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Table 5 Binary logistic regression analysis for severity among patients with COVID-19 infection

From: COVID-19 infection: epidemiological, clinical, and radiological expression among adult population

Variables

Wald

P value

OR

95% CI

Lower

Upper

Age

 ≥ 65 years vs < 65 years

11.87

0.001

4.93

2.74

9.25

Gender

 Male vs female

6.94

0.008

2.18

1.22

3.91

Smoking history

 Smokers vs non-smokers

7.83

0.005

3.31

1.43

7.63

Hypertension

 Yes vs no

5.18

0.02

2.13

1.45

6.72

O2 saturation

 ≤ 93 vs > 93

5.76

0.01

1.98

1.13

3.46

CT severity score

4.40

0.03

2.75

1.06

7.11

CBC

 Lymphopenia vs normal

1.46

0.22

1.59

0.74

3.39

S.ferritin

 High level vs normal

6.48

0.006

2.13

1.22

4.75

D.dimer

 High level vs normal

10.36

0.001

3.88

1.69

8.85

  1. The Wald test (also called the Wald Chi-squared test) is a way to find out if explanatory variables in a model are significant. “Significant” means that they add something to the model; variables that add nothing can be deleted without affecting the model in any meaningful way