Sedation practices in patients intubated in the emergency department compared with those in patients in the intensive care unit
Bibliographic record
Abstract
OBJECTIVE: This study aimed to compare sedation management during and after intubation in the emergency department with that in the intensive care unit. METHODS: This was a single-center retrospective cohort study of adults who were intubated in the emergency department or intensive care unit and who received mechanical ventilation between January 2018 and February 2022. We collected data from electronic medical records. The primary outcome was the duration from intubation to the first documentation of light sedation, which was defined as a Sedation Agitation Scale score of 3 - 4. RESULTS: This study included 264 patients, 95 (36%) of whom were intubated in the emergency department and 169 (64%) in the intensive care unit. With respect to the anesthetic agents used for intubation, ketamine was the most frequently used drug in the emergency department and was used more frequently than in the intensive care unit (61% versus 40%; p = 0.001). Propofol was the predominant sedative used in the intensive care unit, with a higher prevalence than in the emergency department (50% versus 33%; p = 0.01). Additionally, benzodiazepines and fentanyl were more frequently used in the intensive care unit (39% versus 6%; p < 0.001 and 68% versus 9.5%; p < 0.001, respectively). Within 24 hours after intubation, 68% (65/95) of the emergency department patients and 82% (138/169) of the patients intubated in the intensive care unit achieved light sedation, with median durations of 13.5 hours and 10.5 hours, respectively. Patients who were intubated in the emergency department were less likely to achieve light sedation at 24 hours (adjusted hazard ratio 0.64; p = 0.04; 95%CI, 0.42 - 0.97). CONCLUSION: Compared with intensive care unit patients, critically ill patients who were intubated in the emergency department are at risk of deeper sedation and a longer time to achieve light sedation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".