잠시만 기다려 주세요. 로딩중입니다.

Effect of Underlying Comorbidities on the Infection and Severity of COVID-19 in Korea: a Nationwide Case-Control Study

Journal of Korean Medical Science 2020년 35권 25호 p.237 ~ 237
지원준 ( Ji Won-Jun ) - University of Ulsan College of Medicine Asan Medical Center Department of Pulmonary and Critical Care Medicine

허경민 ( Huh Kyung-Min ) - Sungkyunkwan University School of Medicine Samsung Medical Center Department of Medicine
 ( Kang Min-Sun ) - Gachon University College of Medicine Gil Medical Center Artificial Intelligence and Big-Data Convergence Center
홍진욱 ( Hong Jin-Wook ) - Gachon University College of Medicine Gil Medical Center Artificial Intelligence and Big-Data Convergence Center
 ( Bae Gi-Hwan ) - Gachon University College of Medicine Gil Medical Center Artificial Intelligence and Big-Data Convergence Center
 ( Lee Ru-Gyeom ) - Gachon University College of Medicine Gil Medical Center Artificial Intelligence and Big-Data Convergence Center
나예원 ( Na Ye-Won ) - Gachon University College of Medicine Gil Medical Center Artificial Intelligence and Big-Data Convergence Center
최효선 ( Choi Hyo-Seon ) - Gachon University College of Medicine Department of Preventive Medicine
공선영 ( Gong Seon-Yeong ) - Gachon University College of Medicine Department of Preventive Medicine
최윤형 ( Choi Yoon-Hyeong ) - Gachon University College of Medicine Department of Preventive Medicine
고광필 ( Ko Kwang-Pil ) - Gachon University College of Medicine Department of Preventive Medicine
임정수 ( Im Jeong-Soo ) - Gachon University College of Medicine Department of Preventive Medicine
정재헌 ( Jung Jae-Hun ) - Gachon University College of Medicine Department of Preventive Medicine

Abstract


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.

키워드

COVID-19; SARS-CoV-2; Comorbidity; Risk Factor; Severity
원문 및 링크아웃 정보
  
등재저널 정보