E<scp>NDOTRACHEAL</scp>I<scp>NTUBATION AND</scp>E<scp>SOPHAGEAL</scp>T<scp>RACHEAL</scp>C<scp>OMBITUBE</scp>I<scp>NSERTION BY</scp>R<scp>EGULAR</scp>A<scp>MBULANCE</scp>A<scp>TTENDANTS</scp>: A C<scp>OMPARATIVE</scp>T<scp>RIAL</scp>
Bibliographic record
Abstract
OBJECTIVE: Recent cardiac arrest resuscitation guidelines have recommended the esophageal tracheal Combitube (ETC) as an advanced airway management alternative for individuals who infrequently perform endotracheal intubation (ETI). This study attempted to analyze basic (nonparamedic) ambulance attendant success rates at ETI and ETC insertion as well as their continuing skill competency over time and whether ongoing practice on mannequins improved skill performance. METHODS: Three hundred fifty-seven adult patients in cardiorespiratory arrest were treated by 81 basic ambulance attendants. Original study design called for the analysis of two treatment options in three patient groups: ETC insertion, ETI insertion with mannequin practice (ETI-MP), and ETI insertion without mannequin practice (ETI-NMP). The main outcome measures were:successful insertion and ventilation with ETC or ETI, assessed by receiving physicians; and differences in successful insertion/ventilation between the MP and NMP groups. RESULTS: Successful insertion (intent-to-treat) for the ETI-NMP group was 70 of 111 (63%; 95% confidence interval [CI], 54-73%); ETI-MP success was 105 of 139 (76%; 95% CI, 67-84%); ETC-NMP success was 26 of 42 (62%; 95% CI, 49-75%); and ETC-MP success was 36 of 53 (68%; 95% CI, 54-82%). Continuing mannequin practice appeared to improve ETI success (as-treated): MP 75% versus NMP 61% (odds ratio, 2.1; 95% CI, 1.11-3.94). CONCLUSIONS: There were similar rates of successful insertion/ventilation with the ETC and ETI. ETI insertion success was lower without mannequin practice. ETI skill erosion was partially mitigated by additional field experience.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".