A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

Abstract

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.

Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study

“…We identified two protective factors against serious illness: vaccination status and prior history of COVID-19 infection. Many of the risk factors that were identified here, such as age, gender, socioeconomic status, and comorbidities, have also been identified in other models that have been developed [ 8 , 9 , 10 , 11 , 14 , 15 , 16 ]. In another HMO-based Israeli study, the number of doses was found to have a protective effect against hospitalization and mortality.…”

“…Israel et al also developed a scoring model including vaccination status. They already included four doses of vaccine [ 11 ] and evaluated similar variables as our study did. However, they only addressed the number of vaccines and not their timing and did not consider prior episodes of infection.…”

Expert Consensus: Main Risk Factors for Poor Prognosis in COVID-19 and the Implications for Targeted Measures against SARS-CoV-2

“…Rationale . Age is one of the main prognostic factors of a poor clinical outcome (hospitalization, need for intensive care or death) in patients infected with SARS-CoV-2, with a strong association with the age of 65 years and a maximum from the age of 70 years onwards, both in unvaccinated and vaccinated populations [ 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 ]. There is also a correlation between comorbidity and poorer clinical outcome, including mortality, at all ages, although particularly after 60 years of age.…”

“…There is also a correlation between comorbidity and poorer clinical outcome, including mortality, at all ages, although particularly after 60 years of age. The strength of this association increases with the number of comorbidities affecting the patient, with the association being highest for three or more pathological processes, both in unvaccinated and vaccinated subjects, including pediatric patients [ 9 , 40 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 ]. In nursing homes for older adults (NHOA), the factors associated with poorer clinical outcomes are age, health status and frailty [ 31 , 88 , 90 , 92 , 95 , 107 , 108 , 109 , 110 , 111 , 112 , 113 ].…”

“…Rationale. In addition to the negative effect that obesity has on its own, particularly when BMI is around 40 kg/m 2 , obesity is often associated with other comorbidities such as diabetes or cardiovascular disease, and has an impact on the prognosis of patients with SARS-CoV-2 infection, both in the unvaccinated and vaccinated population, including the pediatric setting [ 97 , 98 , 103 , 107 ]. Table 3 summarizes the final recommendations of the panel.…”