Table 4.

ROC curve analysis of the studied markers to differentiate between COVID-19 patients and control and for discrimination of severity.

	Differentiation between total patients and control
	NEAT1 Expression	TUG1 Expression	CCL2 Expression	TNF-α Expression	IL-6 Expression
AUC	0.965	0.999	0.938	0.957	1.0
P value	<0.001	<0.001	<0.001	<0.001	<0.001
95% CI	0.93 - 1.0	0.997 - 1.0	0.88 - 0.99	0.93 - 99	1.0 - 1.0
Cutoff point	90.88	2.28	0.839	3.245	0.359
Sensitivity	96.3%	98.8%	93.8%	91.3%	100%
Specificity	100%	100%	100%	92.5%	100%
PPV	100%	100%	100%	96.1%	100%
NPV	93.0%	97.6%	88.9%	84.1%	100%
Accuracy	97.5%	99.2%	95.8%	91.7%	100%
	Differentiation between moderate and severe COVID-19 patients
	NEAT1 Expression	TUG1 Expression	CCL2 Expression	TNF-α Expression	IL-6 Expression
AUC	0.63	0.51	0.92	0.60	1.0
P value	0.05	0.92	<0.001	0.13	<0.001
95% CI	0.49 - 0.76	0.38 - 0.64	0.86 - 0.99	0.47 - 0.73	1.0 - 1.0
Cutoff point	1481.008	643.63	46654.81	9.62	356.94
Sensitivity	68.9%	60.0%	91.1%	64.4%	100%
Specificity	68.6%	57.1%	82.9%	62.9%	100%
PPV	73.8%	64.3%	87.2%	69.0%	100%
NPV	63.2%	52.6%	87.9%	57.9%	100%
Accuracy	68.8%	58.8%	87.5%	51.3%	100%

AUC; area under the curve, PPV; positive predictive value, NPV; negative predictive value.