Preventing unrecognised oesophageal intubation: a consensus guideline from the Project for Universal Management of Airways and international airway societies*
Bibliographic record
Abstract
Across multiple disciplines undertaking airway management globally, preventable episodes of unrecognised oesophageal intubation result in profound hypoxaemia, brain injury and death. These events occur in the hands of both inexperienced and experienced practitioners. Current evidence shows that unrecognised oesophageal intubation occurs sufficiently frequently to be a major concern and to merit a co-ordinated approach to address it. Harm from unrecognised oesophageal intubation is avoidable through reducing the rate of oesophageal intubation, combined with prompt detection and immediate action when it occurs. The detection of 'sustained exhaled carbon dioxide' using waveform capnography is the mainstay for excluding oesophageal placement of an intended tracheal tube. Tube removal should be the default response when sustained exhaled carbon dioxide cannot be detected. If default tube removal is considered dangerous, urgent exclusion of oesophageal intubation using valid alternative techniques is indicated, in parallel with evaluation of other causes of inability to detect carbon dioxide. The tube should be removed if timely restoration of sustained exhaled carbon dioxide cannot be achieved. In addition to technical interventions, strategies are required to address cognitive biases and the deterioration of individual and team performance in stressful situations, to which all practitioners are vulnerable. These guidelines provide recommendations for preventing unrecognised oesophageal intubation that are relevant to all airway practitioners independent of geography, clinical location, discipline or patient type.
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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 | 0.028 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".