Returning to the emergency room: An analysis of emergency encounters following urologic outpatient surgery
Bibliographic record
Abstract
INTRODUCTION: Previous reports indicate urological surgeries are associated with high rates of hospital re-admission. This study aims to identify factors associated with emergency room (ER) encounters following urological outpatient surgery. METHODS: All outpatient surgeries performed at The Ottawa Hospital between April 1, 2008, and March 31, 2018 by urology, general surgery, gynecology, and thoracic surgery were identified. All ER encounters within 90 days of surgery were captured. Rates of ER encounters by surgical service and procedure type were determined. Patient and surgical factors associated with ER encounters were identified. Factors included age, sex, marital status, presence of primary care provider, procedure, and American Society of Anesthesiologists (ASA) score. RESULTS: A total of 38 377 outpatient surgeries by the included surgical services were performed during the study period, of which urology performed 16 552 (43.1%). Overall, 5641 (14.7%) ER encounters were identified within 90 days of surgery, including 2681 (47.5%) after urological surgery. On multivariable analysis, higher ASA score IV vs. I was associated with higher risk of ER encounter (relative risk [RR] 1.95, 95% confidence interval (CI) 1.46-2.5) and being married was associated with a lower risk of ER encounter (RR 0.85, 95% CI 0.77-0.93). Urological surgeries with the highest risk of ER encounters, compared to the lowest risk procedure (circumcision), were greenlight laser photo vaporization of the prostate (PVP) (RR 3.2, 95% CI 1.8-5.61), ureteroscopy (RR 3.2, 95% CI 1.9-5.4), and ureteric stent insertion (RR 3.1, 95% CI 1.8-5.5). CONCLUSIONS: ER encounters following outpatient surgery are common. This study identifies risk factors to recognize patients that may benefit from additional support to reduce ER care needs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".