Bankart versus Latarjet operation as a revision procedure after a failed arthroscopic Bankart repair
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background An arthroscopic Bankart operation is the most common operative procedure to treat shoulder instability. In case of recurrence, both Bankart and Latarjet procedures are used as revision procedures. The purpose of this study was to compare the re-recurrence rate of instability and clinical results after arthroscopic revision Bankart and open revision Latarjet procedures following failed primary arthroscopic Bankart operations. Methods Consecutive patients operatively treated for shoulder instability at Turku University Hospital between 2002 and 2013 were analyzed. Patients who underwent a primary arthroscopic Bankart operation followed by a recurrence of instability and underwent a subsequent arthroscopic Bankart or open Latarjet revision operation with a minimum of 1 year of follow-up were called in for a follow-up evaluation. The re-recurrence of instability, Subjective Shoulder Value, and Western Ontario Shoulder Instability index were assessed. Results Of 69 patients, 48 (dropout rate, 30%) were available for follow-up. Recurrent instability symptoms occurred in 13 patients (43%) after the revision Bankart procedure and none after the revision Latarjet procedure. A statistically and clinically significant difference in the Western Ontario Shoulder Instability index was found between the patients after the revision Bankart and revision Latarjet operations (68% and 88%, respectively; P = .0166). Conclusions The redislocation rate after an arthroscopic revision Bankart operation is high. Furthermore, patient-reported outcomes remain poor after a revision Bankart procedure compared with a revision Latarjet operation. We propose that in cases of recurring instability after a failed primary Bankart operation, an open Latarjet revision should be considered.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.005 | 0.001 |
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 it