Longitudinal Effects of Acute Anterior Cruciate Ligament Tears on Peri‐Articular Bone in Human Knees Within the First Year of Injury
Bibliographic record
Abstract
Anterior cruciate ligament (ACL) tears are common sports-related knee injuries that increase the risk of developing post-traumatic osteoarthritis. ACL tears are rarely an isolated injury but are often associated with traumatic bone marrow lesions (BMLs). While early loss of bone mass following the ACL injury has been previously described, to date, microarchitectural information has not been reported due to the limited resolution of clinical imaging systems. In this study, we provide the first evidence of detailed bone mass and microarchitectural changes in the first 10 months following an acute ACL tear, and localized to traumatic BMLs. Fifteen participants with an acute unilateral ACL tear were assessed at four-time points using dual-energy X-ray absorptiometry and high-resolution peripheral quantitative computed tomography, and traumatic BMLs were identified with magnetic resonance imaging. Loss of bone mass was localized to the injured knee (-4.6% to -15.8%, depending on bone and depth) and was accelerated immediately following the injury before suggesting a recovery phase. This loss of bone was accelerated even greater in traumatic BMLs (-18.2% to -20.6%, depending on bone). Bone loss was accompanied by microstructural degeneration of trabecular bone. For example, in the lateral femur of the injured knee, the subchondral bone plate decreased in thickness (-9.0%). This study confirmed loss of bone mass in the months following ACL tears and described the underlying bone microstructural changes. The presented bone changes were accelerated in regions of traumatic BMLs. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:2325-2336, 2019.
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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 | 0.003 | 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 | 0.001 |
| 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".