Disability and Litigation From Urinary Tract Injuries at Benign Gynecologic Surgery in Canada
Bibliographic record
Abstract
OBJECTIVES: To estimate the prevalence of urinary tract injury and the relative risk of litigation from an injury for benign gynecologic surgery in Canada and to analyze a subset of cases of litigation, determining independent risk factors that predicted medical and legal outcomes. METHODS: The prevalence of urinary tract injury and the relative risks of litigation from an injury were determined from the national hospital discharge abstract and the national physician malpractice databases. Multiple logistic regression was performed on a subset of litigation cases. RESULTS: The prevalence of urinary tract injury at benign gynecologic surgery was low (0.33%). If a patient sustained a urinary tract injury, there was a high relative risk of litigation (relative risk 91, 95% confidence interval [CI] 55-158). Patients had a higher chance of major disability after urinary tract injury from hysterectomy for abnormal uterine bleeding (odds ratio [OR] 6.16, 95% CI 1.13-39.01, P = .04), but a lower chance of this being a permanent disability (OR 0.23, 95% CI 0.05-0.96, P = .05). Permanent disability was more likely after an obstructed ureter compared with other types of urinary tract injuries (OR 4.54, 95% CI 1.55-14.88, P = .008). Only 18% of the injuries were recognized intraoperatively. An acute bladder injury was more likely to be recognized intraoperatively than other types of injury (OR 14.98, 95% CI 3.89-57.74, P < .001). No obstructed ureters or urinary tract fistulae were recognized intraoperatively. CONCLUSION: Urinary tract injuries are an uncommon but significant complication from benign gynecologic surgery. Such injuries are associated a high relative risk of litigation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".