| Category |
Medical Informatics |
| Manuscript Type |
Observational Study |
| Article Title |
Validated tool for early prediction of intensive care unit admission in COVID-19 patients
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Hao-Fan Huang, Yong Liu, Jin-Xiu Li, Hui Dong, Shan Gao, Zheng-Yang Huang, Shou-Zhi Fu, Lu-Yu Yang, Hui-Zhi Lu, Liao-You Xia, Song Cao, Yi Gao and Xia-Xia Yu |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Shenzhen Municipal Government’s "Peacock Plan" |
KQTD2016053112051497 |
|
| Corresponding Author |
Xia-Xia Yu, PhD, Assistant Professor, School of Biomedical Engineering, Health Science Center, Shenzhen University, No. 3688 Nanhai Avenue, Shenzhen 518060, Guangdong Province, China. xiaxiayu@szu.edu.cn |
| Key Words |
COVID-19; Intensive care units; Machine learning; Prognostic predictive model; Risk stratification |
| Core Tip |
This study established a risk stratification tool for the early prediction of intensive care unit (ICU) admission among coronavirus disease 2019 (COVID-19) patients at hospital admission to enable such patients to receive immediate appropriate care, thus improving medical resource allocation. The model with 13 indicators selected from 65 laboratory results collected at hospital admission could be used to assess the risk of ICU admission. This study provided a simple probability prediction model to identify ICU admission risk in COVID-19 patients at admission. |
| Publish Date |
2021-09-28 10:00 |
| Citation |
Huang HF, Liu Y, Li JX, Dong H, Gao S, Huang ZY, Fu SZ, Yang LY, Lu HZ, Xia LY, Cao S, Gao Y, Yu XX. Validated tool for early prediction of intensive care unit admission in COVID-19 patients. World J Clin Cases 2021; 9(28): 8388-8403 |
| URL |
https://www.wjgnet.com/2307-8960/full/v9/i28/8388.htm |
| DOI |
https://dx.doi.org/10.12998/wjcc.v9.i28.8388 |
