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Record W4393970436 · doi:10.1101/2024.04.04.24305330

Association between sex and race and ethnicity and intravenous sedation use in patients receiving invasive ventilation

2024· preprint· en· W4393970436 on OpenAlexafffund
Sarah Walker, Federico Angriman, Lisa Burry, Leo Anthony Celi, Kirsten M. Fiest, Judy Wawira Gichoya, Alistair E. W. Johnson, Kuan Liu, Sangeeta Mehta, Georgiana Roman-Sarita, Laleh Seyyed-Kalantari, Thanh-Giang T. Vu, Elizabeth L. Whitlock, George Tomlinson, Christopher J. Yarnell

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsThe Scarborough HospitalVector InstituteUniversity of CalgarySunnybrook Health Science CentreSinai Health SystemHealth Sciences CentreUniversity Health NetworkUniversity of Toronto
FundersUniversity of Toronto
KeywordsRace (biology)SedationEthnic groupAssociation (psychology)Intravenous sedationMedicineAnesthesiaPsychologySociologyGender studiesPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Rationale Intravenous sedation is an important tool for managing invasively ventilated patients, yet excess sedation is harmful, and dosing could be influenced by implicit bias. Objective To measure the association between sex, race and ethnicity, and sedation practices. Methods We performed a retrospective cohort study of adults receiving invasive ventilation for 24 hours or more using the MIMIC-IV (2008-2019) database from Boston, USA. We used a repeated-measures design (4-hour time intervals) to study the association between patient sex (female, male) or race and ethnicity (Asian, Black, Hispanic, White) and sedation outcomes. Sedation outcomes included sedative use (propofol, benzodiazepine, dexmedetomidine) and minimum sedation score. We divided sedative use into five categories: no sedative given, then lowest, second, third, and highest quartiles of sedative dose. We used multilevel Bayesian proportional odds modeling to adjust for baseline and time-varying covariates and reported posterior odds ratios with 95% credible intervals [CrI]. Results We studied 6,764 patients: 43% female; 3.5% Asian, 12% Black, 4.5% Hispanic and 80% white. We analyzed 116,519 4-hour intervals. Benzodiazepines were administered to 2,334 (36%) patients. Black patients received benzodiazepines less often and at lower doses than White patients (OR 0.66, CrI 0.49 to 0.92). Propofol was administered to 3,865 (57%) patients. Female patients received propofol less often and at lower doses than male patients (OR 0.72, CrI 0.61 to 0.86). Dexmedetomidine was administered to 1,439 (21%) patients, and use was largely similar across sex or race and ethnicity. As expressed by sedation scores, male patients were more sedated than female patients (OR 1.41, CrI 1.23 to 1.62), and White patients were less sedated than Black patients (OR 0.78, CrI 0.65 to 0.95). Conclusion Among patients invasively ventilated for at least 24 hours, intravenous sedation and attained sedation levels varied by sex and race and ethnicity. Adherence to sedation guidelines may improve equity in sedation management 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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.351
Teacher spread0.267 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes2
Has abstractyes

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