Reducing urinary tract infection in female pelvic surgery: A retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To compare prebundle versus postbundle implementation urinary tract infection (UTI) rates among inpatients within 6 weeks of clean-contaminated pelvic reconstructive surgery. METHODS: The authors conducted a retrospective cohort study from September 2019 to December 2021 at a tertiary hospital. The bundle strategy included the following: universal preoperative UTI check with treatment if positive, replacing prolonged postoperative voiding trials on the ward with earlier discharge and indwelling catheter removal by a nurse continence advisor the next day, and daily cranberry extract for 6 weeks postoperatively. UTI was defined as positive urine culture (≥100 000 colony-forming unit per mL) in a symptomatic patient. Data analysis involved hypothesis testing and logistic regression. RESULTS: The authors reviewed 132 postbundle inpatient charts and retained 93 for analyses. The results were compared with 204 prebundle inpatient charts. The rate of postoperative UTI decreased from 17.6% in the prebundle group to 6.5% after bundle implementation (P = 0.01). The adjusted odds ratio for postbundle versus prebundle likelihood of UTI was 0.35 (95% confidence interval, 0.13-0.98; P = 0.045). Significantly more postbundle patients compared with prebundle patients were discharged home on the first day postoperatively (76.3% vs. 37.7%, P < 0.001). CONCLUSIONS: A clinical bundle can significantly decrease both UTI rates and hospital stay after pelvic reconstructive surgery.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".