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Tuberculosis & Respiratory Diseases

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Vol.84 No.2
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Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia

Tuberculosis & Respiratory Diseases / Tuberculosis & Respiratory Diseases,
2021, v.84 no.2, pp.115-124
https://doi.org/10.4046/trd.2020.0139
Cho Rom Hahm (Seoul Medical Center)
Lee Young Kyung (Department of Radiology, Seoul Medical Center, Seoul, Korea.)
Oh Dong Hyun (Department of Internal Medicine, Seoul Medical Center, Seoul, Korea.)
Ahn Mi Young (Department of Internal Medicine, Seoul Medical Center, Seoul, Korea.)
Choi Jae-Phil (Department of Internal Medicine, Seoul Medical Center, Seoul, Korea.)
Kang Na Ree (Seoul Medical Center)
Oh JungKyun (Department of Hospital Medicine, Seoul Medical Center, Seoul, Korea.)
Choi Hanzo (Department of Emergency Medicine, Myong Ji St. Mary’s Hospital, Seoul, Republic of Korea)
Kim Suhyun (Department of Internal Medicine, Seoul Medical Center, Seoul, Korea.)
Cho, R. H. , Lee, Y. K. , Oh, D. H. , Ahn, M. Y. , Choi, J. , Kang, N. R. , Oh, J. , Choi, H. , & Kim, S. (2021). Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia. Tuberculosis & Respiratory Diseases, 84(2), 115-124, https://doi.org/10.4046/trd.2020.0139
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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.

keywords
Pneumonia, COVID-19, Computed Tomography, Artificial Intelligence, Oxygenation

Reference

1.

1. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med 2020;180:934-43.

2.

2. Berlin DA, Gulick RM, Martinez FJ. Severe COVID-19. N Engl J Med 2020;383:2451-60.

3.

3. Weiss P, Murdoch DR. Clinical course and mortality risk of severe COVID-19. Lancet 2020;395:1014-5.

4.

4. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA 2020;323:1574-81.

5.

5. Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis 2020;94:91-5.

6.

6. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020;8:475-81.

7.

7. Velavan TP, Meyer CG. Mild versus severe COVID-19: laboratory markers. Int J Infect Dis 2020;95:304-7.

8.

8. Zhao W, Zhong Z, Xie X, Yu Q, Liu J. Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: a multicenter study. AJR Am J Roentgenol 2020;214:1072-7.

9.

9. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology 2020;295:715-21.

10.

10. Feng Y, Ling Y, Bai T, Xie Y, Huang J, Li J, et al. COVID-19 with different severities: a multicenter study of clinical features. Am J Respir Crit Care Med 2020;201:1380-8.

11.

11. Chang YC, Yu CJ, Chang SC, Galvin JR, Liu HM, Hsiao CH, et al. Pulmonary sequelae in convalescent patients after severe acute respiratory syndrome: evaluation with thin-section CT. Radiology 2005;236:1067-75.

12.

12. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20.

13.

13. Kim ES, Chin BS, Kang CK, Kim NJ, Kang YM, Choi JP, et al. Clinical course and outcomes of patients with severe acute respiratory syndrome coronavirus 2 infection: a preliminary report of the first 28 patients from the Korean cohort study on COVID-19. J Korean Med Sci 2020;35:e142.

14.

14. Hong KS, Lee KH, Chung JH, Shin KC, Choi EY, Jin HJ, et al. Clinical features and outcomes of 98 patients hospitalized with SARS-CoV-2 infection in Daegu, South Korea: a brief descriptive study. Yonsei Med J 2020;61:431-7.

15.

15. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020;323:1239-42.

16.

16. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical Characteristics of 138 Hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020;323:1061-9.

17.

17. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.

18.

18. Bhatraju PK, Ghassemieh BJ, Nichols M, Kim R, Jerome KR, Nalla AK, et al. COVID-19 in critically ill patients in the Seattle region: case series. N Engl J Med 2020;382:2012-22.

19.

19. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020;395:1054-62.

20.

20. Chen J, Qi T, Liu L, Ling Y, Qian Z, Li T, et al. Clinical progression of patients with COVID-19 in Shanghai, China. J Infect 2020;80:e1-6.

21.

21. Guo L, Wei D, Zhang X, Wu Y, Li Q, Zhou M, et al. Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA score. Front Microbiol 2019;10:2752.

22.

22. Xie J, Tong Z, Guan X, Du B, Qiu H, Slutsky AS. Critical care crisis and some recommendations during the COVID-19 epidemic in China. Intensive Care Med 2020;46:837-40.

23.

23. Huang L, Han R, Ai T, Yu P, Kang H, Tao Q, et al. Serial Quantitative chest CT assessment of COVID-19: deep-learning approach. Radiology Cardiothoracic Imaging 2020;2:e200075.

24.

24. Luo Z, Wang N, Liu P, Guo Q, Ran L, Wang F, et al. Association between chest CT features and clinical course of Coronavirus Disease 2019. Respir Med 2020;168:105989.

25.

25. Liu F, Zhang Q, Huang C, Shi C, Wang L, Shi N, et al. CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients. Theranostics 2020;10:5613-22.

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