본문 바로가기
KERD
논문KCI 등재

The anatomy of COVID-19 comorbidity networks among hospitalized Korean patients

1

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

OBJECTIVES: We aimed to examine how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19).METHODS: Data were provided by the National Medical Center of the Korea Disease Control and Prevention Agency. These data included the clinical and epidemiological information of all patients hospitalized with COVID-19 who were discharged on or before April 30, 2020 in Korea. We conducted comorbidity network and multinomial logistic regression analyses to identify risk factors associated with COVID-19 disease severity and mortality. The outcome variable was the clinical severity score (CSS), categorized as mild (oxygen treatment not needed), severe (oxygen treatment needed), or death.RESULTS: In total, 5,771 patients were included. In the fully adjusted model, chronic kidney disease (CKD) (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.19 to 5.61) and chronic obstructive pulmonary disease (COPD) (OR, 3.19; 95% CI, 1.35 to 7.52) were significantly associated with disease severity. CKD (OR, 5.35; 95% CI, 2.00 to 14.31), heart failure (HF) (OR, 3.15; 95% CI, 1.22 to 8.15), malignancy (OR, 3.38; 95% CI, 1.59 to 7.17), dementia (OR, 2.62; 95% CI, 1.45 to 4.72), and diabetes mellitus (OR, 2.26; 95% CI, 1.46 to 3.49) were associated with an increased risk of death. Asthma and hypertension showed statistically insignificant associations with an increased risk of death.CONCLUSIONS: Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly CKD, COPD, and HF.

Abstract

OBJECTIVES: We aimed to examine how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19).METHODS: Data were provided by the National Medical Center of the Korea Disease Control and Prevention Agency. These data included the clinical and epidemiological information of all patients hospitalized with COVID-19 who were discharged on or before April 30, 2020 in Korea. We conducted comorbidity network and multinomial logistic regression analyses to identify risk factors associated with COVID-19 disease severity and mortality. The outcome variable was the clinical severity score (CSS), categorized as mild (oxygen treatment not needed), severe (oxygen treatment needed), or death.RESULTS: In total, 5,771 patients were included. In the fully adjusted model, chronic kidney disease (CKD) (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.19 to 5.61) and chronic obstructive pulmonary disease (COPD) (OR, 3.19; 95% CI, 1.35 to 7.52) were significantly associated with disease severity. CKD (OR, 5.35; 95% CI, 2.00 to 14.31), heart failure (HF) (OR, 3.15; 95% CI, 1.22 to 8.15), malignancy (OR, 3.38; 95% CI, 1.59 to 7.17), dementia (OR, 2.62; 95% CI, 1.45 to 4.72), and diabetes mellitus (OR, 2.26; 95% CI, 1.46 to 3.49) were associated with an increased risk of death. Asthma and hypertension showed statistically insignificant associations with an increased risk of death.CONCLUSIONS: Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly CKD, COPD, and HF.

참고문헌 (37)

  1. Paules CI, "Coronavirus infections-more than just the common cold", JAMA, 323, pp.707~708 (2020)
  2. Fauci AS, "Covid-19-navigating the uncharted", N Engl J Med, 382, pp.1268~1269 (2020)
  3. "Estimating mortality from COVID-19" (2020)[URL]
  4. "Coronavirus disease (COVID-19) weekly epidemiological update and weekly operational update"[URL]
  5. Wang X, "Comorbid chronic diseases and acute organ injuries are strongly correlated with disease severity and mortality among COVID-19 patients: a systemic review and meta-analysis", Research(Wash D C), 2020, pp.2402961~ (2020)
  6. Wadhera RK, "Variation in COVID-19 hospitalizations and deaths across New York City boroughs", JAMA, 323, pp.2192~2195 (2020)
  7. Richardson S, "Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19in the New York City area", JAMA, 323, pp.2052~2059 (2020)
  8. Livingston E, "Coronavirus disease 2019(COVID-19)in Italy", JAMA, 323, pp.1335~ (2020)
  9. Kashnitsky I, "COVID-19 in unequally ageing European regions", World Dev, 136, pp.105170~ (2020)
  10. Wang H, "Risk of COVID-19 for patients with cancer", Lancet Oncol, 21, pp.e181~ (2020)
  11. Ji Y, "Potential association between COVID-19 mortality and health-care resource availability", Lancet Glob Health, 8, pp.e480~ (2020)
  12. Wu C, "Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China", JAMA Intern Med, 180, pp.934~943 (2020)
  13. Zhou F, "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China : a retrospective cohort study", Lancet, 395, pp.1054~1062 (2020)
  14. Wu Z, "Characteristics of and important lessons from the coronavirus disease 2019(COVID-19)outbreak in China : summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention", JAMA, 323, pp.1239~1242 (2020)
  15. Guan WJ, "Comorbidity and its impact on 1590 patients with COVID-19 in China : a nationwide analysis", Eur Respir J, 55, pp.2000547~ (2020)
  16. Cramer AO, "Comorbidity : a network perspective", Behav Brain Sci, 33, pp.137~150 (2010)
  17. Lee DS, "The implications of human metabolic network topology for disease comorbidity", Proc Natl Acad Sci U S A, 105, pp.9880~9885 (2008)
  18. Yang J, "Prevalence of comorbidities in the novel Wuhan coronavirus(COVID-19)infection : a systematic review and meta-analysis", Int J Infect Dis, 94, pp.91~95 (2020)
  19. Sanyaolu A, "Comorbidity and its impact on patients with COVID-19", SN Compr Clin Med, pp.1~8 (2020)
  20. Zhu L, "Association of blood glucose control and outcomes in patients with COVID19 and pre-existing type 2 diabetes", Cell Metab, 31, pp.1068~1077 (2020)
  21. Atkins JL, "Preexisting comorbidities predicting COVID-19 and mortality in the UK biobank community cohort", J Gerontol A Biol Sci Med Sci, 75, pp.2224~2230 (2020)
  22. Ji Wonjun, "Effect of Underlying Comorbidities on the Infection and Severity of COVID-19 in Korea: a Nationwide Case-Control Study", Journal of Korean Medical Science, 35(25), pp.1~15 (2020), 대한의학회[DOI]
  23. Targher G, "Patients with diabetes are at higher risk for severe illness from COVID-19", Diabetes Metab, 46, pp.335~337 (2020)
  24. Singh AK, "Diabetes in COVID-19 : prevalence, pathophysiology, prognosis and practical considerations", Diabetes Metab Syndr, 14, pp.303~310 (2020)
  25. Singh AK, "Comorbidities in COVID-19 : outcomes in hypertensive cohort and controversies with renin angiotensin system blockers", Diabetes Metab Syndr, 14, pp.283~287 (2020)
  26. Liang W, "Cancer patients in SARS-CoV-2 infection : a nationwide analysis in China", Lancet Oncol, 21, pp.335~337 (2020)
  27. Schiffrin EL, "Hypertension and COVID-19", Am J Hypertens, 33, pp.373~374 (2020)
  28. Jordan RE, "Covid-19: risk factors for severe disease and death", BMJ, 368, pp.m1198~ (2020)
  29. Shahid Z, "COVID-19 and older adults : what we know", J Am Geriatr Soc, 68, pp.926~929 (2020)
  30. Shin EK, "Applied network science for relational chronic disease surveillance", Stud Health Technol Inform, 262, pp.336~339 (2019)
  31. Borgatti SP, "Network analysis of 2-mode data", Soc Networks, 19, pp.243~269 (1997)
  32. Soper HE, "On the distribution of the correlation coefficient in small samples. Appendix II to the papers of"Student"and RA Fisher", Biometrika, 11, pp.328~413 (1917)
  33. Hilbe JM, "Logistic regression models", pp.385~398 (2009), CRC Press
  34. Hosmer DW, "Applied logistic regression", pp.369~311 (2013), John Wiley & Sons
  35. Agresti A, "Categorical data analysis", pp.267~282 (2003), John Wiley &Sons
  36. Dietz W, "Obesity and its implications for COVID-19 mortality", Obesity(Silver Spring), 28, pp.1005~ (2020)
  37. Shin EK, "Geo-clustered chronic affinity : pathways from socio-economic disadvantages to health disparities", JAMIA Open, 2, pp.317~322 (2019)

관련 논문AI추천

Comparison of Comorbidities in Relation to Critical Conditions among Coronavirus Disease 2019 Patients: A Network Meta-AnalysisHoang Tung, Tran Thi Anh Tho대한감염학회 · Infection and Chemotherapy2021 · 제53권 제1호Predictors of Mortality in Patients with COVID-19: A Systematic Review and Meta-analysis김우림, 이경은, 한지민한국임상약학회 · 한국임상약학회지2020 · 제30권 제3호New Scoring System for Predicting Mortality in Patients with COVID-19권기태, 김신우, 김윤정, 배소현, 장현하, 황소윤연세대학교의과대학 · Yonsei Medical Journal2021 · 제62권 제9호한국 코로나바이러스감염증-19 환자 5,628명의 역학적, 임상적 특성: 전국단위 다기관 관찰 연구문성용, 연동건, 이승원대한 소아알레르기 호흡기학회 · Allergy Asthma & Respiratory Disease2021 · 제9권 제3호Analysis of Risk Factors for Severe Acute Respiratory Infection and Pneumonia and among Adult Patients with Acute Respiratory Illness during 2011-2014 Influenza Seasons in Korea강성희, 김신우, 김영근, 김우주, 노지윤, 박경화, 서유빈, 송준영, 위성헌, 이선희, 이재갑, 이진수, 전지호, 정은주, 정혜원, 정희진, 최민주, 최원석대한감염학회 · Infection and Chemotherapy2016 · 제48권 제4호Should all patients with hypertension be worried about developing severe coronavirus disease 2019 (COVID-19)?Alvanegh Akbar Ghorbani, Ataee Mohammad Reza, Bagheri Mehdi, Bahardoust Mansour, Goharrizi Mohammad Ali Sheikh Beig, Heiat Mohammad, Navidiyan Ensiyeh Shabani, Zijoud Seyed Reza Hosseini대한고혈압학회 · Clinical Hypertension2021 · 제27권 제2호

이 간행물의 다른 논문 (102건)