Implementation of a standardized voiding protocol after minimally invasive surgery: A quality improvement initiative
Bibliographic record
Abstract
OBJECTIVES: To assess the effects of the implementation of a standardized voiding protocol in patients undergoing minimally invasive hysterectomy at a single cancer center in terms of the urinary tract infection (UTI) rate, time to first void, and overnight stays secondary to urinary retention. METHODS: We enrolled 102 consecutive patients undergoing minimally invasive hysterectomy at a single cancer center during a 12-month period. A pre-intervention cohort of 100 consecutive patients was identified for comparison. A multidisciplinary team developed and implemented a standardized voiding protocol using quality improvement methodology. We compared the demographics, time to first void, rate of urinary retention, and UTI rates between the pre- and post-intervention cohorts. RESULTS: Our intervention led to a significant reduction in the time to first void (289 min vs. 566 min; P < 0.001), rate of urinary retention (2% vs. 10%; P = 0.015), and postoperative UTI (4% vs. 8%; P = 0.249). There was a similar rate of patients going home with a Foley catheter (9% vs. 11%; P = 0.850). CONCLUSIONS: Implementation of a standardized voiding protocol was associated with a reduction in rate of UTI, time to first void, and overnight stays secondary to urinary retention.
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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 | 0.021 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".