Magnetic resonance imaging arthrography following type II superior labrum from anterior to posterior repair: interobserver and intraobserver reliability
Bibliographic record
Abstract
BACKGROUND: Arthroscopic repair of type II superior labrum from anterior to posterior (SLAP) lesions is a common surgical procedure. However, anatomic healing following repair has rarely been investigated. The intraobserver and interobserver reliability of magnetic resonance imaging arthrography (MRA) following type II SLAP repair has not previously been investigated. This is of particular interest due to recent reports of poor clinical results following type II SLAP lesion repair. PURPOSE: To evaluate the MRA findings following arthroscopic type II SLAP lesion repair and determine its intraobserver and interobserver reliability. STUDY DESIGN: Cohort study (diagnosis), Level of Evidence, 2. METHODS: Twenty-five patients with an isolated type II SLAP lesion (confirmed via diagnostic arthroscopy) underwent standard suture anchor-based repair. At a mean of 25.2 months post-operatively, patients underwent a standardized MRA protocol to investigate the integrity of the repair. MRAs were independently reviewed by two radiologists and a fellowship trained shoulder surgeon. The outcomes were classified as healed SLAP repair or re-torn SLAP repair. RESULTS: On average, 54% of MRAs were interpreted as healed SLAP repairs while 46% of MRAs were interpreted as having a re-torn SLAP repair. Overall, only 43% of the studies had 100% agreement across all interpretations. The intraobserver reliability ranged from 0.71 to 0.81 while the interobserver reliability between readers ranged from 0.13 to 0.44 (Table 1). CONCLUSION: The intraobserver agreement of MRA in the evaluation of type II SLAP repair was substantial to excellent. However, the interobserver agreement of MRA was poor to fair. As a result, the routine use of MRA in the evaluation of type II SLAP lesion repair should be utilized with caution. A global evaluation of the patient, including detailed history and physical examination, is paramount in determining the cause of failure and one should not rely on MRA alone.
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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 | 0.047 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".