Preoperative oral methadone for postoperative pain in patients undergoing cardiac surgery: A randomized double-blind placebo-controlled pilot
Bibliographic record
Abstract
Background Inadequately controlled sternotomy pain after cardiac surgery can lead to delayed recovery and patient suffering. Preoperative intravenous methadone is effective for reducing both postoperative pain and opioid consumption. Despite ease of administration, the effects of preoperative oral methadone are not well described in the literature.Aims This pilot study investigated the effect of preoperative oral methadone on pain scores, analgesia requirements, and opioid-induced side effects.Methods A randomized double-blind placebo-controlled model was used with sampling of patients undergoing sternotomy for isolated coronary artery bypass graft (CABG) surgery (ClinicalTrials.gov registration no. NCT02774499). Participants were randomized to receive oral methadone (0.3 mg/kg) or oral placebo prior to entering the operating room. The primary outcome was pain scores on a 0–10 Verbal Rating Scale. Secondary outcomes included morphine requirements using patient-controlled analgesia (PCA), time to extubation, level of sedation, and side effects such as nausea, vomiting, pruritus, hypoventilation, and hypoxia over a 72-h monitoring time.Results Twenty-one patients completed the study. Oral methadone did not reduce pain scores in the methadone group (P = 0.08). However, postoperative morphine requirement during the first 24 h was reduced by a mean of 23 mg in the methadone group (mean difference, −23; 99% confidence interval [CI], 37–13 mg; P < 0.005). No reduction in pain scores or PCA morphine was observed beyond 24 h postoperatively. There was no difference in incidence of opioid-related side effects between groups throughout the postoperative period.Conclusions Though preoperative oral methadone did not reduce pain scores, morphine requirements were reduced in the first 24 h post-CABG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".