Development of a risk score to identify patients at high risk for a severe course of COVID-19
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
AIM: We aimed to develop a risk score to calculate a person's individual risk for a severe COVID-19 course (POINTED score) to support prioritization of especially vulnerable patients for a (booster) vaccination.
SUBJECT AND METHODS: This cohort study was based on German claims data and included 623,363 individuals with a COVID-19 diagnosis in 2020. The outcome was COVID-19 related treatment in an intensive care unit, mechanical ventilation, or death after a COVID-19 infection. Data were split into a training and a test sample. Poisson regression models with robust standard errors including 35 predefined risk factors were calculated. Coefficients were rescaled with a min-max normalization to derive numeric score values between 0 and 20 for each risk factor. The scores' discriminatory ability was evaluated by calculating the area under the curve (AUC).
RESULTS: Besides age, down syndrome and hematologic cancer with therapy, immunosuppressive therapy, and other neurological conditions were the risk factors with the highest risk for a severe COVID-19 course. The AUC of the POINTED score was 0.889, indicating very good predictive validity.
CONCLUSION: The POINTED score is a valid tool to calculate a person's risk for a severe COVID-19 course.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10389-023-01884-7.
Details
Original language | English |
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Pages (from-to) | 1-10 |
Number of pages | 10 |
Journal | Journal of public health : from theory to practice |
Volume | 32 |
Issue number | 6 |
Publication status | E-pub ahead of print - 22 Mar 2023 |
Peer-reviewed | Yes |
External IDs
PubMedCentral | PMC10032626 |
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Scopus | 85150499345 |