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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