Functional Outcomes of Arthroscopic Capsular Release of the Elbow
Bibliographic record
Abstract
PURPOSE: Elbow contracture is a common and difficult problem to manage. The purpose of this study was to determine the functional outcomes of arthroscopic capsular release in the management of elbow contractures. METHODS: A total of 22 patients (14 males, 8 females; mean age, 42 years) undergoing arthroscopic contracture release were retrospectively reviewed at a minimum follow-up of 1 year (mean, 25 months). In all, 20 patients had a capsulectomy, and 2 underwent capsulotomy. Patient-rated questionnaires (Disability of the Arm, Shoulder, and Hand questionnaire [DASH], American Shoulder and Elbow Surgeons Elbow Form [ASES-e], and Short Form-36 [SF-36]) and clinical, radiographic, and objective evaluations were used to assess outcomes. Motion and strength were measured by independent evaluators through standard goniometry and the LIDO Isokinetic System (Loredan Biomedical, West Sacramento, CA). RESULTS: Mean flexion significantly improved from 122 degrees +/- 15 degrees to 141 degrees +/- 12 degrees (P < .001). Mean extension significantly improved from 38 degrees +/- 18 degrees to 19 degrees +/- 13 degrees (P < .001). Mean arc improvement was 38 degrees +/- 23 degrees (P < .001). None of the patients had instability, and no major neurovascular complications were reported. All patients had improved elbow function with a mean ASES-e score of 31 out of 36. Most patients were satisfied with their surgery, experienced minimal pain, and exhibited minimal impairment on the DASH. CONCLUSIONS: Arthroscopic debridement and capsulectomy of the contracted elbow is effective. Results are comparable with those of other reports in the literature in which both arthroscopic and open methods were used. LEVEL OF EVIDENCE: Level IV.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".