The model had an AUC of 0.956 [95%CI 0.935-0.977] on the training dataset and an AUC of 0.960 [95%CI 0.919-1.0, P < 0.001] on the validation dataset.
Outcome should be “Probability of severe illness in case of infection”.
The nomogram had a C-statistic of 0.967 (95% CI, 0.943–0.992) for predicting the probability in suspected COVID-19 pneumonia patients.
Suspected diagnostic criteria are:
1) Epidemiological history,
2) Fever and / or respiratory symptoms,
3) Suspected COVID-19 pneumonia imaging features,
4) Normal range or decrease of white blood cell (WBC) count or lymphocyte at beginning of disease. Patients who have epidemiological history + any two clinical symptoms or no epidemiological history + three clinical symptoms can be suspected of COVID-19 pneumonia