Comparing the First-Pass Success Rate of the King LTS-D and the i-gel Airway Devices in Out-of-Hospital Cardiac Arrest
Bibliographic record
Abstract
OBJECTIVES: Significant heterogeneity exists internationally in the airway devices used in the pre-hospital setting during cardiac arrest. This study evaluated the first-pass success (FPS) rate of two supraglottic airways (SGAs) used by paramedics during out-of-hospital cardiac arrest: the King LTS-D and the i-gel. METHODS: By examining 2,680 patient care records compiled by Ambulance New Brunswick between 2015 and 2020, we evaluated the FPS rate of the two SGAs using a 2x2 Pearson chi-square test for association, and a Mann-Whitney U test, to determine whether there were significant differences in FPS rates. RESULTS: (1) = 96.01, p < 0.001. The odds of successfully inserting the airway on the first attempt were 2.94 times higher if paramedics used the i-gel than if they used the King LTS-D with a 95% CI [2.32, 3.60]. Mann-Whitney's U test for SGA differences favored the i-gel in fewer attempts for successful insertion (z = -4.357, p < 0.001, d = 0.15). CONCLUSIONS: Among patients in New Brunswick with out-of-hospital cardiac arrest, paramedics had a higher FPS rate with the i-gel compared to the King LTS-D. Our study also found a statistically significant difference between the King LTS-D and i-gel, favoring the i-gel in fewer attempts. Our findings suggest that the i-gel provides a more consistent FPS rate compared to the King LTS-D within our study populations; however, further research is necessary to determine the clinical implications of this. While multiple attempts at tracheal intubation are associated with negative clinical outcomes, no such evidence exists for SGAs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".