Development and Validation of a Multivariable Risk Prediction Model for COVID-19 Mortality in the Southern United States.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 34863394.
- Also identified by DOI 10.1016/j.mayocp.2021.09.002 and PMC identifier 8445799.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
To evaluate clinical characteristics of patients admitted to the hospital with coronavirus disease 2019 (COVID-19) in Southern United States and development as well as validation of a mortality risk prediction model. Southern Louisiana was an early hotspot during the pandemic, which provided a large collection of clinical data on inpatients with COVID-19. We designed a risk stratification model to assess the mortality risk for patients admitted to the hospital with COVID-19. Data from 1673 consecutive patients diagnosed with COVID-19 infection and hospitalized between March 1, 2020, and April 30, 2020, was used to create an 11-factor mortality risk model based on baseline comorbidity, organ injury, and laboratory results. The risk model was validated using a subsequent cohort of 2067 consecutive hospitalized patients admitted between June 1, 2020, and December 31, 2020. The resultant model has an area under the curve of 0.783 (95% CI, 0.76 to 0.81), with an optimal sensitivity of 0.74 and specificity of 0.69 for predicting mortality. Validation of this model in a subsequent cohort of 2067 consecutively hospitalized patients yielded comparable prognostic performance. We have developed an easy-to-use, robust model for systematically evaluating patients presenting to acute care settings with COVID-19 infection.
Medical subject headings
- COVID-19
- Hospitalization
- Proportional Hazards Models
- Risk Assessment