Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.

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. T

SUBMITTER: Fan X 

PROVIDER: S-EPMC8011050 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature