Asymptomatic hypoxia in COVID-19 is associated with poor outcome

Abstract

Objectives: Describe and evaluate the outcome of a coronavirus disease-2019 (COVID-19) patient without shortness of breath.

Design and methods: We retrospectively collected data from COVID-19 patients diagnosed and cared for in Marseille, France. We selected data from patients who at admission, had a low dose CT scanner, dyspnea status, and oxygen saturation available. Blood gas was analyzed in a sample subset of patients.

Results: Among 1712 patients with COVID-19, we report that 1107 (64.7%) do not complain of shortness of breath at admission. The low-dose computed tomography (LDCT) scan showed signs compatible with pneumonia in 757/1,107 (68.4%) of patients without dyspnea. In a subset of patients who had underwent at least one blood gas analysis (n = 161) and presented without dyspnea at admission, 28.1% (27/96) presented with a hypoxemia/hypocapnia syndrome. Asymptomatic hypoxia was associated with a very poor outcome (33.3% were transferred to the ICU and 25.9% died).

Conclusion: The absence of shortness of breath in an old patient with comorbidity merit medical attention and should not be considered as a good sign of well-being. The poor prognosis of asymptomatic hypoxia, highlight the severity of this mild clinical presentation. In these patients, pulse oximetry is an important mean to predict the outcome along with news score and LDCT scanner.

Keywords: 02 sat; COVID-19; D-dimers; Happy; Hypocapnia; Hypoxemia; Hypoxia; Low dose CT-scan.

Figure 1

LDCT scan at admission in a patient with silent COVID-19 pneumonia who abruptly needed O₂ support and ICU surveillance for 48 h and his control LDCT at day 10 of treatment with hydroxychloroquine and azithromycin showing residual lesions with retraction, suggesting fibrosis.

Figure 2

Venn diagram showing that in patients presenting with no dyspnea (27/96) 28.1% will have hypoxemia hypercapnia syndrome defining asymptomatic hypoxia (161 patients).

Figure 3

Associations between blood gas analysis, clinical data, biological data, and clinical outcomes-Hierarchical Clustering on Principal Components (n = 161).