Table 5.

Predictors of COVID-19 mortality in patients with hemoglobinopathy.

Variables	Simple logistic regression			Binary logistic regression
	Crude odds ratio	95% CI	p -value	Adjusted odds ratio	95% CI	p -value
Gender	2.015	(0.741, 5.483)	0.170	1.225	(0.086, 17.391)	0.881
(female vs. male)
Age	1.492	(0.328, 6.795)	0.605	0.171	(0.009, 3.179)	0.237
(pediatric vs. adult)
Types of hemoglobinopathy	7.232	(2.278, 22.958)	0.001*	14.612	(0.425, 502.262)	0.137
(Thal vs. SCD)
Respiratory comorbidity	1.902	(0.398, 9.103)	0.421	89.625	(2.514, 3195.537)	0.014*
(no vs. yes)
Cardiovascular comorbidity	4.081	(1.396, 11.930)	0.010*	35.199	(1.291, 959.526)	0.035*
(no vs. yes)
Splenectomy	3.442	(1.260, 9.403)	0.016*	<0.001	–	0.998
(no vs. yes)
Diabetes mellitus	2.511	(0.760, 8.296)	0.131	<0.001	–	0.998
(no vs. yes)
Oxygen requirement	3.779	(0.614, 23.271)	0.152	8.912	(0.674, 117.824)	0.097
(no vs. yes)

CI, confidence interval; Thal, thalassemia; SCD, sickle cell disease.

Simple logistic regression was performed for all comorbidities vs. mortality as an outcome. Comorbidities with p-value of <0.25 for simple logistic regression were included in the model for binary logistic regression.

^*Indicate statistically significant p < 0.05.