Assessment of COVID-19 progression on day 5 from symptoms onset.
Elisa Gentilotti, Alessia Savoldi, Monica Compri, Anna Górska, Pasquale De Nardo, Alessandro Visentin, Giorgia Be, Elisa Razzaboni, Nicola Soriolo, Dario Meneghin, Domenico Girelli, Claudio Micheletto, Sara Mehrabi, Elda Righi, Evelina Tacconelli
Author Information
Elisa Gentilotti: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Alessia Savoldi: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Monica Compri: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Anna Górska: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Pasquale De Nardo: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy. pasquale.denardo@univr.it.
Alessandro Visentin: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Giorgia Be: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Elisa Razzaboni: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Nicola Soriolo: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Dario Meneghin: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Domenico Girelli: Department of Medicine, Section of Internal Medicine, University of Verona, EuroBloodNet Referral Center for Iron Metabolism Disorders, Azienda Ospedaliera Universitaria Integrata Verona, 37138, Verona, Italy.
Sara Mehrabi: Department of Radiology, University of Verona, Piazzale L.A. Scuro, 10, 37100, Verona, Italy.
Elda Righi: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
Evelina Tacconelli: Division of Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, P.le L.A. Scuro 10, 37134, Verona, Italy.
BACKGROUND: A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. METHODS: Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO/FiO ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. RESULTS: A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66-0.81) for predicting disease progression by day-11. CONCLUSION: An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians' decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.
