Effective analgesia and decreased length of stay for patients undergoing radical prostatectomy: Effectiveness of a clinical pathway.
Bibliographic record
Abstract
OBJECTIVES: To assess the impact of a clinical pathway (CP) on length of stay (LOS), complications, readmission rates, and patient satisfaction for patients undergoing a radical retropubic prostatectomy (RRP). MATERIALS AND METHODS: A standardized CP for all patients undergoing RRP was developed and implemented. Post-operatively, patients enrolled in the CP received oral ibuprofen and acetaminophen analgesia, with oral and subcutaneous narcotics available for breakthrough pain. Patients enrolled in the CP were compared to a pre-CP historical cohort. Patients were asked to complete a short, validated satisfaction questionnaire 10 days post-operatively. RESULTS: Sixty-eight consecutive patients underwent a RRP following CP implementation and were compared to a historical cohort of 147 pre-CP patients. Median LOS decreased by 50% (4 days versus 2 days, p < 0.0001) while complication and readmission rates were unchanged. Patient satisfaction was high in all domains. Overall, 29.4% of patients treated within the CP required no narcotic analgesia during their admission. CONCLUSIONS: The implementation of a CP for patients undergoing a RRP is a simple and effective method for reducing LOS without compromising complication, readmission rates or patient satisfaction.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".