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Record W4387692892 · doi:10.1097/ccm.0000000000006056

The Predictive Validity of the Berlin Definition of Acute Respiratory Distress Syndrome for Patients With COVID-19-Related Respiratory Failure Treated With High-Flow Nasal Oxygen: A Multicenter, Prospective Cohort Study*

2023· article· en· W4387692892 on OpenAlexaff
Marina Busico, Nora A. Fuentes, Adrián Gallardo, Alejandra Vitali, Jorgelina Quintana, Matias Olmos, Karen E. A. Burns, Mariano Esperatti

Bibliographic record

VenueCritical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineARDSProspective cohort studyCohortNasal cannulaCohort studyMechanical ventilationReceiver operating characteristicInternal medicineRespiratory distressRespiratory failureSurgeryLung

Abstract

fetched live from OpenAlex

OBJECTIVES: The Berlin definition of acute respiratory distress syndrome (ARDS) was constructed for patients receiving invasive mechanical ventilation (IMV) with consideration given to issues related to reliability, feasibility, and validity. Notwithstanding, patients with acute respiratory failure (ARF) may be treated with high-flow nasal oxygen (HFNO) and may not fall within the scope of the original definition. We aimed to evaluate the predictive validity of the Berlin definition in HFNO-treated patients with COVID-19-related respiratory failure who otherwise met ARDS criteria. DESIGN: Multicenter, prospective cohort study. SETTING: Five ICUs of five centers in Argentina from March 2020 to September 2021. PATIENTS: We consecutively included HFNO-treated patients older than 18 years with confirmed COVID-19-related ARF, a Pa o2 /F io2 of less than 300 mm Hg, bilateral infiltrates on imaging, and worsening respiratory symptoms for less than 1 week. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We evaluated the predictive validity of mortality at day 28 using the area under the receiver operating characteristics curve (AUC), compared the predictive validity across subgroups, and characterized relevant clinical outcomes. We screened 1,231 patients and included 696 ARDS patients [30 (4%) mild, 380 (55%) moderate, and 286 (41%) severe]. For the study cohort, the AUC for mortality at day 28 was 0.606 (95% CI, 0.561-0.651) with the AUC for subgroups being similar to that of the overall cohort. Two hundred fifty-six patients (37%) received IMV. By day 28, 142 patients (21%) had died, of whom 81 (57%) had severe ARDS. Mortality occurred primarily in patients who were transitioned to IMV. CONCLUSIONS: The predictive validity of the Berlin ARDS definition was similar for HFNO-treated patients as compared with the original population of invasively ventilated patients. Our findings support the extension of the Berlin definition to HFNO-treated patients with ARDS.

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)0.003
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.026
GPT teacher head0.302
Teacher spread0.275 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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