Abstract:
OBJECTIVES:To appraise effective predictors for COVID-19 mortality in a retrospective cohort study. METHODS:A total of 1270 COVID-19 patients, including 984 admitted in Sino French New City Branch (training and internal validation sets randomly split at 7:3 ratio) and 286 admitted in Optical Valley Branch (external validation set) of Wuhan Tongji hospital, were included in this study. Forty-eight clinical and laboratory features were screened with LASSO method. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed death risk prediction model with simple-tree XGBoost model. Performances of models were evaluated by AUC, prediction accuracy, precision, and F1 scores. RESULTS:Six features, including disease severity, age, levels of high-sensitivity C-reactive protein (hs-CRP), lactate dehydrogenase (LDH), ferritin, and interleukin-10 (IL-10), were selected as predictors for COVID-19 mortality. Simple-tree XGBoost model conducted by these features can predict death risk accurately with >90% precision and >85% sensitivity, as well as F1 scores >0.90 in training and validation sets. CONCLUSION:We proposed the disease severity, age, serum levels of hs-CRP, LDH, ferritin, and IL-10 as significant predictors for death risk of COVID-19, which may help to identify the high-risk COVID-19 cases. KEY MESSAGES A machine learning method is used to build death risk model for COVID-19 patients. Disease severity, age, hs-CRP, LDH, ferritin, and IL-10 are death risk factors. These findings may help to identify the high-risk COVID-19 cases.
journal_name
Ann Medjournal_title
Annals of medicineauthors
Guan X,Zhang B,Fu M,Li M,Yuan X,Zhu Y,Peng J,Guo H,Lu Ydoi
10.1080/07853890.2020.1868564subject
Has Abstractpub_date
2021-12-01 00:00:00pages
257-266issue
1eissn
0785-3890issn
1365-2060journal_volume
53pub_type
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abstract::There are few relevant animal models for neurodegenerative diseases to be used for human drug development. Most current drugs for neurodegenerative diseases act through different neurotransmitter systems. Positron emission tomography (PET) is a unique tool in the study of neurodegenerative diseases as it enables quant...
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pub_type: 临床试验,杂志文章,评审
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pub_type: 杂志文章,多中心研究
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