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KMID : 1044520210840020115
Tuberculosis and Respiratory Diseases
2021 Volume.84 No. 2 p.115 ~ p.124
Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia
Hahm Cho-Rom

Lee Young-Kyung
Oh Dong-Hyun
Ahn Mi-Young
Choi Jae-Phil
Kang Na-Ree
Oh Jung-Kyun
Choi Han-Zo
Kim Su-Hyun
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 ¡Â94% 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 ¡Ã280 ¥ìg/L (p=0.029), lactate dehydrogenase ¡Ã240 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
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