Remifentanil for tracheal intubation without neuromuscular blocking drugs in adult patients: a systematic review and meta‐analysis
Bibliographic record
Abstract
Summary There is increasing interest in the use of short‐acting opioids such as remifentanil to facilitate tracheal intubation. The aim of this systematic review was to determine the efficacy and safety of remifentanil for tracheal intubation compared with neuromuscular blocking drugs in adult patients. We conducted a systematic search for randomised controlled trials evaluating remifentanil for tracheal intubation. Primary outcomes included tracheal intubation conditions and adverse events. Twenty‐one studies evaluating 1945 participants were included in the analysis. Use of remifentanil (1.5–4.0 μg.kg ‐1 ) showed no evidence of a difference in tracheal intubation success rate compared with neuromuscular blocking drugs (risk ratio (95%CI) 0.97 (0.94–1.01); six studies; 1232 participants; I 2 28%; p = 0.16; moderate‐certainty evidence). Compared with neuromuscular blocking drugs, the use of remifentanil (2.0–4.0 μg.kg ‐1 ) makes little to no difference in terms of producing excellent tracheal intubation conditions (risk ratio (95%CI) 1.16 (0.72–1.87); two studies; 121 participants; I 2 31%, p = 0.54; moderate‐certainty of evidence). There was no evidence of an effect between remifentanil (2.0–4.0 μg.kg ‐1 ) and neuromuscular blocking drugs for bradycardia (risk ratio (95%CI) 0.44 (0.01–13.90); two studies; 997 participants; I 2 81%; p = 0.64) and hypotension (risk ratio (95%CI) 1.05 (0.44–2.49); three studies; 1071 participants; I 2 92%; p = 0.92). However, the evidence for these two outcomes was judged to be of very low‐certainty. We conclude that remifentanil may be used as an alternative drug for tracheal intubation in cases where neuromuscular blocking drugs are best avoided, but more studies are required to evaluate the haemodynamic adverse events of remifentanil at different doses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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".