Impact of Tibial and Femoral Tunnel Position on Clinical Results After Anterior Cruciate Ligament Reconstruction
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to correlate anatomic and nonanatomic tibial and femoral tunnel positions after anterior cruciate ligament (ACL) reconstruction with clinical outcome by use of bone-patellar tendon-bone (BPTB) single-bundle (SB) and semitendinosus-gracilis (STG) double-bundle (DB) techniques. METHODS: The 3-dimensional computed tomography scans of 53 patients' knees (27 BPTB-SB and 26 STG-DB) were prepared and measured by 2 examiners according to their tibial and femoral tunnel positions. We evaluated these radiologic constructions and measurements by use of the Cohen κ interobserver and intraobserver coefficient for 2 observers. Patients undergoing both techniques were divided into anatomic and nonanatomic reconstructions according to the findings of Zantop and Petersen. We correlated anatomically and nonanatomically reconstructed patients with clinical outcome by the Tegner score, Western Ontario and McMaster Universities Osteoarthritis Index score, International Knee Documentation Committee score, KT-1000 arthrometer (MEDmetric, San Diego, CA), and pivot-shift test in both techniques. RESULTS: The radiologic constructions and measurements of 53 computed tomography scans were achieved with a good agreement of interobserver and intraobserver coefficients for 2 observers. We found significantly superior clinical outcome in anatomic ACL reconstructions in both techniques in terms of higher clinical scores (Tegner and International Knee Documentation Committee), higher anterior posterior stability, and less pivot shift. We observed the best outcome in anatomic STG-DB reconstructions. CONCLUSIONS: This investigation showed that better clinical results are associated with anatomic ACL reconstructions. LEVEL OF EVIDENCE: Level II, prospective comparative 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 | 0.001 | 0.004 |
| 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".