Skip to main content

Table 2 Logistic analysis of each factor’s ability in predicting the risk of ICU admission with COVID-19

From: Exploiting an early warning Nomogram for predicting the risk of ICU admission in patients with COVID-19: a multi-center study in China

  Prediction model
β Odds ratio (95%CI) P-value
Intercept 8.409 4485.633 (0.000-NA) 0.997
Age < 65 years − 1.650 0.192(0.102–0.356) 0.000
Female −0.548 0.578(0.312–1.055) 0.077
Respiratory rate < 22 −1.516 0.220(0.120–0.403) 0.000
Systolic Blood Pressure > 100 mmHg −1.466 0.231(0.067–0.966) 0.029
Non-Smoking 0.974 2.647(1.308–5.245) 0.006
Fever (No) −0.912 0.402(0.186–0.808) 0.014
Cough (No) −0.172 0.842(0.438–1.583) 0.599
Dyspnea (No) −0.489 0.613(0.325–1.177) 0.134
Fatigue (No) −0.419 0.658(0.362–1.192) 0.166
Sore Throat (No) −0.725 0.484(0.205–1.249) 0.112
Asthma (No) 14.989 32,340(0.000-NA) 0.984
Chronic Respiratory Disease (No) −0.405 0.667(0.206–2.347) 0.509
Chronic Kidney Disease (No) −2.043 0.130(0.031–0.582) 0.005
Cardiovascular System Disease (No) −0.465 0.628(0.275–1.516) 0.283
Autoimmune Disease (No) −1.132 0.322(0.075–1.544) 0.135
Hematological Disease (No) −16.456 0.000(NA-Inf) 0.995
Stroke History (No) −0.780 0.458(0.130–1.955) 0.251
Chronic Liver Disease (No) 0.041 1.042(0.361–3.854) 0.945
Without contact history of COVID-19 0.450 1.569(0.748–3.537) 0.252