MétaCan
Menu
Back to cohort
Record W4313332376 · doi:10.1097/mcc.0000000000001011

The impact of the coronavirus pandemic on sedation in critical care: volatile anesthetics in the ICU

2022· review· en· W4313332376 on OpenAlexaff
Angela Jerath, Marat Slessarev

Bibliographic record

VenueCurrent Opinion in Critical Care · 2022
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsHealth Sciences CentreUniversity of TorontoWestern UniversityInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsSedationMedicinePandemicCoronavirus disease 2019 (COVID-19)Intensive care medicineHealth careCoronavirusSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Economic shortage2019-20 coronavirus outbreakAnesthesiaDiseaseVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To reflect on the impact of the coronavirus pandemic on sedation for mechanically ventilated patients. RECENT FINDINGS: Shortages of intravenous sedatives during coronavirus pandemic renewed interest in using widely available inhaled anaesthetics for sedation of critically ill patients. Universally used for surgical anaesthesia, inhaled anaesthetics may offer therapeutic advantages in patients with acute lung injury with good sedation profiles, rapid clearance and lower lung inflammation in pilot trials. However, enabling ICU sedation with inhaled anaesthetics required technological and human resource innovation during the chaos of the global pandemic. The disruption of standard sedation practices is challenging during normal operations, yet pandemic facilitated innovation in this field by fostering cross-discipline collaboration supported by healthcare professionals, hospitals, research institutes and regulators. SUMMARY: Although further research is needed to establish the role of inhaled anaesthetics in critical care sedation toolkit, maintaining the spirit of innovation ignited during the recent coronavirus pandemic would require ongoing collaboration and streamlining of processes among healthcare, research and regulatory institutions.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.321
GPT teacher head0.541
Teacher spread0.221 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Critical CareSame topicInfection Control and VentilationFrench-language works237,207