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Record W2311680441 · doi:10.1164/rccm.201512-2435cp

Volatile Anesthetics. Is a New Player Emerging in Critical Care Sedation?

2016· review· en· W2311680441 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of TorontoUniversity Health NetworkToronto General Hospital
Fundersnot available
KeywordsSedationMedicineIntensive care medicinePropofolIntensive care unitVolatile anestheticCritically illCritical illnessBenzodiazepineAnesthesiaAnesthetic

Abstract

fetched live from OpenAlex

Volatile anesthetic agent use in the intensive care unit, aided by technological advances, has become more accessible to critical care physicians. With increasing concern over adverse patient consequences associated with our current sedation practice, there is growing interest to find non-benzodiazepine-based alternative sedatives. Research has demonstrated that volatile-based sedation may provide superior awakening and extubation times in comparison with current intravenous sedation agents (propofol and benzodiazepines). Volatile agents may possess important end-organ protective properties mediated via cytoprotective and antiinflammatory mechanisms. However, like all sedatives, volatile agents are capable of deeply sedating patients, which can have respiratory depressant effects and reduce patient mobility. This review seeks to critically appraise current volatile use in critical care medicine including current research, technical consideration of their use, contraindications, areas of controversy, and proposed future research topics.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.045
GPT teacher head0.408
Teacher spread0.363 · 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