The Effectiveness of a Criteria-Led Discharge Initiative on the Length of Stay of Patients Who Underwent a Robotic-Assisted Laparoscopic Prostatectomy
Bibliographic record
Abstract
ObjectivesTo determine the impact of a criteria-led discharge initiative (CLD) on the hospital length of stay of patients undergoing a robotic-assisted laparoscopic prostatectomy (RALP).MethodsThis is a cohort study of prospectively collected data completed at a major tertiary hospital from December 2017 to August 2020. The CLD initiative consists of 4 criteria: clinical haemodynamic stability (heart rate < 100 beats/minute, systolic blood pressure > 100mmHg), a drain output of less than 50 mL, flatulence or bowel movement, and the ability to tolerate an oral diet. The primary outcome was hospital length of stay for patients before and after the introduction of CLD.ResultsOne hundred men undergoing RALP before the implementation of the CLD initiative were compared to 118 men undergoing RALP following the implementation of CLD. The patients had similar baseline demographic features. There was a significant difference found in hospital LOS with the pre-CLD group LOS (mean = 1.8 days, SE = 0.12) being longer than the LOS in the post-CLD group (mean = 1.4 days, SE = 0.09, P = 0.015). There were no significant between-group differences in the proportion of patients discharged on the first postoperative day and the 30-day readmission rate.ConclusionWithin our study population, we have demonstrated that the introduction of CLD was associated with reduced hospital LOS with no increase in adverse events. These findings support the need for the development of CLD in other conditions.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".