcomes of anterior cruciate ligament (ACL) reconstruction using hamstring autograft (HA) plus lateral extra-articular tenodesis (LET), isolated all-soft tissue quadriceps autograft (QA), and isolated HA. METHODS: A retrospective review was performed comparing high-risk patients undergoing ACL reconstruction with isolated HA, isolated QA, or HA + LET from August 2013 to January 2023. High-risk patients, as determined by high-grade pivot shift or generalized ligament laxity, with at least a 2-year follow-up, were included. Lysholm and International Knee Documentation Committee scores were compared at 3, 6, 12, and 24 months postoperatively. Retear rate, postoperative pivot-shift grade, return to sport, and complications were recorded. RESULTS: In total, 159 patients (56 HA, 47 HA + LET, and 56 QA) were included. At 6 months postoperatively, the HA International Knee Documentation Committee score was significantly lower than that of the HA + LET and QA groups (P < .0001). Similarly, the Lysholm score was significantly lower in the HA cohort at 6 months, 1 year, and 2 years postoperatively (P < .0001-.02). There was no difference in the rate of achieving the minimally important clinical difference between the cohorts for either of these outcome scores. The retear rate was significantly higher in the HA group (17.9%) compared to the HA + LET (4.3%) and QA (1.8%) cohorts (P = .01). The rate of postoperative pivot shift of grade 2 or more was also higher in the isolated HA group (P = .04). CONCLUSIONS: The use of an all-soft tissue QA or HA + LET for ACL reconstruction resulted in a lower retear rate and postoperative pivot-shift grade compared to an isolated HA graft in high-risk patients at 2 years postoperatively. There was no difference in the rate of achieving the minimal clinically important difference between the cohorts. The QA and HA + LET reconstruction options may improve stability and decrease the failure rate compared with HA reconstruction alone. LEVEL OF EVIDENCE: Level III, retrospective cohort study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".