Rocuronium vs. succinylcholine for rapid sequence intubation: a Cochrane systematic review
Bibliographic record
Abstract
Summary This systemic review was performed to determine whether rocuronium creates intubating conditions comparable to those of succinylcholine during rapid sequence intubation of the trachea. We searched the Cochrane Central Register of Controlled Trials ( CENTRAL ; 2015, Issue 2), MEDLINE (1966 to February Week 2 2015), and EMBASE (1988 to February 14 2015) for any randomised controlled trials or controlled clinical trials that reported intubating conditions comparing rocuronium and succinylcholine for rapid or modified rapid sequence intubation. The dose of rocuronium was at least 0.6 mg.kg −1 and succinylcholine was at least 1 mg.kg −1 . Sixty‐six studies were identified and 50 included, representing 4151 participants. Overall, succinylcholine was superior to rocuronium for achieving excellent intubating conditions (risk ratio (95% CI ) 0.86 (0.81 to 0.92), n = 4151) and clinically acceptable intubation conditions (risk ratio (95% CI ) 0.97 (0.95–0.99), n = 3992). A high incidence of detection bias amongst the trials coupled with significant heterogeneity means that the quality of evidence was moderate for these conclusions. Succinylcholine was more likely to produce excellent intubating conditions when using thiopental as the induction agent: risk ratio (95% CI ) 0.81 (0.73–0.88), n = 2302) with or without the use of opioids (risk ratio (95% CI ) 0.85 (0.78–0.93), n = 2292 or 0.85 (0.76–0.95), n = 1428).
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 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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".