Abstract
Introduction: Global shortages in the supply of SARS-CoV-2 vaccines have resulted in campaigns to first inoculate individuals at highest risk for death from COVID-19. Here, we develop a predictive model of COVID-19-related death using longitudinal clinical data from patients in metropolitan Detroit.
Methods: All individuals included in the analysis had a laboratory-confirmed SARS-CoV-2 infection. Thirty-six pre-existing conditions with a false discovery rate p<0.05 were combined with other demographic variables to develop a parsimonious prediction model using least absolute shrinkage and selection operator regression. The model was then prospectively validated in a separate set of individuals with confirmed COVID-19.
Results: The study population consisted of 15 502 individuals with laboratory-confirmed SARS-CoV-2. The main prediction model was developed using data from 11 635 individuals with 709 reported deaths (case fatality ratio 6.1%). The final prediction model consisted of 14 variables with 11 comorbidities. This model was then prospectively assessed among the remaining 3867 individuals (185 deaths; case fatality ratio 4.8%). When compared with using an age threshold of 65 years, the 14-variable model detected 6% more of the individuals who would die from COVID-19. However, below age 45 years and its risk equivalent, there was no benefit to using the prediction model over age alone.
Discussion: Using a prediction model, such as the one described here, may help identify individuals who would most benefit from COVID-19 inoculation, and thereby may produce more dramatic initial drops in deaths through targeted vaccination.
Keywords: COVID-19; viral infection.
【저자키워드】 COVID-19, viral infection, 【초록키워드】 SARS-CoV-2, viral infection, vaccination, SARS-COV-2 infection, Comorbidities, risk, SARS-CoV-2 vaccines, SARS-CoV-2 vaccine, Patient, death, age, threshold, case fatality ratio, Analysis, Predictive, false discovery rate, Detroit, study population, Clinical data, individual, help, laboratory-confirmed SARS-CoV-2 infection, Final, supply, COVID-19-related death, operator, laboratory-confirmed, variable, benefit, initial, highest, described, identify, develop, reported, condition, demographic variable, 【제목키워드】 vaccination, death, implication,