Does Pre-hospital Endotracheal Intubation Improve Survival in Adults with Non-traumatic Out-of-hospital Cardiac Arrest? A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Endotracheal intubation (ETI) is currently considered superior to supraglottic airway devices (SGA) for survival and other outcomes among adults with non-traumatic out-of-hospital cardiac arrest (OHCA). We aimed to determine if the research supports this conclusion by conducting a systematic review. METHODS: We searched the MEDLINE, Scopus and CINAHL databases for studies published between January 1, 1980, and 30 April 30, 2013, which compared pre-hospital use of ETI with SGA for outcomes of return of spontaneous circulation (ROSC); survival to hospital admission; survival to hospital discharge; and favorable neurological or functional status. We selected studies using pre-specified criteria. Included studies were independently screened for quality using the Newcastle-Ottawa scale. We did not pool results because of study variability. Study outcomes were extracted and results presented as summed odds ratios with 95% CI. RESULTS: We identified five eligible studies: one quasi-randomized controlled trial and four cohort studies, involving 303,348 patients in total. Only three of the five studies reported a higher proportion of ROSC with ETI versus SGA with no difference reported in the remaining two. None found significant differences between ETI and SGA for survival to hospital admission or discharge. One study reported better functional status at discharge for ETI versus SGA. Two studies reported no significant difference for favorable neurological status between ETI and SGA. CONCLUSION: Current evidence does not conclusively support the superiority of ETI over SGA for multiple outcomes among adults with OHCA.
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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 | 0.010 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".