Tuberc Respir Dis.  2021 Apr;84(2):115-124. 10.4046/trd.2020.0139.

Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia

• Hahm CR
• Lee YK
• Oh DH
• Ahn MY
• Choi JP
• Kang NR
• Oh J
• Choi H
• Kim S

• KMID: 2514020
• DOI: http://doi.org/10.4046/trd.2020.0139

Abstract

Background
This study aimed to determine the parameters for worsening oxygenation in non-severe coronavirus disease 2019 (COVID-19) pneumonia.
Methods
This retrospective cohort study included cases of confirmed COVID-19 pneumonia in a public hospital in South Korea. The worsening oxygenation group was defined as that with SpO2 ≤94% or received oxygen or mechanical ventilation (MV) throughout the clinical course versus the non-worsening oxygenation group that did not experience any respiratory event. Parameters were compared, and the extent of viral pneumonia from an initial chest computed tomography (CT) was calculated using artificial intelligence (AI) and measured visually by a radiologist.
Results
We included 136 patients, with 32 (23.5%) patients in the worsening oxygenation group; of whom, two needed MV and one died. Initial vital signs and duration of symptoms showed no difference between the two groups; however, univariate logistic regression analysis revealed that a variety of parameters on admission were associated with an increased risk of a desaturation event. A subset of patients was studied to eliminate potential bias, that ferritin ≥280 μg/L (p=0.029), lactate dehydrogenase ≥240 U/L (p=0.029), pneumonia volume (p=0.021), and extent (p=0.030) by AI, and visual severity scores (p=0.042) were the predictive parameters for worsening oxygenation in a sex-, age-, and comorbid illness-matched case-control study using propensity score (n=52).
Conclusion
Our study suggests that initial CT evaluated by AI or visual severity scoring as well as serum markers of inflammation on admission are significantly associated with worsening oxygenation in this COVID-19 pneumonia cohort.

Keyword

Pneumonia; COVID-19; Computed Tomography; Artificial Intelligence; Oxygenation