Emergent airway management of the critically ill patient: current opinion in critical care
Bibliographic record
Abstract
PURPOSE OF REVIEW: To describe techniques to facilitate safe intubation in critically ill patients. RECENT FINDINGS: Despite advances in the treatment of critically ill patients, endotracheal intubation remains a high-risk procedure associated with complications that can lead to appreciable morbidity and mortality. In addition to the usual anatomical factors that can predict a difficult intubation, incorporating pathophysiological considerations and crisis resource management may enhance safety and mitigate risk. Enhancing preoxygenation with high-flow oxygen or noninvasive ventilation, the early use of intravenous fluids and/or vasopressors to prevent hypotension and videolaryngoscopy for first pass success are all promising additions to airway management.Facilitating intubation by either sedation with paralysis or allowing patients to continue to breathe spontaneously are reasonable options for airway management. These approaches have potential advantages and disadvantages. SUMMARY: Recognizing the unique challenges of endotracheal intubation in critically ill patients is paramount in limiting further deterioration during this high-risk procedure. A safe approach to intubation focuses on recognizing risk factors that predict challenges in achieving an optimal view of the glottis, maintaining optimal oxygenation, and minimizing the risks and benefits of sedation/induction strategies that are meant to facilitate intubation and avoid clinical deterioration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".