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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