Methadone for critically ill patients under mechanical ventilation in the intensive care unit: a systematic review
Bibliographic record
Abstract
PURPOSE: Pain may pose significant challenges in the intensive care unit, especially in mechanically ventilated patients. Methadone has recently emerged as an alternative option for eliciting acute analgesia. In this systematic review, we evaluated the use of methadone in mechanically ventilated patients in the intensive care unit. SOURCE: We searched MEDLINE, EMBASE, Wiley's Cochrane Library, CINAHL, PubMed (non-MEDLINE), Scopus, and LILACS databases from inception to January 24th, 2025. Eligible studies included randomized controlled trials and observational studies that compared the use of methadone to the standard of care or to other analgosedation strategies in mechanically ventilated patients in the intensive care unit. The primary outcome was the duration of mechanical ventilation. The secondary outcomes included opioid-associated adverse effects and scores regarding pain, agitation, and delirium. PRINCIPAL: findings: The search strategy yielded 3,523 studies. A total of 773 patients were included across the 12 studies (including 7 abstracts and 5 manuscripts). Patient populations included patients with trauma, those with burns, those at high risk for fentanyl abstinence syndrome, those with opioid use disorder, those with opioid withdrawal symptoms, and those who had received fentanyl for 72 hours prior to weaning. Overall, compared with the group that did not receive methadone, the methadone group was associated with more ventilator-free days, shorter weaning times, and a greater probability of successful weaning on day 5. Most of the studies exhibited high risks of bias; moreover, the overall quality of the evidence was low. CONCLUSION: Few studies have evaluated the use of methadone in mechanically ventilated patients. Based on the low-quality evidence, methadone may be associated with improved patient-centered outcomes. Further research is warranted with respect to this topic.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".