Table 2

Multivariable logistic regression model using backward stepwise algorithm for selection of independent predictors of severe course of COVID-19

Predictors	Regression coefficients	SE	OR (95% CI)	P value
Sex
Women			Reference category
Men	0.742	0.112	2.10 (1.68 to 2.62)	<0.001
Age (years)
<40			Reference category
40–49	1.227	0.464	3.41 (1.37 to 8.48)	0.008
50–59	2.478	0.414	11.92 (5.30 to 26.81)	<0.001
60–69	3.424	0.399	30.68 (14.04 to 67.04)	<0.001
70–79	4.109	0.398	60.89 (27.93 to 132.73)	<0.001
80–89	4.725	0.400	112.68 (51.48 to 246.63)	<0.001
90+	5.299	0.428	200.12 (86.50 to 462.97)	<0.001
Comorbidities
Chronic kidney disease	0.679	0.157	1.97 (1.45 to 2.68)	<0.001
Chronic obstructive pulmonary disease	0.436	0.144	1.55 (1.17 to 2.05)	0.002
Recent history of cancer (≤5 years)	0.432	0.194	1.54 (1.05 to 2.25)	0.026
Chronic heart failure	0.408	0.166	1.50 (1.09 to 2.08)	0.014
Acid-related disorders	0.382	0.118	1.47 (1.16 to 1.85)	0.001
Diabetes mellitus	0.323	0.129	1.38 (1.07 to 1.78)	0.012
Intercept	−6.448	0.386	–	<0.001

Overall predictive power: AUC (95% CI): 0.893 (0.880 to 0.907); sensitivity: 85.8% and specificity: 80.3%.
Age, sex and comorbidities from table 1 were entered into the model.