A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received
Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Microorganisms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-2607/10/6/1238 |
| _version_ | 1827658227555237888 |
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| author | Ariel Israel Alejandro A. Schäffer Eugene Merzon Ilan Green Eli Magen Avivit Golan-Cohen Shlomo Vinker Eytan Ruppin |
| author_facet | Ariel Israel Alejandro A. Schäffer Eugene Merzon Ilan Green Eli Magen Avivit Golan-Cohen Shlomo Vinker Eytan Ruppin |
| author_sort | Ariel Israel |
| collection | DOAJ |
| description | Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model’s performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online. |
| first_indexed | 2024-03-09T22:58:49Z |
| format | Article |
| id | doaj.art-24fb8deac1a6452c919f7c00219f8759 |
| institution | Directory Open Access Journal |
| issn | 2076-2607 |
| language | English |
| last_indexed | 2024-03-09T22:58:49Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Microorganisms |
| spelling | doaj.art-24fb8deac1a6452c919f7c00219f87592023-11-23T18:05:18ZengMDPI AGMicroorganisms2076-26072022-06-01106123810.3390/microorganisms10061238A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines ReceivedAriel Israel0Alejandro A. Schäffer1Eugene Merzon2Ilan Green3Eli Magen4Avivit Golan-Cohen5Shlomo Vinker6Eytan Ruppin7Leumit Health Services, Tel-Aviv 6473817, IsraelCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USALeumit Health Services, Tel-Aviv 6473817, IsraelLeumit Health Services, Tel-Aviv 6473817, IsraelLeumit Health Services, Tel-Aviv 6473817, IsraelLeumit Health Services, Tel-Aviv 6473817, IsraelLeumit Health Services, Tel-Aviv 6473817, IsraelCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USAVaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model’s performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.https://www.mdpi.com/2076-2607/10/6/1238COVID-19disease severitycalculatordiabetesobesitykidney disease |
| spellingShingle | Ariel Israel Alejandro A. Schäffer Eugene Merzon Ilan Green Eli Magen Avivit Golan-Cohen Shlomo Vinker Eytan Ruppin A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received Microorganisms COVID-19 disease severity calculator diabetes obesity kidney disease |
| title | A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received |
| title_full | A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received |
| title_fullStr | A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received |
| title_full_unstemmed | A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received |
| title_short | A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received |
| title_sort | calculator for covid 19 severity prediction based on patient risk factors and number of vaccines received |
| topic | COVID-19 disease severity calculator diabetes obesity kidney disease |
| url | https://www.mdpi.com/2076-2607/10/6/1238 |
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