High Failure Rate of Noninvasive Oxygenation Strategies in Critically Ill Subjects With Acute Hypoxemic Respiratory Failure Due to COVID-19.

Background: The efficacy of noninvasive oxygenation strategies (NIOS) in treating COVID-19 disease is unknown. We conducted a prospective observational study to assess the rate of NIOS failure in subjects treated in the ICU for hypoxemic respiratory failure due to COVID-19.
Methods: Patients receiving first-line treatment NIOS for hypoxemic respiratory failure due to COVID-19 in the ICU of a university hospital were included in this study; laboratory data were collected upon arrival, and 28-d outcome was recorded. After propensity score matching based on Simplified Acute Physiology (SAPS) II score, age, [Formula: see text] and [Formula: see text] at arrival, the NIOS failure rate in subjects with COVID-19 was compared to a previously published cohort who received NIOS during hypoxemic respiratory failure due to other causes.
Results: A total of 85 subjects received first-line treatment with NIOS. The most frequently used methods were helmet noninvasive ventilation and high-flow nasal cannula; of these, 52 subjects (61%) required endotracheal intubation. Independent factors associated with NIOS failure were SAPS II score ( P = .009) and serum lactate dehydrogenase at enrollment ( P = .02); the combination of SAPS II score ≥ 33 with serum lactate dehydrogenase ≥ 405 units/L at ICU admission had 91% specificity in predicting the need for endotracheal intubation. In the propensity-matched cohorts (54 pairs), subjects with COVID-19 showed higher risk of NIOS failure than those with other causes of hypoxemic respiratory failure (59% vs 35%, P = .02), with an adjusted hazard ratio of 2 (95% CI 1.1-3.6, P = .01).
Conclusions: As compared to hypoxemic respiratory failure due to other etiologies, subjects with COVID-19 who were treated with NIOS in the ICU were burdened by a 2-fold higher risk of failure. Subjects with a SAPS II score ≥ 33 and serum lactate dehydrogenase ≥ 405 units/L represent the population with the greatest risk.
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