High-Flow Nasal Cannula Treatment in Patients with COVID-19 Acute Hypoxemic Respiratory Failure
Bibliographic record
Abstract
Abstract BackgroundThe increasing burden of coronavirus disease 2019 (COVID-19)-related acute hypoxemic respiratory failure (AHRF) is straining intensive care unit (ICU) resources globally. Early use of high-flow nasal cannula (HFNC) decreases the need for endotracheal intubation (EI) in different causes of respiratory failure. While HFNC is used in COVID-19-related AHRF, its efficacy remains to be investigated. We aimed to examine whether the use of high-flow nasal oxygen therapy (HFNO) prevents the need for intubation in COVID-19 with (AHRF).MethodsThis is a single-center prospective observational study that was conducted at a tertiary teaching hospital in Saudi Arabia the period from April, 2020 to August, 2020. Adults patients admitted to the ICU with AHRF secondary to COVID-19 pneumonia and managed with HFNC were included. We excluded hemodynamically unstable patients and those who were intubated or managed with non-invasive ventilation. Patients’ data and clinical outcomes were pre-defined. The primary outcome was to determine the rate of EI among patients who were treated with HFNC. Secondary outcomes included predictors of HFNC success/failure, mortality, and hospital length of stay. ResultsWe consecutively screened 111 hospitalized COVID-19 patients with AHRF,. Out of those, 44 (40%) patients received HFNC with a median duration of three days (IQR, 1–5). The median age was 57 years (interquartile range [IQR], 46–64), and 82% were men. HFNC failure and EI occurred in 29 (66%) patients. Patients who failed HFNC treatment had higher risk of death compared to those who did not (52% vs. 0%; p=0.001). At baseline, the prevalence of hypertension, chronic kidney disease, and asthma was higher in the HFNC failure group. After adjustment for possible confounders, a high Sequential Organ Failure Assessment (SOFA) score and a low ROX index were significantly associated with HFNC failure (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.04–1.93; p=0.025; and HR, 0.61; 95% CI, 0.42–0.88; p=0.008, respectively). ConclusionsIn this prospective study, one-third of hypoxemic COVID-19 patients who received HFNC did not require intubation. High SOFA score and low ROX index were associated with HFNC failure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".