Development and validation of an early warning score (EWAS) for predicting clinical deterioration in patients with coronavirus disease 2019

Background: Since the pandemic outbreak of coronavirus disease 2019 (COVID-19), the health system capacity in highly endemic areas has been overwhelmed. Approaches to efficient management are urgently needed. We aimed to develop and validate a score for early prediction of clinical deterioration of COVID-19 patients. Methods: In this retrospective multicenter cohort study, we included 1138 mild to moderate COVID-19 patients admitted to 33 hospitals in Guangdong Province from December 27, 2019 to March 4, 2020 (N =818; training cohort), as well as two hospitals in Hubei Province from January 21 to February 22, 2020 (N =320; validation cohort) in the analysis. Results: The 14-day cumulative incidences of clinical deterioration were 7.9% and 12.1% in the training and validation cohorts, respectively. An Early WArning Score (EWAS) (ranging from 0 to 4.5), comprising of age, underlying chronic disease, neutrophil to lymphocyte ratio, C-reactive protein, and D-dimer levels, was developed (AUROC: 0.857). By applying the EWAS, patients were categorized into low-, medium-, and high risk groups (cut-off values: two and three). The 14-day cumulative incidence of clinical deterioration in the low-risk group was 1.8%, which was significantly lower than the incidence rates in the medium- (14.4%) and high-risk (40.9%) groups (P <.001). The predictability of EWAS was similar in the validation cohort (AUROC =0.781), patients in the low-, medium-, and high-risk groups had 14-day cumulative incidences of 2.6%, 10.0%, and 25.7%, respectively (P <.001). Conclusion: The EWAS, which is based on five common parameters, can predict COVID-19-related clinical deterioration and may be a useful tool for a rapid triage and establishing a COVID-19 hierarchical management system that will greatly focus clinical management and medical resources to reduce mortality in highly endemic areas.

[1]  Shouzhi Fu,et al.  Clinical Features of Maintenance Hemodialysis Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. , 2020, Clinical journal of the American Society of Nephrology : CJASN.

[2]  C. Eastin,et al.  Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The Journal of Emergency Medicine.

[3]  Xin Zhou,et al.  Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China , 2020, The Journal of Emergency Medicine.

[4]  J. Xiang,et al.  Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study , 2020, The Lancet.

[5]  K. Yuen,et al.  Clinical Characteristics of Coronavirus Disease 2019 in China , 2020, The New England journal of medicine.

[6]  S. Zhang,et al.  Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series , 2020, BMJ.

[7]  Yan Zhao,et al.  Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. , 2020, JAMA.

[8]  Ting Yu,et al.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study , 2020, The Lancet.

[9]  Jing Zhao,et al.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.

[10]  Ralph S. Baric,et al.  Receptor Recognition by the Novel Coronavirus from Wuhan: an Analysis Based on Decade-Long Structural Studies of SARS Coronavirus , 2020, Journal of Virology.

[11]  Y. Hu,et al.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China , 2020, The Lancet.

[12]  J. Davidson,et al.  Cardiovascular complications of acute respiratory infections: current research and future directions , 2019, Expert review of anti-infective therapy.

[13]  Hai-hua Luo,et al.  Diagnostic value of blood parameters for community‐acquired pneumonia , 2018, International immunopharmacology.

[14]  S. Karakonstantis,et al.  Neutrophil to Lymphocyte Ratio As a Risk Stratification Tool for Older Adults with Pneumonia , 2018, Journal of the American Geriatrics Society.

[15]  X. Li,et al.  The vasoprotective axes of the renin‐angiotensin system: Physiological relevance and therapeutic implications in cardiovascular, hypertensive and kidney diseases , 2017, Pharmacological research.

[16]  A. Pulvirenti,et al.  Neutrophil‐To‐Lymphocyte Ratio: An Emerging Marker Predicting Prognosis in Elderly Adults with Community‐Acquired Pneumonia , 2017, Journal of the American Geriatrics Society.

[17]  E. Shin,et al.  Predictors of mortality in Middle East respiratory syndrome (MERS) , 2017, Thorax.

[18]  C. Ki,et al.  Predictive factors for pneumonia development and progression to respiratory failure in MERS-CoV infected patients , 2016, Journal of Infection.

[19]  M. Fine,et al.  Cardiac Complications in Patients With Community-Acquired Pneumonia: Incidence, Timing, Risk Factors, and Association With Short-Term Mortality , 2012, Circulation.

[20]  H. Yong,et al.  Clinical, laboratory and radiologic characteristics of 2009 pandemic influenza A/H1N1 pneumonia: primary influenza pneumonia versus concomitant/secondary bacterial pneumonia , 2011, Influenza and other respiratory viruses.

[21]  M. Niederman,et al.  Markers of treatment failure in hospitalised community acquired pneumonia , 2008, Thorax.

[22]  O. Tsang,et al.  Outcomes and Prognostic Factors in 267 Patients with Severe Acute Respiratory Syndrome in Hong Kong , 2003, Annals of Internal Medicine.