Morphological Risk Factors for Pediatric Anterior Cruciate Ligament Tears and Tibial Spine Fractures
Bibliographic record
Abstract
Background: Both tibial spine fractures (TSFs) and anterior cruciate ligament (ACL) tears result in functional loss of knee stability. Nonetheless, it remains unclear why some patients sustain ACL tears, whereas others have TSFs. Purpose: To identify the common morphological risk factors for pediatric ACL tears and TSFs and to determine the morphological differences between them using multiplanar reconstruction of magnetic resonance imaging (MRI). Study Design: Cohort study; Level of evidence, 3. Methods: Age- and sex-matched participants (159 total [53 ACL tears, 53 TSFs, and 53 controls]) aged <18 years who visited a pediatric tertiary-care center for ACL tears, TSFs, or anterior knee pain from March 2009 to April 2023 were included. Each group comprised 41 male and 12 female participants. Data on demographic characteristics and estimated bone age based on the knee MRI atlas were retrospectively collected, and various knee morphological parameters were evaluated using multiplanar reconstruction of MRI. Parameters showing significant differences among the 3 groups were selected as independent variables for multivariable multinomial logistic regression analysis, with the groups as dependent variables. Results: The mean chronological age at the time of MRI was 13.2 ± 2.3 years. Height, weight, body mass index, bone age, articular medial tibial slope, and bony medial tibial slope did not differ among the groups. Articular lateral tibial slope was independently associated with the occurrence of both ACL tears (relative risk ratio [RRR], 1.42 [95% confidence interval (CI), 1.16-1.74]; P = .001) and TSFs (RRR, 1.33 [95% CI, 1.10-1.62]; P = .004). A high notch width index was a protective factor against ACL tears (RRR, 0.86 [95% CI, 0.77-0.96]; P = .006) but not against TSFs (RRR, 1.01 [95% CI, 0.91-1.12]; P = .848). Conclusion: A high articular lateral tibial slope was a common risk factor for ACL tears and TSFs. Patients with ACL tears had a narrower intercondylar notch than those with TSFs and controls.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".