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Record W4392202759 · doi:10.1016/j.chstcc.2024.100059

Barriers, Facilitators, and Trends in Prone Positioning for ARDS

2024· article· en· W4392202759 on OpenAlexaff
Thomas Bodley, Dominique Piquette, Kaveh G Shojania, Ruxandra Pinto, Damon C. Scales, Andre CKB Amaral

Bibliographic record

VenueCHEST Critical Care · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsHealth Sciences CentreThe Scarborough HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsARDSProne positionMedicineSurgeryInternal medicineLung

Abstract

fetched live from OpenAlex

Background Prone positioning is a historically underused evidence-based practice for ARDS. Despite increased prone positioning during the COVID-19 pandemic, some patients may remain at risk of nonuse. Research Question What is the current evidence-based gap for prone positioning in ARDS, how is use changing over time, and what are patient-level barriers and facilitators to prone positioning? Study Design and Methods This retrospective cohort included invasively ventilated adults with ARDS and who met prone positioning criteria from six hospitals. The rate of prone positioning among eligible patients was summarized from January 2018 through December 2021. Segmented Poisson regression was used to describe temporal trends. Logistic regression was used to identify patient-level barriers and facilitators to prone positioning. Results Seven hundred ninety-nine patients fulfilled criteria for prone positioning. The mean age was 57 years, 125 patients (15.6%) had COVID-19, mean ICU stay was 19.5 days, and the mortality rate was 50.1%. Prone positioning was used in 297 of 799 patients (37.2%). Prone positioning was increasing before the pandemic with a relative rate (RR) of 1.12 per quarter (95% CI, 1.03-1.22). Prone positioning increased during the pandemic vs before the pandemic (RR, 1.62; 95% CI, 1.02-2.61), but not for patients with nonrespiratory diagnoses causing ARDS (RR, 0.74; 95% CI, 0.22-2.52). Barriers to prone positioning included vasopressor use (OR for withholding prone positioning, 1.15 per 0.1 μm/kg/min norepinephrine equivalent; 95% CI, 1.06-1.26), age (OR, 1.12 per 5 years; 95% CI, 1.03-1.22), and having undergone surgery (OR, 2.41; 95% CI, 1.00-5.81). Facilitators included having COVID-19 (OR for withholding prone positioning, 0.10; 95% CI, 0.04-0.24) or another respiratory illness (OR, 0.42; 95% CI, 0.23-0.79), and receiving neuromuscular blockade (OR, 0.22; 95% CI, 0.13-0.38). Interpretation Despite increased prone positioning during the COVID-19 pandemic, an evidence-based gap persists, especially for patients with nonrespiratory causes of ARDS. Multiple barriers and facilitators must be targeted to increase prone positioning.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.348
Teacher spread0.324 · 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 designNot applicable
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

Citations5
Published2024
Admission routes1
Has abstractyes

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