Intersurgeon variations in postoperative length of stay after video-assisted thoracoscopic surgery lobectomy
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Bibliographic record
Abstract
Objectives: To identify factors associated with prolonged postoperative length of stay (LOS) after VATS lobectomy (VATS-L), explore potential intersurgeon variation in LOS and ascertain whether or not early discharge influences hospital readmission rates. Methods: We conducted a retrospective analysis of patients who underwent VATS-L at a single academic center between 2018 and 2021. Each VATS lobectomy procedure was performed by 1 of 7 experienced thoracic surgeons. The primary end point of interest was prolonged LOS, defined as an index LOS >3 days. Results: < .001), patient age (odds ratio [OR], 1.03; 95% CI, 1.02-1.06), operation time (OR, 1.01; 95% CI, 1.01-1.01), postoperative complication (OR, 3.60; 95% CI, 2.45-5.29), and prolonged air leak (OR, 8.95; 95% CI, 4.17-19.23). There was no significant association between LOS and gender, body mass index, coronary artery disease, prior atrial fibrillation, American Society of Anesthesiologists score >3, and prior ipsilateral thoracic surgery or sternotomy. There was no association between LOS ≤3 days and hospital readmission (20 [5.3%] vs 39 [5.9%]; OR, 0.88; 95% CI, 0.50-1.53). Conclusions: An intersurgeon variation in postoperative LOS after VATS-L exists and is independent of patient baseline characteristics or perioperative complications. This variation seems to be more closely related to differences in postoperative management and discharge practices rather than to surgical quality. Postoperative discharge within 3 days is safe and does not increase hospital readmissions.
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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) | 0.001 | 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 it