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Covidogram as a simple tool for predicting severe course of COVID-19: population-based study
Jiri Jarkovsky1,2, Klara Benesova1,2, Vladimir Cerny3,4
1Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
BMJ Open
|February 24, 2021
Summary
A new model, the "covidogram," helps identify patients at high risk for severe COVID-19. It uses age, sex, and chronic diseases to predict severe outcomes, aiding early intervention for better COVID-19 patient care.
Area of Science:
- Infectious Diseases
- Epidemiology
- Medical Informatics
Background:
- COVID-19 presents with a wide spectrum of disease severity.
- Early identification of high-risk patients is crucial for effective management.
- Predictive models can aid in stratifying patients for intensive care.
Purpose of the Study:
- To develop a prognostic model for predicting severe acute respiratory infection outcomes in COVID-19 patients.
- To identify key independent prognostic factors for severe COVID-19.
- To create a user-friendly tool for risk assessment.
Main Methods:
- A population-based study analyzing 7455 COVID-19 patients.
- Utilized reverse transcription-PCR for diagnosis.
- Developed a prediction model ('covidogram') based on independent prognostic factors.
Main Results:
- 6.2% of patients experienced a severe COVID-19 course.
- Independent negative prognostic factors included age, male sex, chronic kidney disease, COPD, cancer history, heart failure, diabetes, and PPI use for acid-related disorders.
- The model achieved an Area Under the ROC Curve (AUC) of 0.893.
Conclusions:
- The 'covidogram' is a simple, reliable tool for identifying patients at high risk of severe COVID-19.
- The model incorporates age, sex, and chronic diseases.
- Further research is needed on the role of acid-related disorders and PPIs as predictors.
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