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    COVID-19 Resource Center
    Critical Review: Preliminary indicators of mortality in subjects infected with COVID-19 based on data from China and South Korea
    Last Updated: 3/25/20
    Free CMEs

    This article was published in collaboration with TheNNT.com.

    An odds ratio (OR) is a comparison of the odds of an event or outcome in those with a particular risk factor, versus the odds of that outcome or event in those without that particular risk factor. OR is a useful way to estimate how the presence of a risk factor increases the likelihood of an event. For example, age ≥60 years can significantly increase the risk of mortality in patients with community-acquired pneumonia (CAP).1

    Figure 1.

    Many practicing clinicians have developed a gestalt of prognostic indicators based on experience or are familiar with scores to help prognosticate outcomes for patients with CAP. As a point of reference the ORs for CAP and COVID-19 (Table 1) are shown together in order to help clinicians put into context different risk factors with magnitudes higher ORs and similar ORs when making clinical decisions for patients with the novel coronavirus.

    Table 1: Risk factors associated with mortality in subjects infected with CAP and COVID-19
    Odds Ratio and 95%CI
    Factor CAP1 COVID-192,3
    Chinese Cohort
    COVID-196
    S Korea CDC Cohort
    Age ≥60 5.2 (3.9 - 6.8) 9.9 (8.5 - 11.7) 30.7 (14.7 - 64)
    Male gender 1.7 (1.3 - 2.2) 1.7 (1.5 - 1.9) 2.0 (1.2 - 3.1)
    Hypertension - 3.3 (2.8 - 4.0)
    Cardiovascular disease 2.6 (1.9 - 3.5) 5.9 (4.6 - 7.5)
    Diabetes 2.1 (1.4 - 3.1) 3.5 (2.8 - 4.6)
    Chronic lung disease 1.5 (1.1 - 2.0) 2.8 (1.9 - 4.1)
    Cancer 3.2 (2.3 - 4.4) 2.4 (1.1 - 5.6)
    In South Korea CDC Dataset,6 the odds ratio for death in age group ≥60 is 30.7 (95% CI, 14.7 – 64) and the odds ratio for death in male gender is 1.95 (95% CI, 1.23 – 3.07). South Korea has very robust testing, in which case fatality rates were significantly lower across all age groups as compared with the Chinese data, but even more so in patients less than 60 - where there seems to be many positive patients with mild symptoms.

    Figure 2.


    To be clear, these figures do NOT compare the absolute mortality rate between CAP and COVID-19 patients with pneumonia. It is also important to note that the data presented here are mainly from the first cohort of COVID-19 patients from China.2-3 Therefore, this information may not be generalizable to other populations, and is also limited in that it only includes those patients who were tested. Lastly, the characteristics of patients and the behavior of the disease is constantly evolving. Therefore, we emphasize on the “preliminary” nature of the information provided here.


    Of note, the prevalence of Diabetes (DM) and cardiovascular disease (CVD) in the cohort of patients reported by the Chinese CDC are notably lower than in U.S. populations, ~2.5% vs. 10.5% (all ages, 13% US adults) and ~2.0% vs. 12.1% (adults with diagnosed heart disease) respectively.2-5 This could be in part due to missing information. If so it could also indicate that patients with DM and/or CVD in this dataset are generally sicker than the average patient with DM and/or CVD in the U.S., which would inflate the OR.


    Figure 3.


    In addition, we have listed the prognostic value of some of the lab abnormalities reported in various datasets (Table 2). We encourage the readers to interpret these results with caution as the numbers are derived from datasets in a retrospective manner with a significant percentage of missing data. Therefore, at best, they are suggestive of poor outcomes and their prognostic value has to be validated properly in future studies that are prospective with improved methodology. In addition, most of the ORs have very wide confidence intervals (most likely due to small sample sizes), which further limits the validity of the data. While the original Chinese cohort includes over 44,000 patients, some of the lab values are based on studies of less than 200 patients.

    Table 2. Laboratory Values associated with mortality
    Laboratory Value Odds ratio and 95% CI
    Lymphocyte count <0.8 (x 10*9 / L) 8.8 (4.3 - 18.4)7
    Bilateral consolidations on imaging 1.98 (0.89 - 4.5)8*
    Ground Glass Opacities on imaging 2.1 (0.99 - 4.7)8*
    D-Dimer > 1ug/L** 14 (6.3 - 31)3
    Elevated C-Reactive Protein** 10.5 (1.2 - 34.7)7
    LDH > 245 u/L** 45.4 (6.0 - 338)7
    * Not statistically significant
    ** Limited validity due to wide confidence intervals and small sample sizes

    Examining the existing data highlights the importance of age as the most important prognostic factor. Therefore, we have listed the fatality rates from COVID-19 based on age groups in Table 3. The data indicates more than a triple-fold increase in mortality from COVID-19 infection in patients in age group 60-69 years compared to those aged 50-59 years. The mortality continues to rise significantly in persons aged 70 years and above.

    Table 3. Fatality rate in different age groups derived from Chinese CDC2 and South Korea CDC6 datasets
    Chinese CDC dataset2 South Korea CDC dataset6
    Age group Deaths/confirmed cases Fatality rate Deaths/confirmed cases Fatality rate
    0-9 0/416 0% 0/83 0%
    10-19 1/549 0.2% 0/427 0%
    20-29 7/3619 0.2% 0/2301 0%
    30-39 18/7600 0.2% 1/842 0.12%
    40-49 38/8571 0.4% 1/1141 0.09%
    50-59 130/10008 1.3% 6/1568 0.38%
    60-69 309/8583 3.6% 14/1012 1.38%
    70-79 312/3918 8% 28/525 5.33%
    ≥80 208/1408 14.8% 25/263 9.51%

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    About the Authors
    Shahriar Zehtabchi, MD

    Shahriar Zehtabchi, MD

    Editor-in-Chief, TheNNT.com 
     Professor and Vice Chair of Academic Affairs 
     Department of Emergency Medicine 
     SUNY Downstate Health Sciences University
    Joe Habboushe, MD, MBA

    Joe Habboushe, MD, MBA

    Co-Founder and CEO, MDCalc 
     Associate Professor 
     Department of Emergency Medicine 
     NYU Langone Health
    Peer Reviewed By
    Cassidy Dahn, MD

    Cassidy Dahn, MD

    Clinical Assistant Professor 
     Department of Emergency Medicine 
     NYU Langone Health
    Kyan Askari, MD

    Kyan Askari, MD

    Departments of Critical Care and Emergency Medicine 
     Mount Sinai Medical Center (Miami, FL)
    References
    Mortensen EM, Coley CM, Singer DE, Marrie TJ, Obrosky DS, Kapoor WN, Fine MJ. Causes of death for patients with community-acquired pneumonia: results from the Pneumonia Patient Outcomes Research Team cohort study. Arch Intern Med. 2002 May 13;162(9):1059-64
    Chinese CDC. Available at: http://weekly.chinacdc.cn/en/article/id/e53946e2-c6c4-41e9-9a9b-fea8db1a8f51
    Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020. pii: S0140-6736(20)30566-3
    US CDC. Available at: https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf
    US CDC. Available at: https://www.cdc.gov/heartdisease/facts.htm
    Korean CDC. Available at: https://www.cdc.go.kr/board/board.es?mid=a30402000000&bid=0030
    Liu W, Tao ZW, Lei W, et al.. Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J (Engl). 2020. doi: 10.1097/CM9.0000000000000775. [Epub ahead of print]
    Guan WJ, Ni ZY, Hu Y, et al; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020. doi: 10.1056/NEJMoa2002032.
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