Poster 116: When do Patients Return to Sports? Arthroscopic Anatomic Glenoid Reconstruction Versus Bankart Repair
Bibliographic record
Abstract
Objectives: Participation in contact or collision sports is a known risk factor for shoulder instability. Recurrent instability is a barrier to return to same level of athletic activities following surgical intervention. Previous literature has described that approximately 50% to 90% of patients return to sports following stabilization procedures. However, it is currently unknown the rate and timing of return to sports after Arthroscopic Anatomic Glenoid Reconstruction (AAGR). This study aimed to determine the rate of return and the time to return to sports of patients’ who underwent AAGR compared to a Bankart, alone. Methods: This is a subcohort of 100 patients who consented to a randomized controlled trial and were randomized for AAGR or Bankart procedure (1:1 ratio). The subgroup consists of individuals at a minimum 2-year follow up and participate in a sport at either the recreational or competitive level. A descriptive analysis was completed on the percentage of patients that returned to their preinjury sport, as well as when they returned and compared between groups. Descriptive reporting on why patients did not return was included. Results: Age, follow up, sex, and sport level were all statistically similar between the 2 groups. The rate to return was significantly larger for patients in the AAGR group (78%) compared with the Bankart group (60%). For those who did return to sports, time to return was not significantly different between the AAGR group (9.48 ± 4.2 months) and Bankart group (10.2 ± 6.2 months). For those who did not return in the Bankart group, redislocation was the greatest factor (38%). In the AAGR group, prioritizing work and life (30%) and lack of confidence (30%) were the top reasons for not returning. Conclusions: AAGR demonstrated superior rate of return to sports compared to those who underwent a Bankart repair. Patients in the Bankart group did not return due to redislocation events, whereas individuals in AAGR did not return due to a lack of confidence or prioritizing their work and life. These results can aid in setting realistic expectations for patients undergoing AAGR and can help guide discussions around postoperative rehabilitation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".