Network meta-analysis of comparative efficacy and safety of intubation devices in children
Bibliographic record
Abstract
To evaluate the comparative efficacy and safety of different intubation devices on intubation outcomes in pediatric intubation. We identified relevant studies from previous meta-analyses and literature retrieval in PubMed, EMBASE, and Cochrane Library. The primary outcome was the first-pass success (FPS), and the secondary outcome included the time to intubation (TTI) and the risk of local complications (LC). Network meta-analysis was performed using STATA 14.0. Twenty-three randomized comparative trials (RCTs) including 12 devices were included. Compared with Macintosh, Airtraq (odds ratio [OR] = 13.05, 95% confidence interval [CI] = 4.68 to 36.38), Miller (OR = 4.77, 95%CI = 1.32 to 17.22), Glidescope (OR = 2.76, 95%CrI = 1.60 to 4.75) and McGrath (OR = 4.61, 95%CI = 1.18 to 17.99) obtained higher PFS. Meanwhile, Airtraq was superior to Glidescope (OR = 0.21, 95%CI = 0.07 to 0.65) for PFS. For TTI, Canada was superior to other intubation devices, as well as CMAC was superior to TruViewEVO2, Glidescope, and StorzDCI. Airtraq lowered the risk of LC compared with Macintosh and Pentax but there was no statistical difference between Airtraq and KingVision. Airtraq may be the optimal option for FPS, Canada for TTI, and KingVision for LC in pediatric intubation.
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.048 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".