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Record W4404660406 · doi:10.1186/s41479-024-00145-9

Oxygenation indices and early prediction of outcome in hypoxemic patients with COVID-19 pneumonia requiring noninvasive respiratory support in pulmonary intermediate care unit

2024· article· en· W4404660406 on OpenAlexaff
Raffaele Scala, Teresa Renda, Sonia Bambina, Luca Guidelli, Stefania Arniani, Laura Carrassa, Simon Oczkowski

Bibliographic record

VenuePneumonia · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)PneumoniaOxygenationIntensive care medicineIntensive care unit2019-20 coronavirus outbreakCardiologyInternal medicineDiseaseVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Early prediction of non-invasive respiratory therapy (NIRT) failure is crucial to avoid needless prolongation of respiratory support and delayed endotracheal intubation. Data comparing the predictive value of oxygenation indices (OI) in COVID-19 receiving NIRT are scant. The aim of this monocentric retrospective study of prospectively collected data was to assess the effectiveness of different OI in predicting NIRT outcome at baseline (t0), 12 h (t12) and 24 h (t24) of treatment in hypoxemic patients with COVID-19-related pneumonia, managed in a Pulmonary Intermediate Care Unit (October 2020-June 2021). METHODS: We assessed the predictive value of SpO2/FiO2, PaO2/FiO2, standardised PaO2/FiO2 ratio (s-PaO2/FiO2), respiratory index (RI), arterial-alveolar oxygen gradient (a-ADO2), age adjusted arterial-alveolar oxygen ratio (adj-a-ADO2D). Receiver operating characteristics (ROC), AUC and best sensitivity-specificity cut-off values were calculated at t0, t12, t24. NIRT failure risk was adjusted for non-oxygenation predictors. RESULTS: Among 590 patients with COVID-19 infection, 368 met the eligibility criteria for inclusion in the study [mean (CI95%): PaO2/FiO2 214(206,8-221,9); PaCO2 mean 32,9 mmHg,(32,4-33,4)]. NIRT failure and hospital mortality rate were 23,4% and 19,6%, respectively. Older age, male gender, agitation/confusion, need for sedation, inability to tolerate prone positioning were independent predictors of NIRT failure. SpO2/FiO2, a-ADO2 and adj-aADO2 at t12 and t24, PaO2/FiO2 and RI at t24 were associated with NIRT failure. Prognostic predictivity of OI increased from t0 to t24. Greater ROC-AUC values were obtained with SpO2/FiO2 0,662 (0,60-0,72) (t0), PaO2/FiO2 0,697 (0,63-0,76) (t12) and s-PaO2/FiO2 0,769 (0,71-0,83) (t24). NIRT failure was independently predicted by PaO2/FiO2, s-PaO2/FiO2 and RI at any observation time and by SpO2/FiO2 and O2 gradients respectively at t0 and t24. SaO2/FiO2 ≤ 300 (t0), PaO2/FiO2 ≤ 151,7 (t12) and s-PaO2/FiO2 ≤ 160,4 (t24) turned out to be the best predictors of NIRT outcome. CONCLUSIONS: OI showed different effectiveness in predicting NIRT failure within 24 h of treatment in COVID-19 related pneumonia. This may be due to the multi-factorial pathophysiology of hypoxemia. Our study empathises furthermore the role of non-oxygenation-related parameters in contributing to the outcome. These findings may be useful to build a predictive model also in no COVID-19 related hypoxemic pneumonia.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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