Posteromedial versus Anteromedial Hamstring Tendon Harvest for Anterior Cruciate Ligament Reconstruction: A Retrospective Comparison of Accidental Gracilis Harvests, Outcomes, and Operative Times
Bibliographic record
Abstract
Abstract Hamstring autografts are frequently harvested for anterior cruciate ligament reconstruction (ACLR), traditionally through the anteromedial (AM) approach. Recently, a posteromedial (PM) approach has been described. The primary purpose of this study was to compare rates of unintentional gracilis (Gr) harvest or premature tendon amputation with these approaches. We also sought to compare operative times and patient-reported outcome measures (PROMs) between both groups and between those with only semitendinosus (ST) grafts or with combined ST and Gr grafts. Patients who underwent ACLR with hamstring autograft by a single surgeon from 2014 to 2016 were retrospectively reviewed. An accidental harvest was identified as an unintentional Gr harvest or premature graft amputation. PROMs included the Knee Osteoarthritis and Outcomes Score, Western Ontario and McMaster Universities Osteoarthritis Index, and International Knee Documentation Committee score. Two out of 22 (9.1%) patients in the AM group had unintentional Gr tendon harvests, while none (out of 29) were identified in the PM group (p = 0.101). Group mean PROMs were not significantly different between patients in either group or patients with either ST-only grafts and those with combined ST + Gr. Average operative times and tourniquet times were significantly shorter with the PM approach versus the AM approach (101 ± 18.2 vs 129 ± 25.6 minutes, p = 0.002; 68 ± 14.8 vs 90 ± 28.9 minutes, p = 0.005). The PM approach was associated with a trend toward decreased risk of unintentional harvest of the Gr tendon and significantly decreased operative and tourniquet times without affecting knee outcomes compared with the traditional AM approach. Accidental Gr harvest was not associated with worse outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".