Initial experience with ketamine-based analgesia in patients undergoing robotic radical cystectomy and diversion
Bibliographic record
Abstract
INTRODUCTION: We instituted a ketamine-predominant analgesic regimen in the peri- and postoperative periods to limit the effects of narcotic analgesia on bowel function in patients undergoing radical cystectomy. The primary end points of interest were time to return of bowel function, time to discharge, and efficacy of the analgesic regimen. METHODS: We performed a retrospective chart review of patients undergoing robotic-assisted laparoscopic cystectomy (RARC) with urinary diversion by a single surgeon at our institution from January 1, 2011 to June 30, 2012. Patients receiving the opioid-minimizing ketamine protocol were compared to a cohort of patients undergoing RARC with an opioid-predominant analgesic regimen. RESULTS: In total, 15 patients (Group A) were included in the ketamine-predominant regimen and 25 patients (Group B) in the opioid-predominant control group. Three patients (19%) in Group A discontinued the protocol due to ketamine side effects. The mean time to bowel movement and length of stay in Group A versus Group B was 3 versus 6 days (p < 0.001), and 4 versus 8 days, respectively (p < 0.001). Group A patients received an average of 13.0 mg of morphine versus 97.5 mg in Group B (p < 0.001). CONCLUSIONS: Patients who received our ketamine pain control regimen had a shorter time to return of bowel function and length of hospitalization after RARC. Our study has its limitations as a retrospective, single surgeon, single institution study and the non-randomization of patients. Notwithstanding these limitations, this study was not designed to show inferiority of one approach, but instead to show that our protocol is safe and efficacious, warranting further study in a prospective fashion.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".