The COVEG score to predict severity and mortality among hospitalized patients with COVID-19

Mohamed El-Kassas1, Maha El Gaafary2, Mohamed Elbadry3

  • 1Endemic Medicine Department, Faculty of Medicine, Helwan University, Cairo, Egypt. m_elkassas@yahoo.com.

Insights

A new COVEG score accurately predicts COVID-19 severity and mortality in hospitalized patients. This tool aids in determining admission criteria and reducing patient deaths.

Area of Science:

  • Infectious Diseases
  • Clinical Medicine
  • Biostatistics

Background:

  • Predicting COVID-19 severity and mortality is crucial for effective patient management and resource allocation.
  • Identifying key clinical and laboratory features can inform admission criteria and improve outcomes for hospitalized patients.

Purpose of the Study:

  • To evaluate clinical-laboratory features of hospitalized COVID-19 patients.
  • To develop and validate a novel scoring system (COVEG score) for predicting COVID-19 severity and mortality.

Main Methods:

  • Retrospective cohort study of 1308 COVID-19 patients from five Egyptian university hospitals.
  • Analysis of demographics, comorbidities, clinical data, and laboratory parameters.
  • Development of the COVEG severity and mortality scores using regression analysis and ROC curves.

Main Results:

  • The study included 1308 patients (76.1% moderate, 23.9% severe COVID-19), with an overall mortality of 12.6%.
  • Key predictors for severity included age, D-dimer, serum ferritin, C-reactive protein, and neutrophil:lymphocyte ratio.
  • The COVEG severity score and COVEG mortality score demonstrated high predictive accuracy (AUC 0.882 and 0.883, respectively).

Conclusions:

  • The developed COVEG score accurately predicts both the severity and mortality of COVID-19 in hospitalized patients.
  • The COVEG score can be a valuable tool for clinical decision-making, potentially improving patient outcomes and reducing mortality.
Abstract

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