INTEROBSERVER RELIABILITY OF A COMPREHENSIVE LATERAL DISCOID MENISCUS CLASSIFICATION SYSTEM: A MULTICENTER ARTHROSCOPIC VIDEO ANALYSIS STUDY
Bibliographic record
Abstract
Introduction/Background: Lateral discoid meniscus (LDM) is the most common congenital anomaly of the knee. Due to the significant heterogeneity in pathomorphology, LDM treatment remains challenging. Treatment approaches and surgical techniques vary widely among surgeons and different types of LDM. Current classification systems inadequately describe the spectrum of pathology or dictate treatment. Hypothesis/Purpose: The Pediatric Research in Sports Medicine (PRISM) meniscal study group developed and tested the reliability of a novel classification system designed to comprehensively capture the intricacies of LDM pathomorphology and guide treatment decisions. Methods: The PRISM LDM Classification System was developed through an initial review of existing classification systems followed by group consensus method by pediatric meniscal surgeons from 20 tertiary academic centers. Four factors were evaluated: (1) meniscal width (surface area), (2) meniscal height (thickness, +/- horizontal delamination), (3) peripheral stability (and instability pattern), and (4) tearing (and tear location)(Table 1). A stepwise arthroscopic exam utilizing two standard anterior viewing portals was established for optimizing diagnosis of LDM features. From a set of 101 arthroscopic videos submitted for review, 41 were selected for quality by 3 of the authors (non-’readers’). Five ‘readers’ then performed assessments using the classification system. Interobserver reliability of the primary and secondary rating factors was assessed using the Fleiss kappa coefficient (K, 95% CI), designed for multiple readers with nominal variables (Reliability Classification: Fair 0.21-0.40 fair, Moderate 0.41-0.60, Substantial 0.61-0.80, and Excellent 0.80-1.00). Results: The majority of the primary and secondary rating factors demonstrated ‘substantial’ reliability, such as meniscal width (complete vs. incomplete, K 0.609; 0.512-0.706) and posterior horn stability (stable vs. unstable, K 0.693; 0.594-0.792), or ‘moderate’ reliability, such as meniscal height (normal vs. abnormal, K 0.444; 0.347-0.541), overall stability, (stable vs. unstable, K 0.569; 0.472-0.666), and tear presence (tear vs. no tear, K 0.541; 0.444-0.638). Several features demonstrated only ‘fair’ agreement, including anterior horn stability (stable vs. unstable, K 0.358; 0.258-0.457), meniscal body stability (stable vs. unstable, K 0.314; 0.214-0.413), and tear type (no tear, radial, vertical, complex, K 0.386; 0.325-0.446). Conclusion/Discussion: A novel classification system that more comprehensively and descriptively characterizes the spectrum of LDM pathology demonstrated moderate or substantial agreement in most diagnostic categories analyzed. Specific features demonstrating fair agreement may warrant investigation of alternative steps in the arthroscopic exam or descriptors to improve agreement. A comprehensive classification system is critical to advance LDM research from single-center, level 4 studies to prospective multicenter efforts that will enhance improve communication, research, and evidence-based treatment of LDM pathology.
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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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".