Evidence-Based Guideline for Prehospital Airway Management
Bibliographic record
Abstract
Airway management is a cornerstone of emergency medical care. This project aimed to create evidence-based guidelines based on the systematic review recently conducted by the Agency for Healthcare Research and Quality (AHRQ). A technical expert panel was assembled to review the evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology. The panel made specific recommendations on the different PICO (population, intervention, comparison, outcome) questions reviewed in the AHRQ review and created good practice statements that summarize and operationalize these recommendations. The recommendations address the use of ventilation with bag-valve mask ventilation alone vs. supraglottic airways vs. endotracheal intubation for adults and children with cardiac arrest, medical emergencies, and trauma. Additional recommendations address the use of video laryngoscopy and drug-assisted airway management. These recommendations, and the associated good practice statements, offer EMS agencies and clinicians an opportunity to review the available evidence and incorporate it into their airway management strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.009 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".