Adverse events following robotic surgery: population-based analysis
Bibliographic record
Abstract
BACKGROUND: Robotic surgery was integrated into some healthcare systems despite there being few well designed, real-world studies on safety or benefit. This study compared the safety of robotic with laparoscopic, thoracoscopic, and open approaches in common robotic procedures. METHODS: This was a population-based, retrospective study of all adults who underwent prostatectomy, hysterectomy, pulmonary lobectomy, or partial nephrectomy in Ontario, Canada, between 2008 and 2018. The primary outcome was 90-day total adverse events using propensity score overlap weights, and secondary outcomes were minor or major morbidity/adverse events. RESULTS: Data on 24 741 prostatectomy, 75 473 hysterectomy, 18 252 pulmonary lobectomy, and 6608 partial nephrectomy operations were included. Relative risks for total adverse events in robotic compared with open surgery were 0.80 (95 per cent c.i. 0.74 to 0.87) for radical prostatectomy, 0.44 (0.37 to 0.52) for hysterectomy, 0.53 (0.44 to 0.65) for pulmonary lobectomy, and 0.72 (0.54 to 0.97) for partial nephrectomy. Relative risks for total adverse events in robotic surgery compared with a laparoscopic/thoracoscopic approach were 0.94 (0.77 to 1.15), 1.00 (0.82 to 1.23), 1.01 (0.84 to 1.21), and 1.23 (0.82 to 1.84) respectively. CONCLUSION: The robotic approach is associated with fewer adverse events than an open approach but similar to a laparoscopic/thoracoscopic approach. The benefit of the robotic approach is related to the minimally-invasive approach rather than the platform itself.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".