Ligamentous Posttraumatic Ankle Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Ankle sprains are the most common injuries in sports and recreational activities. HYPOTHESIS: Ankle osteoarthritis can be caused by ankle ligament lesions. Latency time between injury and osteoarthritis is influenced by the type and side of the injured ligaments. The side of the ligamentous lesion correlates with the hindfoot alignment. STUDY DESIGN: Case series; Level of evidence, 4. METHODS: Of a cohort of 247 patients with ankle arthritis, we reviewed data from 30 patients (33 ankles; mean age, 58.6 years) with ligamentous end-stage ankle osteoarthritis. The patients were evaluated etiologically, clinically, and radiologically. RESULTS: Etiologic analysis: 55% had a ligamentous lesion from sports injuries (soccer, 33%); 85% injured the lateral ankle ligaments, and 15% injured the medial and medial-lateral ligaments. The mean latency time between injury and osteoarthritis was 34.3 years. The survivorship rate for single severe ankle sprains was worse than that for chronic recurrent ligamentous lesions (mean latency time, 25.7 vs 38.0 years; P < .05), and the rate for medial sprains was worse than for lateral sprains (mean latency time, 27.5 vs 35.0 years; P < .05). At follow-up, the American Orthopaedic Foot and Ankle Society hindfoot score was 23.0 points, 52% had varus malalignment, 52% had persistent instability, and the mean ankle arthritis grade was 2.6 points. There was a correlation between chronic lateral ankle instability and varus malalignment. CONCLUSION: Lateral ankle sprains in sports are the main cause of ligamentous posttraumatic ankle osteoarthritis and correlate with varus malalignment. At the time of end-stage ligamentous ankle osteoarthritis, persistent instability may be encountered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".