The effect of methadone and ketamine on quality of recovery in patients undergoing laparoscopic cholecystectomy: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Acute pain following laparoscopic cholecystectomy is most intense in the first 24 h. The use of shorter-acting opioids for pain management may contribute to increased postoperative morbidity. The combination of methadone and ketamine has been associated with lower postoperative pain scores and less opioid use. We aimed to determine whether the combination of ketamine and methadone improves the quality of recovery. METHODS: This prospective cohort study included patients undergoing laparoscopic cholecystectomy. Patients who received either methadone alone or a combination of methadone and ketamine (0.3 mg/kg) were followed up for 24 h after surgery. The primary outcome was the quality of recovery, measured using the quality of recovery-40 (QoR-40) questionnaire. Secondary outcomes included postoperative pain intensity, opioid consumption, and the incidence of nausea and vomiting. RESULTS: The QoR-40 scores were higher in patients who received methadone and ketamine than in those who received methadone alone [197 (194.7-198) versus 195 (189-197), P = 0.01]. Postoperative pain scores, the incidence of postoperative nausea and vomiting, and postoperative opioid use were similar between the groups. The combination of methadone and ketamine was not associated with lower incidence of moderate-to-severe pain in propensity score analysis. CONCLUSIONS: Although the combination of methadone and ketamine showed a slight increase in QoR40 scores at 24 h postoperatively, the observed difference between the groups was not clinically significant. Moreover, the absence of a reduction in postoperative pain intensity and similar perioperative opioid consumption between the groups further support the hypothesis that small, isolated doses of ketamine may not be effective in improving recovery quality compared with methadone alone.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".