Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.

Journal: Frontiers in immunology

PMID: 39555074

Abstract

INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome coronavirus 2 is alarmingly high. This study aimed to explore the predictive value of a novel model for assessing the risk of death in this vulnerable cohort.

Authors

Linchao Zhu
Yimin Yao

Medical Laboratory, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

Keywords

Aged Aged, 80 and over Area Under Curve Bayes Theorem Biomarkers C-Reactive Protein China COVID-19 Female Humans Interleukin-6 Leukocyte Count Lymphocytes Machine Learning Male Monocytes Neutrophils Prediction Algorithms Predictive Value of Tests Regression Analysis SARS-CoV-2

External Resources

View on PubMed Access via DOI PubMed (39555074)

Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.

Abstract

Authors

Keywords

External Resources

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