Development of a brief scoring system to predict any-cause mortality in patients hospitalized with COVID-19 infection.
PLoS One
; 16(7): e0254580, 2021.
Artículo
en Inglés
| MEDLINE | ID: covidwho-1315888
ABSTRACT
Patients hospitalized with COVID-19 infection are at a high general risk for in-hospital mortality. A simple and easy-to-use model for predicting mortality based on data readily available to clinicians in the first 24 hours of hospital admission might be useful in directing scarce medical and personnel resources toward those patients at greater risk of dying. With this goal in mind, we evaluated factors predictive of in-hospital mortality in a random sample of 100 patients (derivation cohort) hospitalized for COVID-19 at our institution in April and May, 2020 and created potential models to test in a second random sample of 148 patients (validation cohort) hospitalized for the same disease over the same time period in the same institution. Two models (Model A two variables, presence of pneumonia and ischemia); (Model B three variables, age > 65 years, supplemental oxygen ≥ 4 L/min, and C-reactive protein (CRP) > 10 mg/L) were selected and tested in the validation cohort. Model B appeared the better of the two, with an AUC in receiver operating characteristic curve analysis of 0.74 versus 0.65 in Model A, but the AUC differences were not significant (p = 0.24. Model B also appeared to have a more robust separation of mortality between the lowest (none of the three variables present) and highest (all three variables present) scores at 0% and 71%, respectively. These brief scoring systems may prove to be useful to clinicians in assigning mortality risk in hospitalized patients.
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
COVID-19
Tipo de estudio:
Estudio de cohorte
/
Estudio experimental
/
Estudio observacional
/
Estudio pronóstico
/
Ensayo controlado aleatorizado
Límite:
Adulto
/
Anciano
/
Femenino
/
Humanos
/
Masculino
/
Middle aged
Idioma:
Inglés
Revista:
PLoS One
Asunto de la revista:
Ciencia
/
Medicina
Año:
2021
Tipo del documento:
Artículo
País de afiliación:
Journal.pone.0254580
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