Validation and repurposing of the MSL-COVID-19 score for prediction of severe COVID-19 using simple clinical predictors in a triage setting: The Nutri-CoV score.
PLoS One
; 15(12): e0244051, 2020.
Article
em En
| MEDLINE
| ID: mdl-33326502
ABSTRACT
BACKGROUND:
During the COVID-19 pandemic, risk stratification has been used to decide patient eligibility for inpatient, critical and domiciliary care. Here, we sought to validate the MSL-COVID-19 score, originally developed to predict COVID-19 mortality in Mexicans. Also, an adaptation of the formula is proposed for the prediction of COVID-19 severity in a triage setting (Nutri-CoV).METHODS:
We included patients evaluated from March 16th to August 17th, 2020 at the Instituto Nacional de Ciencias Médicas y Nutrición, defining severe COVID-19 as a composite of death, ICU admission or requirement for intubation (n = 3,007). We validated MSL-COVID-19 for prediction of mortality and severe disease. Using Elastic Net Cox regression, we trained (n = 1,831) and validated (n = 1,176) a model for prediction of severe COVID-19 using MSL-COVID-19 along with clinical assessments obtained at a triage setting.RESULTS:
The variables included in MSL-COVID-19 are pneumonia, early onset type 2 diabetes, age > 65 years, chronic kidney disease, any form of immunosuppression, COPD, obesity, diabetes, and age <40 years. MSL-COVID-19 had good performance to predict COVID-19 mortality (c-statistic = 0.722, 95%CI 0.690-0.753) and severity (c-statistic = 0.777, 95%CI 0.753-0.801). The Nutri-CoV score includes the MSL-COVID-19 plus respiratory rate, and pulse oximetry. This tool had better performance in both training (c-statistic = 0.797, 95%CI 0.765-0.826) and validation cohorts (c-statistic = 0.772, 95%CI 0.0.745-0.800) compared to other severity scores.CONCLUSIONS:
MSL-COVID-19 predicts inpatient COVID-19 lethality. The Nutri-CoV score is an adaptation of MSL-COVID-19 to be used in a triage environment. Both scores have been deployed as web-based tools for clinical use in a triage setting.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Índice de Gravidade de Doença
/
COVID-19
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
Limite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article