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    COVID-19 Resource Center
    Critical Review: COVID-19 Calculators during Extreme Resource-Limited Situations
    PMID: 32259419
    Last Updated: 3/17/20
    Free CMEs
    Disclaimer
    This review is based on incomplete data and reviews. Some newer calculators have not yet been externally validated. This review may become outdated as we learn more.

    Calculators should never replace clinical judgment.
    Learn More about COVID-19 Calcs

    SARS-CoV-2, also known as the Novel Coronavirus, was first reported in China in December 2019 as the pathogen behind the pattern of severe infectious pneumonias that were particularly fatal in the elderly. By January of 2020, it was declared a global public health emergency.


    In the near future we may face scenarios in which we do not have enough resources (ventilators, ECMOs, etc) for the number of critically sick COVID patients. We may not have enough healthcare workers, as COVID-19 positive or exposed healthcare workers need to be quarantined. During these worst-case-scenarios, new crisis standards of care and thresholds for ICU admissions will be needed. Clinical decision scores may support the clinician’s decision making - especially if properly adapted for this unique pandemic and for the patient being treated.


    In this review, we aim to discuss clinical prediction scores for pneumonia severity to examine which ones may provide value in this unique situation – across three main decision points. Initial data from a cohort of over 44,000 Chinese COVID patients, including risk factors for mortality, were compared with that of cohorts used to study the clinical scores in order to estimate potential appropriateness of each score and how to best adjust results at the bedside. For example, age over 60 is a risk factor for mortality in bacterial pneumonia (OR 5.2), but a considerably stronger one in COVID patients (OR 9.9-32). Other risk factors seem to also confer even higher risk in COVID patients than in normal bacterial pneumonia patients, including cardiovascular disease, diabetes, and lung disease. Low lymphocyte counts are also correlated with higher mortality, also at a surprisingly large amount.1-3


    Table 1: Risk factors associated with mortality in subjects infected with COVID-19
    Odds Ratio (95% CI) for Mortality
    Factor CAP COVID-19
    Chinese Cohort1-2
    COVID-19
    S Korea CDC Cohort4
    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)
    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) -
    Lymphocyte count <0.8 (x 10*9 / L) - 8.8 -
    Bilateral consolidations on imaging - 1.98† -
    Ground Glass Opacities on imaging - 2.1† -
    * In the 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.
    Not statistically significant.

    There’s also evidence, based on a much smaller cohort of 191 patients, that a SOFA >5 (OR 5.5, 2.6 - 12.2, p<0.0001) and D-dimer >1,000 on admission (OR 18, 2.6 - 128.6, p<0.0001) confer significant mortality risk in COVID patients.1 In addition, procalcitonin levels have been found to be normal or even low – if found to be high, it may suggest a bacterial coinfection necessitating antibiotics; while CRP levels have been found to be higher in worsening disease and may provide prognostic value.5-6


    Continue Reading
    Discharge or Admit?
    ICU, Ventilator, Vasopressors?
    ECMO?
    DECISION POINT #1: Discharge or Admit?
    PSI/PORT
    May be more accurate, adjust for elderly
    MuLBSTA
    Designed for viral pneumonia, not externally validated, use clinical judgment
    CURB-65
    May be useful, consider others first
    PSI/PORT may add value; consider the new MuLBSTA score; adjust for elderly

    Each of these scores were designed to predict mortality and used to determine who can safely be sent home. A low risk CURB-65 score (0 or 1), confers a 0.6-2.7% risk of mortality.7 A low risk PSI/PORT score (<90) confers a 0.1-2.8% risk of mortality.8 Comparing the utility of the two, CURB-65 may not identify patients requiring ICU admission as well as the PSI. In addition, CURB-65 does not consider patients’ comorbidities (e.g. COPD), which may have a major impact on outcomes in COVID-19 patients. While CURB-65 is considerably faster to compute, with less inputs, this advantage matters less in the age of electronic records and resources. The PSI/PORT places a larger emphasis on age than CURB-65, assigning points by absolute age (i.e., a 70-year-old gets 70 points), which seems more consistent with what we know about COVID-19’s high mortality in the elderly.


    In both of these cohorts, community acquired pneumonia was generally defined as a combination of clinical (e.g. fever, cough, dyspnea, rales) and radiographic (e.g. infiltrate on CXR) findings in the absence of risk factors for healthcare. Neither the CURB-65 or PSI/PORT studies differentiated between viral and bacterial pathogens as a cause for the pneumonia, although the incidence of viral-associated CAP may be up to 29%, with rhinoviruses and influenza being the most common.9-10


    Recently, a clinical prediction tool was developed to risk-stratify patients specifically diagnosed with viral pneumonia - the MuLBSTA score.10 The aim of this was to predict clinical characteristics that affect mortality in patients with viral pneumonia. Interestingly, there are predictors of adverse outcomes that correlate with the clinical characteristics that are reported in COVID-19 patients. The presence of a multilobar infiltrate, low lymphocyte count, smoking history, and advanced age all were independent risk factors for mortality in this population - all relatively consistent with risk factors from our COVID cohort. But… before we get too excited, we must take note that this single-center, retrospective, not-externally-validated design may lead to bias and unknown applicability and generalizability.


    Main Takeaways:
    • Due to stronger emphasis on age and comorbidities, PSI/PORT may be a more accurate tool in disposition decision-making for COVID-19 patients, as age and underlying disease seem to be the major contributors to adverse patient-oriented outcomes.
    • The MuLBSTA score examines a patient population with similar characteristics to those with COVID-19 PNA. However, this single-center, retrospective study limits its applicability and reliability. We recommend its use as adjunct to clinical suspicion, but not in isolation.
    • All of these scores likely underestimate the importance of advanced age and of low lymphocytes.
    Learn More about COVID-19 Calcs

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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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