Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.
Virol J
; 18(1): 67, 2021 03 31.
Artículo
en Inglés
| MEDLINE | ID: covidwho-1166917
ABSTRACT
BACKGROUND:
Risk scores are needed to predict the risk of death in severe coronavirus disease 2019 (COVID-19) patients in the context of rapid disease progression.METHODS:
Using data from China (training dataset, n = 96), prediction models were developed by logistic regression and then risk scores were established. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) was used for external validation.RESULTS:
A NSL model (area under the curve (AUC) 0.932) and a NL model (AUC 0.903) were developed based on neutrophil percentage and lactate dehydrogenase with and without oxygen saturation (SaO2) using the training dataset. AUCs of the NSL and NL models in the test dataset were 0.910 and 0.871, respectively. The risk scoring systems corresponding to these two models were established. The AUCs of the NSL and NL scores in the training dataset were 0.928 and 0.901, respectively. At the optimal cut-off value of NSL score, the sensitivity and specificity were 94% and 82%, respectively. The sensitivity and specificity of NL score were 94% and 75%, respectively.CONCLUSIONS:
These scores may be used to predict the risk of death in severe COVID-19 patients and the NL score could be used in regions where patients' SaO2 cannot be tested.Palabras clave
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
Oxígeno
/
Mortalidad Hospitalaria
/
COVID-19
/
L-Lactato Deshidrogenasa
/
Modelos Teóricos
/
Neutrófilos
Tipo de estudio:
Estudios diagnósticos
/
Estudio observacional
/
Estudio pronóstico
/
Ensayo controlado aleatorizado
Límite:
Anciano
/
Femenino
/
Humanos
/
Masculino
/
Middle aged
País/Región como asunto:
Asia
Idioma:
Inglés
Revista:
Virol J
Asunto de la revista:
Virología
Año:
2021
Tipo del documento:
Artículo
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