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Record W4386156786 · doi:10.1097/cce.0000000000000968

Failure of First Transition to Pressure Support Ventilation After Spontaneous Awakening Trials in Hypoxemic Respiratory Failure: Influence of COVID-19

2023· article· en· W4386156786 on OpenAlexaff
Joaquín Pérez, Matías Accoce, Javier Hernán Dorado, Daniela Inés Gilgado, Emiliano Navarro, Gimena Paola Cardoso, Irene Telías, Pablo Rodríguez, Laurent Brochard

Bibliographic record

VenueCritical Care Explorations · 2023
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSinai Health SystemUniversity of TorontoUniversity Health NetworkSt. Michael's Hospital
Fundersnot available
KeywordsMedicineMechanical ventilationRespiratory failureFraction of inspired oxygenEtiologyVentilation (architecture)Odds ratioPressure support ventilationCoronavirus disease 2019 (COVID-19)CohortAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the rate of failure of the first transition to pressure support ventilation (PSV) after systematic spontaneous awakening trials (SATs) in patients with acute hypoxemic respiratory failure (AHRF) and to assess whether the failure is higher in COVID-19 compared with AHRF of other etiologies. To determine predictors and potential association of failure with outcomes. DESIGN: Retrospective cohort study. SETTING: Twenty-eight-bedded medical-surgical ICU in a private hospital (Argentina). PATIENTS: Subjects with arterial pressure of oxygen (AHRF to F io 2 [Pa o 2 /F io 2 ] < 300 mm Hg) of different etiologies under controlled mechanical ventilation (MV). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We collected data during controlled ventilation within 24 hours before SAT followed by the first PSV transition. Failure was defined as the need to return to fully controlled MV within 3 calendar days of PSV start. A total of 274 patients with AHRF (189 COVID-19 and 85 non-COVID-19) were included. The failure occurred in 120 of 274 subjects (43.7%) and was higher in COVID-19 versus non-COVID-19 (49.7% and 30.5%; p = 0.003). COVID-19 diagnosis (odds ratio [OR]: 2.22; 95% CI [1.15–4.43]; p = 0.020), previous neuromuscular blockers (OR: 2.16; 95% CI [1.15–4.11]; p = 0.017) and higher fentanyl dose (OR: 1.29; 95% CI [1.05–1.60]; p = 0.018) increased the failure chances. Higher BMI (OR: 0.95; 95% CI [0.91–0.99]; p = 0.029), Pa o 2 /F io 2 (OR: 0.87; 95% CI [0.78–0.97]; p = 0.017), and pH (OR: 0.61; 95% CI [0.38–0.96]; p = 0.035) were protective. Failure groups had higher 60-day ventilator dependence ( p < 0.001), MV duration ( p < 0.0001), and ICU stay ( p = 0.001). Patients who failed had higher mortality in COVID-19 group ( p < 0.001) but not in the non-COVID-19 ( p = 0.083). CONCLUSIONS: In patients with AHRF of different etiologies, the failure of the first PSV attempt was 43.7%, and at a higher rate in COVID-19. Independent risk factors included COVID-19 diagnosis, fentanyl dose, previous neuromuscular blockers, acidosis and hypoxemia preceding SAT, whereas higher BMI was protective. Failure was associated with worse 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)0.010
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.072
GPT teacher head0.365
Teacher spread0.293 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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