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Record W4220724255 · doi:10.1136/bmj-2021-068585

Prone positioning of patients with moderate hypoxaemia due to covid-19: multicentre pragmatic randomised trial (COVID-PRONE)

2022· article· en· W4220724255 on OpenAlexaffabout
Michael Fralick, Michael Colacci, Laveena Munshi, Kevin Venus, Lee Fidler, Haseena Hussein, Karen Britto, Rob Fowler, Bruno R. da Costa, Irfan A. Dhalla, Richard Dunbar‐Yaffe, Leora Branfield Day, Thomas E. MacMillan, Jonathan S. Zipursky, Travis Carpenter, Terence Tang, Amanda Cooke, Rachel Hensel, Melissa Bregger, Alexis Gordon, Erin Worndl, Stephanie Go, Keren Mandelzweig, Lana A. Castellucci, Daniel Tamming, Fahad Razak, Amol A. Verma

Bibliographic record

VenueBMJ · 2022
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of OttawaHumber River Regional HospitalThe Scarborough HospitalSt Joseph's Health CentreSunnybrook Health Science CentreSt. Michael's HospitalTrillium Health CentreWilliam Osler Health SystemUniversity of TorontoOttawa HospitalHealth Sciences CentreUniversity Health NetworkSinai Health SystemMount Sinai Hospital
Fundersnot available
KeywordsMedicineInterquartile rangeProne positionFraction of inspired oxygenCoronavirus disease 2019 (COVID-19)Oxygen therapyRandomized controlled trialRespiratory failureMechanical ventilationEmergency medicinePediatricsSurgeryInternal medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the effectiveness of prone positioning to reduce the risk of death or respiratory failure in non-critically ill patients admitted to hospital with covid-19. DESIGN: Multicentre pragmatic randomised clinical trial. SETTING: 15 hospitals in Canada and the United States from May 2020 until May 2021. PARTICIPANTS: Eligible patients had a laboratory confirmed or a clinically highly suspected diagnosis of covid-19, needed supplemental oxygen (up to 50% fraction of inspired oxygen), and were able to independently lie prone with verbal instruction. Of the 570 patients who were assessed for eligibility, 257 were randomised and 248 were included in the analysis. INTERVENTION: Patients were randomised 1:1 to prone positioning (that is, instructing a patient to lie on their stomach while they are in bed) or standard of care (that is, no instruction to adopt prone position). MAIN OUTCOME MEASURES: The primary outcome was a composite of in-hospital death, mechanical ventilation, or worsening respiratory failure defined as needing at least 60% fraction of inspired oxygen for at least 24 hours. Secondary outcomes included the change in the ratio of oxygen saturation to fraction of inspired oxygen. RESULTS: The trial was stopped early on the basis of futility for the pre-specified primary outcome. The median time from hospital admission until randomisation was 1 day, the median age of patients was 56 (interquartile range 45-65) years, 89 (36%) patients were female, and 222 (90%) were receiving oxygen via nasal prongs at the time of randomisation. The median time spent prone in the first 72 hours was 6 (1.5-12.8) hours in total for the prone arm compared with 0 (0-2) hours in the control arm. The risk of the primary outcome was similar between the prone group (18 (14%) events) and the standard care group (17 (14%) events) (odds ratio 0.92, 95% confidence interval 0.44 to 1.92). The change in the ratio of oxygen saturation to fraction of inspired oxygen after 72 hours was similar for patients randomised to prone positioning and standard of care. CONCLUSION: Among non-critically ill patients with hypoxaemia who were admitted to hospital with covid-19, a multifaceted intervention to increase prone positioning did not improve outcomes. However, wide confidence intervals preclude definitively ruling out benefit or harm. Adherence to prone positioning was poor, despite multiple efforts to increase it. Subsequent trials of prone positioning should aim to develop strategies to improve adherence to awake prone positioning. STUDY REGISTRATION: ClinicalTrials.gov NCT04383613.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.027
GPT teacher head0.307
Teacher spread0.280 · 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.

Study designRandomized trial
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

Citations110
Published2022
Admission routes2
Has abstractyes

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