Halogenated volatile anesthetics in the intensive care unit: current knowledge on an upcoming practice
Bibliographic record
Abstract
The aim of this narrative review was to highlight key points of volatile anesthetics administration in the intensive care unit (ICU), including AnaConDa® and Mirus® devices characteristics and the reported findings on clinical outcomes in critically ill patients. Intravenous sedation in the ICU is associated with issues, such as over- and under-sedation. Halogenated compounds, which can be safely administered by inserting a device in any ICU ventilation circuit, have interesting pharmacodynamic and pharmacokinetic profiles for patients with multi-organ failure. Moreover, analysis of the concentration of exhaled volatile compounds could help evaluation of sedation depth. A recent meta-analysis confirmed that rapid washout of the volatile anesthetics improved both extubation readiness and quality of awakening when compared to intravenous sedation. When administered for a long period, volatile anesthetics improved sedation stability with fewer dose adjustments. Pre- and post-conditioning properties of halogenated compounds are interesting and long-term exposition to this compound is investigated for a potential impact on mortality rate and ICU/hospital length of stay. For now, psychomotor side effects have been reported, mostly in infants, but there were no hepatic or renal injuries. Findings regarding hemodynamic stability are conflicting. Apart from sedation, volatile anesthetics were therapeutic in case reports of status asthmaticus and epilepticus and data are cumulating for benefits in cases of acute respiratory distress syndrome. According to current literature, they should be withheld in cerebral injury. To summarize, the use of volatile anesthetics for sedation is yet only approved by German guidelines, but could spread due to its potential benefits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".