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Record W4412166401 · doi:10.5114/ait/207183

Volatile anesthetics in the intensive care unit

2025· review· en· W4412166401 on OpenAlexaff
Alexander Morrison‐Nozik, Marcin Wąsowicz

Bibliographic record

VenueAnaesthesiology Intensive Therapy · 2025
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineSedationVolatile anestheticIntensive care medicineIntensive care unitPharmacodynamicsIsofluraneAnesthesiaSedativeMechanical ventilationCritically illPharmacokineticsPharmacology

Abstract

fetched live from OpenAlex

The use of volatile anesthetics as an alternative sedation modality in the intensive care unit (ICU) has gained traction over the last several years. Volatile agents such as sevoflurane and isoflurane possess favorable pharmacokinetic and pharmacodynamic properties that make them suitable choices for titration of sedation in patients requiring mechanical ventilation. Several studies have continued to demonstrate their efficacy and safety particularly when assessing wake-up times and times to extubation in contrast to various intravenous sedatives. Leveraging the pharmacodynamic properties of the volatile agents may also be beneficial in certain disease states. As there are devices currently available to enable delivery of volatile anesthetics to patients in the ICU, ongoing studies exist to determine how to best use this sedation modality. This review outlines the recent evidence and discusses perspectives on volatile-based sedation for critically ill patients.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.061
GPT teacher head0.371
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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