Revision Anterior Cruciate Ligament Reconstruction in Military Personnel
Bibliographic record
Abstract
This study aims to report the clinical and functional outcomes of revision anterior cruciate ligament (ACL) reconstruction in a young, active duty military population. Patients undergoing revision ACL reconstruction were enrolled in an institutional clinical database and followed prospectively. The primary outcomes were patients' scores on a timed run, as compared with recorded scores before reinjury. Secondary outcomes included scores on the Knee Injury and Osteoarthritis Outcome Score (KOOS), the Western Ontario and McMaster Universities Arthritis Index (WOMAC), the International Knee Documentation Committee subjective (IKDC subjective), the Short Form - 36 health survey (SF-36) version 2, the Single Assessment Numeric Evaluation (SANE), and the Tegner activity scale. A total of 13 patients were identified who met the inclusion criteria and had complete follow-up. The mean age at revision ACL reconstruction was 20.5 years (range, 19-22 years), and mean follow-up was 40.2 months (range, 13-66 months). All patients underwent a single stage revision ACL reconstruction with ipsilateral bone-patellar tendon-bone autograft, ipsilateral hamstring autograft, or bone-tendon-bone allograft. Mean physical readiness test (PRT) score at final follow-up was not statistically different than documented preinjury PRT score (77.9 vs. 85.5, p > 0.05), nor was the mean run time (7:12 vs. 6:43/mile, p > 0.05). Significant improvements exceeding published minimal clinically important differences were seen in SANE score, SF-36 physical component summary score, KOOS sports and recreation, KOOS quality of life, WOMAC pain score, and WOMAC function score. Patients undergoing revision ACL reconstruction at our facility show good recovery of baseline physical performance as measured by the semiannual PRT and timed run test, and significant improvements in patient-reported outcome scores. Level of Evidence Level IV, case series.
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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".