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Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study
Miri Mizrahi Reuveni1, Jennifer Kertes1, Shirley Shapiro Ben David1,2
1Health Division, Maccabi Healthcare Services, Tel Aviv 6812509, Israel.
Biomedicines
|March 29, 2023
Summary
A new scoring tool accurately identifies COVID-19 patients at high risk for severe illness during the Omicron wave. This model aids in prioritizing care and antiviral treatment for vulnerable individuals.
Area of Science:
- Epidemiology
- Infectious Diseases
- Public Health
Background:
- Risk stratification models are crucial for identifying patients susceptible to severe COVID-19.
- The Omicron variant presented unique challenges for predicting severe illness outcomes.
Purpose of the Study:
- To develop and implement a scoring tool for identifying COVID-19 patients at risk of severe illness during the Omicron wave.
- To aid in prioritizing patient follow-up and treatment decisions.
Main Methods:
- Retrospective cohort study of 409,693 COVID-19 patients in Israel (Nov 2021 - Jan 2022).
- A predictive model for severe illness (hospitalization or death) was developed using one-third of the cohort and validated on the remaining two-thirds.
- Model performance was assessed using sensitivity, specificity, positive predictive value, and ROC analysis.
Main Results:
- The model achieved 88.7% accuracy in predicting severe COVID-19 illness.
- Key risk factors for severe disease included advanced age (>75), immunosuppression, and late-term pregnancy.
- Vaccination within six months and prior COVID-19 infection were associated with a reduced risk of severe illness.
Conclusions:
- The developed scoring tool effectively identifies high-risk COVID-19 patients during the Omicron wave.
- This model facilitates prioritized patient management, including closer medical follow-up and timely antiviral therapy selection.
- The tool is valuable for resource allocation and optimizing patient outcomes during widespread infection.
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