[Treatment of anterior shoulder instability with remplissage for Hill-Sachs injuries and Bankart injury compared to pure Bankart injuries].
Bibliographic record
Abstract
BACKGROUND: Anterior shoulder dislocation occurs in more than 90% of the time, the main cause is traumatic, describing two main lesions in this pathology: Bankarts and Hill-Sachss injury, the recurrence rate is not similar in open repair and with a possible advantage of arthroscopic surgery with less loss of movement range, lower risk of subscapular muscle damage, faster return to daily activities and increased patient satisfaction. OBJECTIVE: Assessing functionality, mobility and stability of the shoulder in patients treated: arthroscopic Bankart repair versus arthroscopic Bankart repair + remplissage. METHODS: Clinical records of patients with shoulder instability were reviewed Hill-Sachs and Bankart lesions were doumented; 21 post-surgical patients and were physically examined to evaluate the range of motion, Rowe functional scales and Western Ontario Shoulder Instability Index were used. 13 months of follow up as an average. RESULTS: There was no recurrence of dislocation with either technique, greater satisfaction was observed in the remplissage group; however, the limitation of the motion arc is greater. CONCLUSION: Both groups reduce instability, control pain and mostly satisfy patients in the 13-month follow-up.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".