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논문 기본 정보

자료유형
학술저널
저자정보
Ji Wonjun (Department of Pulmonary and Critical Care Medicine Asan Medical Center University of Ulsan College) Huh Kyungmin (Division of Infectious Diseases Department of Medicine Samsung Medical Center Sungkyunkwan Universi) Kang Minsun (Artificial Intelligence and Big-Data Convergence Center Gil Medical Center Gachon University Colleg) Hong Jinwook (Gachon University College of Medicine) Bae Gi Hwan (Artificial Intelligence and Big-Data Convergence Center Gil Medical Center Gachon University Colleg) Rugyeom Lee (Gachon University College of Medicine) Na Yewon (Artificial Intelligence and Big-Data Convergence Center Gil Medical Center Gachon University Colleg) Choi Hyoseon (Department of Preventive Medicine Gachon University College of Medicine Incheon Korea.) Gong Seon Yeong (Department of Preventive Medicine Gachon University College of Medicine Incheon Korea.) Choi Yoon-Hyeong (Department of Preventive Medicine Gachon University College of Medicine Incheon Korea.) Ko Kwang-Pil (Department of Preventive Medicine Gachon University College of Medicine Incheon Korea.) Im Jeong-Soo (Department of Preventive Medicine Gachon University College of Medicine Incheon Korea.) 정재훈 (가천대학교)
저널정보
대한의학회 Journal of Korean Medical Science Journal of Korean Medical Science Vol.35 No.25
발행연도
2020.1
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1 - 15 (15page)

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Background: The coronavirus disease 2019 (COVID-19) pandemic is an emerging threat worldwide. It remains unclear how comorbidities affect the risk of infection and severity of COVID-19. Methods: This is a nationwide retrospective case-control study of 219,961 individuals, aged 18 years or older, whose medical costs for COVID-19 testing were claimed until May 15, 2020. COVID-19 diagnosis and infection severity were identified from reimbursement data using diagnosis codes and on the basis of respiratory support use, respectively. Odds ratios (ORs) were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. Results: The COVID-19 group (7,341 of 219,961) was young and had a high proportion of female. Overall, 13.0% (954 of 7,341) of the cases were severe. The severe COVID-19 group had older patients and a proportion of male ratio than did the non-severe group. Diabetes (odds ratio range [ORR], 1.206–1.254), osteoporosis (ORR, 1.128–1.157), rheumatoid arthritis (ORR, 1.207–1.244), substance use (ORR, 1.321–1.381), and schizophrenia (ORR, 1.614–1.721) showed significant association with COVID-19. In terms of severity, diabetes (OR, 1.247; 95% confidential interval, 1.009–1.543), hypertension (ORR, 1.245–1.317), chronic lower respiratory disease (ORR, 1.216–1.233), chronic renal failure, and end-stage renal disease (ORR, 2.052–2.178) were associated with severe COVID-19. Conclusion: We identified several comorbidities associated with COVID-19. Health care workers should be more careful while diagnosing and treating COVID-19 when patients have the abovementioned comorbidities.
#COVID-19 #SARS-CoV-2 #Comorbidity #Risk Factor #Severity

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참고문헌 (23)

참고문헌 신청
World Health Organization / Coronavirus disease 2019 (COVID-19) situation report google schola Emami A / 2020 / Prevalence of underlying diseases in hospitalized patients with COVID-19 : a systematic review and meta-analysis / Arch Acad Emerg Med 8(1):e35 google schola Yang J / 2020 / Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2 : a systematic review and meta-analysis / Int J Infect Dis 94:91~95 google schola Guan WJ / 2020 / Comorbidity and its impact on 1590patients with COVID-19 in China : a nationwide analysis / Eur Respir J 55(5):2000547 google schola Li X / 2020 / Risk factors for severity and mortality in adult COVID-19inpatients in Wuhan / J Allergy Clin Immunol Crossref

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