Live surgery increases operative time but not complication rate in patients undergoing arthroscopic anatomic glenoid reconstruction
Bibliographic record
Abstract
OBJECTIVES: Live broadcast surgery is an innovative method of remotely introducing new operative techniques to surgeons globally. However, due to the potential impact on patient outcomes, its use remains somewhat controversial. The objective of this study was to determine the effect of live surgery on operative time and perioperative complication rate in patients undergoing arthroscopic anatomic glenoid reconstruction (AAGR) for shoulder instability. We hypothesized that live surgery would maintain a similar surgical time and intraoperative and postoperative complication profile. METHODS: This was a retrospective review of 94 patients who underwent AAGR between 2013 and 2023. A 1:1 ratio was used to match patients who underwent live virtual AAGR (live broadcast group) to patients who underwent AAGR without live surgery (no broadcast group), based on sex, body mass index, and age. The primary outcome for the study was surgical time, defined as the time from initial incision to final closure. Second, we compared the intraoperative and perioperative complications between the groups. RESULTS: The live broadcast group had a statistically significantly longer procedure time compared with the no broadcast group (86.90 ± 13.1 vs. 80.70 ± 14.0 min, p = 0.04). Neither group experienced intraoperative complications nor were perioperative complications statistically significantly different between the groups (p = 0.62). One patient (2.4 %) in the live broadcast group developed a postoperative hematoma, while one patient (2.4 %) in the no broadcast group developed a wound infection. CONCLUSIONS: This study demonstrated that live surgeries are on average 6 min longer than surgeries that are not broadcast live but are not associated with increased complications in patients undergoing AAGR. Surgeons globally could benefit from this teaching platform without increased risk to the patient. LEVEL OF EVIDENCE: Level III (observational).
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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 | 0.005 |
| 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) | 0.002 | 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".