A nomogram to predict the risk of unfavourable outcome in COVID-19: a retrospective cohort of 279 hospitalized patients in Paris area
Creators: name: Nguyen, Yann
name: Corre, Félix
name: Honsel, Vasco
name: Curac, Sonja
name: Zarrouk, Virginie
name: Burtz, Catherine Paugam
name: Weiss, Emmanuel
name: Moyer, Jean-Denis
name: Gauss, Tobias
name: Grégory, Jules
name: Bert, Frédéric
name: Trichet, Catherine
name: Peoc’h, Katell
name: Vilgrain, Valérie
name: Rebours, Vinciane
name: Fantin, Bruno
name: Galy, Adrien
Publisher: name: Taylor & Francis
Year: 2020
Subjects: subject: Medicine
subject: Biotechnology
subject: Mathematical Sciences not elsewhere classified
subject: Developmental Biology
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology
subject: Computational Biology

description: To identify predictive factors of unfavourable outcome among patients hospitalized for COVID-19. We conducted a monocentric retrospective cohort study of COVID-19 patients hospitalized in Paris area. An unfavourable outcome was defined as the need for artificial ventilation and/or death. Characteristics at admission were analysed to identify factors predictive of unfavourable outcome using multivariable Cox proportional hazard models. Based on the results, a nomogram to predict 14-day probability of poor outcome was proposed. Between March 15th and April 14th, 2020, 279 COVID-19 patients were hospitalized after a median of 7 days after the first symptoms. Among them, 88 (31.5%) patients had an unfavourable outcome: 48 were admitted to the ICU for artificial ventilation, and 40 patients died without being admitted to ICU. Multivariable analyses retained age, overweight, polypnoea, fever, high C-reactive protein, elevated us troponin-I, and lymphopenia as risk factors of an unfavourable outcome. A nomogram was established with sufficient discriminatory power (C-index 0.75), and proper consistence between the prediction and the observation. We identified seven easily available prognostic factors and proposed a simple nomogram for early detection of patients at risk of aggravation, in order to optimize clinical care and initiate specific therapies.KEY MESSAGESSince novel coronavirus disease 2019 pandemic, a minority of patients develops severe respiratory distress syndrome, leading to death despite intensive care. Tools to identify patients at risk in European populations are lacking.In our series, age, respiratory rate, overweight, temperature, C-reactive protein, troponin and lymphocyte counts were risk factors of an unfavourable outcome in hospitalized adult patients.We propose an easy-to-use nomogram to predict unfavourable outcome for hospitalized adult patients to optimize clinical care and initiate specific therapies. Since novel coronavirus disease 2019 pandemic, a minority of patients develops severe respiratory distress syndrome, leading to death despite intensive care. Tools to identify patients at risk in European populations are lacking. In our series, age, respiratory rate, overweight, temperature, C-reactive protein, troponin and lymphocyte counts were risk factors of an unfavourable outcome in hospitalized adult patients. We propose an easy-to-use nomogram to predict unfavourable outcome for hospitalized adult patients to optimize clinical care and initiate specific therapies.