Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development.

Tao Fan Bo Hao Shuo Yang Bo Shen Zhixin Huang Zi-Long Lu Rui Xiong Xiaokang Shen Wenyang Jiang Lin Zhang Donghang Li Ruyuan He Heng Meng Weichen Lin Haojie Feng Qing Geng

Published in: JMIR medical informatics (2020)

This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

Keyphrases

lymph node metastasis
end stage renal disease
ejection fraction
coronavirus disease
sars cov
randomized controlled trial
newly diagnosed
palliative care
squamous cell carcinoma
electronic health record
big data
risk assessment
patient reported outcomes
human health
real time pcr