Redefining “Critical” Bone Loss in Shoulder Instability
Bibliographic record
Abstract
BACKGROUND: Glenoid bone loss is a common finding in association with anterior shoulder instability. This loss has been identified as a predictor of failure after operative stabilization procedures. Historically, 20% to 25% has been accepted as the "critical" cutoff where glenoid bone loss should be addressed in a primary procedure. Few data are available, however, on lesser, "subcritical" amounts of bone loss (below the 20%-25% range) on functional outcomes and failure rates after primary arthroscopic stabilization for shoulder instability. PURPOSE: To evaluate the effect of glenoid bone loss, especially in subcritical bone loss (below the 20%-25% range), on outcomes assessments and redislocation rates after an isolated arthroscopic Bankart repair for anterior shoulder instability. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Subjects were 72 consecutive anterior instability patients (73 shoulders) who underwent isolated anterior arthroscopic labral repair at a single military institution by 1 of 3 sports medicine fellowship-trained orthopaedic surgeons. Data were collected on demographics, the Western Ontario Shoulder Instability (WOSI) score, Single Assessment Numeric Evaluation (SANE) score, and failure rates. Failure was defined as recurrent dislocation. Glenoid bone loss was calculated via a standardized technique on preoperative imaging. The average bone loss across the group was calculated, and patients were divided into quartiles based on the percentage of glenoid bone loss. Outcomes were analyzed for the entire cohort, between the quartiles, and within each quartile. Outcomes were then further stratified between those sustaining a recurrence versus those who remained stable. RESULTS: The mean age at surgery was 26.3 years (range, 20-42 years), and the mean follow-up was 48.3 months (range, 23-58 months). The cohort was divided into quartiles based on bone loss. Quartile 1 (n = 18) had a mean bone loss of 2.8% (range, 0%-7.1%), quartile 2 (n = 19) had 10.4% (range, 7.3%-13.5%), quartile 3 (n = 18) had 16.1% (range, 13.5%-19.8%), and quartile 4 (n = 18) had 24.5% (range, 20.0%-35.5%). The overall mean WOSI score was 756.8 (range, 0-2097). The mean WOSI score correlated with SANE scores and worsened as bone loss increased in each quartile. There were significant differences (P < .05) between quartile 1 (mean WOSI/SANE, 383.3/62.1) and quartile 2 (mean, 594.0/65.2), between quartile 2 and quartile 3 (mean, 839.5/52.0), and between quartile 3 and quartile 4 (mean, 1187.6/46.1). Additionally, between quartiles 2 and 3 (bone loss, 13.5%), the WOSI score increased to rates consistent with a poor clinical outcome. There was an overall failure rate of 12.3%. The percentage of glenoid bone loss was significantly higher among those repairs that failed versus those that remained stable (24.7% vs 12.8%, P < .01). There was no significant difference in failure rate between quartiles 1, 2, and 3, but there was a significant increase in failure (P < .05) between quartiles 1, 2, and 3 (7.3%) when compared with quartile 4 (27.8%). Notably, even when only those patients who did not sustain a recurrent dislocation were compared, bone loss was predictive of outcome as assessed by the WOSI score, with each quartile's increasing bone loss predictive of a worse functional outcome. CONCLUSION: While critical bone loss has yet to be defined for arthroscopic Bankart reconstruction, our data indicate that "critical" bone loss should be lower than the 20% to 25% threshold often cited. In our population with a high level of mandatory activity, bone loss above 13.5% led to a clinically significant decrease in WOSI scores consistent with an unacceptable outcome, even in patients who did not sustain a recurrence of their instability.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".