Year
Month

(Peer-Reviewed) Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study
XIONG Yi Bai 熊一白 ¹, TIAN Ya Xin 田亚欣 ¹, MA Yan 马艳 ¹, YANG Wei 杨伟 ¹, LIU Bin 刘斌 ¹, RUAN Lian Guo 阮连国 ², LU Cheng 吕诚 ¹, HUANG Lu Qi 黄璐琦 ³
¹ Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China
中国 北京 中国中医科学院中医临床基础医学研究所
² Department of Infectious Diseases, JinYinTan Hospital, Wuhan 430024, Hubei, China
中国 湖北 武汉 金银潭医院感染性疾病科
³ National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
中国 北京 中国中医科学院中药资源中心
Objective

Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies.

Methods

We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score.

Results

A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio (OR, 1.27; 95% CI, 1.15–1.39), albumin (OR, 0.76; 95% CI, 0.70–0.83), and chest computed tomography abnormalities (OR, 2.01; 95% CI, 1.41–2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667–0.8776).

Conclusion

This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.
Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study_1
Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study_2
Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study_3
Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study_4
  • Pixel-controlled programmable metasurface as phase-type spatial terahertz modulator
  • Guibin Li, Guanyi Li, Zehao He, Xinke Wang, Peter J. Klar, He Ma, Yan Zhang
  • Opto-Electronic Advances
  • 2026-09-15
  • Spatiotemporal beam stirring in a multicore fiber
  • Alena Y. Kolesnikova, Mikhail D. Gervaziev, Nikita V. Bochkarev, Denis S. Kharenko, Evgeniy V. Podivilov, Sergey A. Babin
  • Opto-Electronic Advances
  • 2026-09-15
  • Ultrafast all-optical modulation of wide-bandwidth pulses enabled by silicon-metasurfaces
  • Kaloyan Georgiev, Khosro Zangeneh Kamali, Anton A. Trifonov, Giulia Crotti, Lyuben Petrov, Stefan Georgiev, Hristo Iliev, Lei Xu, Unai Arregui Leon, Mohsen Rahmani, Giuseppe Della Valle, Ivan Buchvarov, Dragomir Neshev
  • Opto-Electronic Advances
  • 2026-09-15
  • Physics-informed neural fields enable blind aberration correction for partially coherent quantitative phase imaging
  • Shun Zhou, Xingyu Huang, Linpeng Lu, Habib Ullah, Kaiyu Du, Maciej Trusiak, Malgorzata Kujawinska, Yuzhen Zhang, Yao Fan, Qian Chen, Qinrong Zhang, Chao Zuo
  • Opto-Electronic Science
  • 2026-08-26
  • Programmable directional photonic spiking neuron based on a non-Hermitian silicon microresonator
  • Stefano Biasi, Bülent Aslan, Stefano Gretter, Davide Olivieri, Alessandro Foradori, Riccardo Franchi, Lorenzo Pavesi
  • Opto-Electronic Science
  • 2026-08-26
  • Mutual empowerment of artificial intelligence and metasurfaces: intelligent nanophotonics and optical intelligence
  • Yu Zhao, Zile Li, Yongquan Zeng, Shaohua Yu, Guoxing Zheng
  • Opto-Electronic Science
  • 2026-08-26
  • Heterogeneously integrated micro-ring with SnS₂ for dual-functional optical modulation and photodetection
  • Jinyi Du, Lidan Lu, Xu Zhang, Bofei Zhu, Wenbo Bo, Yingjie Xu, Guang Chen, Yanlin He, Guanghui Ren, Xiaoping Lou, Zheng You, Lianqing Zhu
  • Opto-Electronic Advances
  • 2026-08-25
  • Hardware-aware lightweight photonic spiking neural network for pattern classification
  • Shuiying Xiang, Yahui Zhang, Shangxuan Shi, Haowen Zhao, Dianzhuang Zheng, Xingxing Guo, Yanan Han, Ye Tian, Liyue Zhang, Yuechun Shi, Yue Hao
  • Opto-Electronic Advances
  • 2026-08-25
  • PhyspeNet: An empirical physics-aware network for adaptive speckle reconstructive spectrometry
  • Junrui Liang, Min Jiang, Jun Li, Zhongming Huang, Junhong He, Yanting Guo, Yanzhao Ke, Jun Ye, Jiangming Xu, Jinyong Leng, Pu Zhou
  • Opto-Electronic Advances
  • 2026-08-25
  • Video-rate wavefront capture and replay via single-shot reference-free measurement: toward holographic telepresence
  • Minwook Kim, Chansuk Park, Chulmin Oh, KyeoReh Lee, Herve Hugonnet, YongKeun Park
  • Opto-Electronic Advances
  • 2026-08-25
  • Luminescent YAG:Ce³⁺ 3D micro-structures via multi-photon laser lithography
  • Robertas Virkėtis, Greta Merkininkaitė, Artūr Harnik, Ugnė Ūsaitė, Dominykas Dapšys, Arturo Susarrey-Arce, Simas Šakirzanovas, Mangirdas Malinauskas
  • Opto-Electronic Advances
  • 2026-08-25
  • A 36 × 240 Gbps hybrid mode/wavelength division multiplexing transmitter using lithium niobate on insulator
  • Mingyu Zhu, Weihan Wang, Ruitao Ma, Aoyun Gao, Chun Gao, Zexu Wang, Fei Huang, Zhenyuan Bao, Dajian Liu, Jiaxuan Gan, Zejie Yu, Huan Li, Weike Zhao, Daoxin Dai
  • Opto-Electronic Advances
  • 2026-08-25



  • Therapeutic efficacy observation of Tuina manipulation for pediatric adenoid hypertrophy        Military traumatic brain injury: a challenge straddling neurology and psychiatry
    About
    |
    Contact
    |
    Copyright © PubCard