COVID-19 Research Paper Volume 13, Issue 14 pp 17961—17977
Two novel nomograms based on inflammatory cytokines or lymphocyte subsets to differentially diagnose severe or critical and Non-Severe COVID-19
- 1 Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China
- 2 Department of Emergency, China-Japan Union Hospital of Jilin University, Changchun 130021, China
- 3 Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
- 4 Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun 130021, China
- 5 Department of Critical Care Unit, China-Japan Union Hospital of Jilin University, Changchun 130021, China
- 6 Department of Neurosurgery, China-Japan Union Hospital of Jilin University, Changchun 130021, China
Received: March 10, 2021 Accepted: July 2, 2021 Published: July 19, 2021https://doi.org/10.18632/aging.203307
How to Cite
Copyright: © 2021 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
We intend to evaluate the differences of the clinical characteristics, cytokine profiles and immunological features in patients with different severity of COVID-19, and to develop novel nomograms based on inflammatory cytokines or lymphocyte subsets for the differential diagnostics for severe or critical and non-severe COVID-19 patients. We retrospectively studied 254 COVID-19 patients, 90 of whom were severe or critical patients and 164 were non-severe patients. Severe or critical patients had significantly higher levels of inflammatory cytokines than non-severe patients as well as lower levels of lymphocyte subsets. Significantly positive correlations between cytokine profiles were observed, while they were all significantly negatively correlated with lymphocyte subsets. Two effective nomograms were developed according to two multivariable logistic regression cox models based on inflammatory cytokine profiles and lymphocyte subsets separately. The areas under the receiver operating characteristics of two nomograms were 0.834 (95% CI: 0.779–0.888) and 0.841 (95% CI: 0.756–0.925). The bootstrapped-concordance indexes of two nomograms were 0.834 and 0.841 in training set, and 0.860 and 0.852 in validation set. Calibration curves and decision curve analyses demonstrated that the nomograms were well calibrated and had significantly more clinical net benefits. Our novel nomograms can accurately predict disease severity of COVID-19, which may facilitate the identification of severe or critical patients and assist physicians in making optimized treatment suggestions.