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Mayo Clin Proc ; 96(12): 3030-3041, 2021 12.
Artículo en Inglés | MEDLINE | ID: mdl-34863394

RESUMEN

OBJECTIVE: 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. PATIENTS AND METHODS: 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. RESULTS: 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. CONCLUSION: We have developed an easy-to-use, robust model for systematically evaluating patients presenting to acute care settings with COVID-19 infection.


Asunto(s)
COVID-19 , Hospitalización/estadística & datos numéricos , Modelos de Riesgos Proporcionales , Medición de Riesgo/métodos , COVID-19/mortalidad , COVID-19/prevención & control , COVID-19/terapia , Técnicas de Laboratorio Clínico/métodos , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Comorbilidad , Modelos Epidemiológicos , Femenino , Mortalidad Hospitalaria , Humanos , Louisiana/epidemiología , Masculino , Persona de Mediana Edad , Puntuaciones en la Disfunción de Órganos , Pronóstico , Reproducibilidad de los Resultados , Factores de Riesgo , Índice de Severidad de la Enfermedad
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