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Record W3212747713 · doi:10.1097/cce.0000000000000567

Assessment of 28-Day In-Hospital Mortality in Mechanically Ventilated Patients With Coronavirus Disease 2019: An International Cohort Study

2021· article· en· W3212747713 on OpenAlexaff
Gianluigi Li Bassi, Jacky Y. Suen, Nicole White, Heidi J. Dalton, Jonathon P. Fanning, Amanda Corley, Sally Shrapnel, Samuel Hinton, Simon Forsyth, Rex Parsons, John G. Laffey, Eddy Fan, Robert H. Bartlett, Daniel Brodie, Aidan Burrell, Davide Chiumello, Alyaa Elhazmi, Giacomo Grasselli, Carol Hodgson, Shingo Ichiba, Carlos Luna, Eva Miranda Marwali, Laura Merson, Srinivas Murthy, Alistair Nichol, Mauro Panigada, Paolo Pelosi, Antoní Torres, Pauline Yeung Ng, Mark Ogino, John F. Fraser

Bibliographic record

VenueCritical Care Explorations · 2021
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersExtracorporeal Life Support Organization
KeywordsMedicineCoronavirus disease 2019 (COVID-19)CohortCoronavirusCohort studyEmergency medicineDiseaseSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mechanical ventilation2019-20 coronavirus outbreakIntensive care medicineVirologyInternal medicineInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

IMPORTANCE: Factors associated with mortality in coronavirus disease 2019 patients on invasive mechanical ventilation are still not fully elucidated. OBJECTIVES: To identify patient-level parameters, readily available at the bedside, associated with the risk of in-hospital mortality within 28 days from commencement of invasive mechanical ventilation or coronavirus disease 2019. DESIGN, SETTING, AND PARTICIPANTS: Prospective observational cohort study by the global Coronavirus Disease 2019 Critical Care Consortium. Patients with laboratory-confirmed coronavirus disease 2019 requiring invasive mechanical ventilation from February 2, 2020, to May 15, 2021. MAIN OUTCOMES AND MEASURES: Patient characteristics and clinical data were assessed upon ICU admission, the commencement of invasive mechanical ventilation and for 28 days thereafter. We primarily aimed to identify time-independent and time-dependent risk factors for 28-day invasive mechanical ventilation mortality. RESULTS: One-thousand five-hundred eighty-seven patients were included in the survival analysis; 588 patients died in hospital within 28 days of commencing invasive mechanical ventilation (37%). Cox-regression analysis identified associations between the hazard of 28-day invasive mechanical ventilation mortality with age (hazard ratio, 1.26 per 10-yr increase in age; 95% CI, 1.16–1.37; p < 0.001), positive end-expiratory pressure upon commencement of invasive mechanical ventilation (hazard ratio, 0.81 per 5 cm H 2 O increase; 95% CI, 0.67–0.97; p = 0.02). Time-dependent parameters associated with 28-day invasive mechanical ventilation mortality were serum creatinine (hazard ratio, 1.28 per doubling; 95% CI, 1.15–1.41; p < 0.001), lactate (hazard ratio, 1.22 per doubling; 95% CI, 1.11–1.34; p < 0.001), Pa co 2 (hazard ratio, 1.63 per doubling; 95% CI, 1.19–2.25; p < 0.001), pH (hazard ratio, 0.89 per 0.1 increase; 95% CI, 0.8–14; p = 0.041), Pa o 2 /F io 2 (hazard ratio, 0.58 per doubling; 95% CI, 0.52–0.66; p < 0.001), and mean arterial pressure (hazard ratio, 0.92 per 10 mm Hg increase; 95% CI, 0.88–0.97; p = 0.003). CONCLUSIONS AND RELEVANCE: This international study suggests that in patients with coronavirus disease 2019 on invasive mechanical ventilation, older age and clinically relevant variables monitored at baseline or sequentially during the course of invasive mechanical ventilation are associated with 28-day invasive mechanical ventilation mortality hazard. Further investigation is warranted to validate any causative roles these parameters might play in influencing clinical outcomes.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.041
GPT teacher head0.391
Teacher spread0.350 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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