Rotational laxity greater in patients with contralateral anterior cruciate ligament injury than healthy volunteers
Bibliographic record
Abstract
Rotational stability of the knee has been traditionally difficult to quantify, limiting the ability of the orthopedic community to determine the potential role of rotational laxity in the etiology of anterior cruciate ligament (ACL) injuries. The purposes of this multicenter cohort study were to evaluate the reliability of a robotic axial rotation measurement system, determine whether the uninjured knees of patients that had previous contralateral ACL reconstruction demonstrated different rotational biomechanical characteristics than a group of healthy volunteers, and determine whether knee rotational biomechanical characteristics differ between male and female non-injured limbs in groups of both healthy volunteers and patients with a previous contralateral ACL injury. Fourteen healthy volunteers and 79 patients with previous unilateral ACL injury participated in this study. Patients were tested using a computerized tibial axial rotation system. Only the normal (non-operated) knee data were used for analysis. In order to assess the reliability of the robotic measurement system, 10 healthy volunteers were tested daily over four consecutive days by four different examiners. Rotational laxity and compliance measures demonstrated excellent reliability (ICC = 0.97). Patients with a contralateral ACL injury demonstrated significantly increased tibial internal rotation (20.6° vs. 11.4°, P < 0.001) and reduced external rotation (16.7° vs. 26.6°, P < 0.001) compared to healthy volunteers. Females demonstrated significantly increased internal and external rotation, as well as significantly increased rotational compliance compared with males (P < 0.05). Computer-assisted measurement techniques may offer clinicians an accurate, reliable, non-invasive method to select the most appropriate preventative or surgical interventions for patients with increased knee rotational laxity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".