Indications for Surgical Management of Osteochondritis Dissecans of the Knee in the Pediatric Population: A Systematic Review
Bibliographic record
Abstract
Several case series have been published exploring the surgical management of osteochondritis dissecans (OCD) of the knee in pediatric patients. This systemic review was performed to identify the surgical indications for this condition. A search of the Embase and Ovid Medline databases was performed to identify clinical studies reporting outcomes of surgical management of OCD in the knee in this patient population. A quality assessment of the included articles was conducted independently by two reviewers using a quality assessment tool developed by Yang et al. A total of 25 articles met the eligibility criteria and were reviewed; 40% of studies did not clearly describe their surgical indications. The remainder of the studies had a failure of nonoperative management with or without the concomitant use of imaging as their indication for surgery, or used lesion stability itself as the indication for surgery. This review outlines several surgical indications presented in the literature for the treatment of OCD lesions of the knee in the pediatric population. The most common indication for surgery was a failure of a trial of nonoperative treatment with or without the concomitant use of serial imaging. Although the quality of the case series was high, inconsistencies in reporting radiographic and arthroscopic classification of the OCD lesion were common.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".