Table 3:

Logistic regression model for mortality risk

			Odds Ratio	95% Confidence interval	P	βi (coefficient)
β 0	(Intercept)		0.000		0.0000	−11.227376
Age	continuous in years		1.105	[1.095–1.115]	0.0000	0.099573
Sex	Male		1.000	reference		0
	Female		0.500	[0.401–0.625]	0.0000	−0.692446
Vaccine doses	0		1.000	reference		0
	1		0.921	[0.627–1.354]	0.6771	−0.081842
	2		0.936	[0.698–1.254]	0.6561	−0.066541
	3		0.223	[0.091–0.551]	0.0011	−1.498783
BMI category	Underweight	< 18.5	2.179	[1.056–4.496]	0.0350	0.778997
	Normal	18.5 – 25	1.000	reference		0
	Overweight	25 – 30	0.979	[0.733–1.307]	0.8866	−0.021027
	Obese I	30 – 35	1.085	[0.785–1.500]	0.6196	0.081961
	Obese II+	≥ 35	1.963	[1.383–2.786]	0.0002	0.674479
Kidney function GFR category	G1 (Normal)	≥ 90	1.000	reference		0
	G2	60–89	1.283	[0.965–1.705]	0.0861	0.249162
	G3a	45–59	2.000	[1.390–2.878]	0.0002	0.693180
	G3b	30–44	3.097	[2.035–4.715]	0.0000	1.130578
	G4/G5	<30	6.888	[4.389–10.810]	0.0000	1.929831
Hemoglobin A1C %	< 6.5		1.000	reference		0
	[6.5, 8.0)		1.137	[0.851–1.518]	0.3842	0.128408
	[8.0, 10.0)		1.479	[0.983–2.226]	0.0602	0.391618
	≥ 10.0		1.782	[0.905–3.510]	0.0948	0.577767
Comorbidities	Hypertension		1.348	[1.011–1.797]	0.0421	0.298497
	Pulmonary Disease		1.475	[1.113–1.956]	0.0069	0.388824
	Malignancy		1.138	[0.868–1.491]	0.3489	0.129199

^*Odds ratio is defined as Exp(coefficient).

Coefficients in the last column are the β_i to be used to calculate the odds ratio, using the following formula: Odds Ratio = Exp (β₀ + x₁ β₁ + x₂ β₂ + x₃ β₃ + x₄ β₄ + …)

Probability of event can be obtained from the odds ratio, using the formula: p = (Odds Ratio) / (1 + Odds Ratio)