Bibliographic record
Abstract
Endotracheal intubation in the ICU is a high-risk procedure, resulting in significant morbidity and mortality. Up to 40% of cases are associated with marked hypoxemia or hypotension. The ICU patient is physiologically very different from the usual patient who undergoes intubation in the operating room, and different intubation techniques should be considered. The common operating room practice of sedation and neuromuscular blockade to facilitate intubation may carry significant risk in the ICU patient with a marked oxygenation abnormality, particularly when performed by the non-expert. Preoxygenation is largely ineffective in these patients and oxygen desaturation occurs rapidly on induction of anesthesia, limiting the time available to secure the airway. The ICU environment is less favorable for complex airway management than the operating room, given the frequent lack of availability of additional equipment or additional expert staff. ICU intubations are frequently carried out by trainees, with a lesser degree of airway experience. Even in the presence of a non-concerning airway assessment, these patients are optimally managed as a difficult airway, utilizing an awake approach. Endotracheal intubation may be achieved by awake direct laryngoscopy in the sick ICU patient whose level of consciousness may be reduced by sepsis, hypercapnia or hypoxemia. As the patient's spontaneous respiratory efforts are not depressed by the administration of drugs, additional time is available to obtain equipment and expertise in the event of failure to secure the airway. ICU intubation complications should be tracked as part of the ICU quality improvement process.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".