A lower Instability Severity Index score threshold may better predict recurrent anterior shoulder instability after arthroscopic Bankart repair: a systematic review
Bibliographic record
Abstract
Importance The Instability Severity Index (ISI) score was developed to evaluate a patient's risk of recurrent shoulder instability following arthroscopic Bankart repair. While patients with an ISI score of >6 were originally recommended to undergo an open procedure (ie, Latarjet) to minimise the risk of recurrence, recent literature has called into question the utility of the ISI score. Objective The purpose of this systematic review was to evaluate the efficacy of the ISI score as a tool to predict postoperative recurrence among patients undergoing arthroscopic Bankart procedures. Evidence review Articles were included if study participants underwent arthroscopic Bankart repair for anterior shoulder instability and reported postoperative recurrence by ISI score at a minimum of 2 years of follow-up. Methodological study quality was assessed using the Methodological Index for Non-Randomized Studies criteria. Pearson's χ 2 test was used to compare recurrence rates among patients above and below an ISI score of 4. Sensitivity, specificity, mean ISI scores and predictive value of individual factors of the ISI score were qualitatively reviewed. Findings Four studies concluded the ISI score was effective in predicting postoperative recurrence following arthroscopic Bankart repair; however, these studies found threshold values lower than the previously proposed score of >6 may be more predictive of recurrent instability. A pooled analysis of these studies found patients with an ISI score <4 to experience significantly lower recurrence rates when compared with patients with a score ≥4 (6.3% vs 26.0 % , p<0.0001). The mean ISI score among patients who experienced recurrent instability was also significantly higher than those who did not. Conclusions and relevance The ISI score as constructed by Balg and Boileau may have clinical utility to help predict recurrent anterior shoulder instability following arthroscopic Bankart repair. However, this review found the threshold values published in their seminal article to be insufficient predictors of recurrent instability. Instead, a lower score threshold may provide as a better predictor of failure. The paucity of level I and II investigations limits the strength of these conclusions, suggesting a need for further large, prospective studies evaluating the predictive ability of the ISI score. Level of evidence 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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".