Comparison of Anesthetics for Laryngeal Mask Airway Insertion: A Network Meta-Analysis
Bibliographic record
Abstract
Objective: This study aimed to establish which anesthetic agents are associated with minimized adverse outcomes during laryngeal mask airway (LMA) insertion. Methods: Databases were searched for randomized controlled trials (RCTs) with American Society of Anesthesiologists I or II adult patients (≥15 years of age) receiving general anesthesia (GA) with an LMA. Propofol only was the comparator to other anesthetics used during LMA insertion. The primary outcome was prolonged apnea, and secondary outcomes were adverse airway events, LMA insertion failure, inadequate depth of anesthesia, and hemodynamic events. A network meta-analysis was conducted to estimate the treatment effects (odds ratios, 95% credible intervals, and surface under the cumulative ranking curve [SUCRA]). Results: A total of 28 anesthetic combinations used on 4695 patients for GA induction and LMA insertion were examined across 53 RCTs. Overall, there was an apnea incidence rate of 33.3% (849 of 2548) with a mean time of 3.74 ± 3.56 minutes (n = 3091). Propofol + dexmedetomidine had the highest overall summed score of SUCRA ranks in reducing adverse outcomes (apnea incidence: SUCRA = 37%, apnea time: SUCRA = 66%, airway adverse event: SUCRA = 67%, insertion failure: SUCRA = 73%, inadequate depth of anesthesia: SUCRA = 84%). In comparison among all propofol combinations, propofol alone ranked lowest for overall summed score of SUCRA in reducing adverse outcomes (apnea incidence: SUCRA = 47%, apnea time: SUCRA = 71%, airway adverse event: SUCRA = 9%, insertion failure: SUCRA = 20%, inadequate depth of anesthesia: SUCRA = 9%). Conclusion: All anesthetic combinations, other than those with thiopental, reduced adverse outcomes as compared with propofol alone. The combination of propofol and dexmedetomidine infused over 10 minutes ranked as the most effective for reducing adverse outcomes during LMA insertion.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.047 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".