Modelling of a triage scoring tool for SARS-COV-2 PCR testing in health-care workers: data from the first German COVID-19 Testing Unit in Munich

Table 4 Variables selected for logistic regression

Characteristics	Univariable logistic regression				Multivariable logistic regression model
Characteristics	Odds ratio	p value	95% confidence interval		Odds ratio	p value	95% confidence interval
Abdominal pain	17.56	0.000	5.99	51.51	7.38	0.070	0.85	64.36
Any exposition	3.52	0.000	1.93	6.43	3.80	0.002	1.66	8.71
Chest pain	6.84	0.000	2.81	16.69
Cough	5.84	0.000	4.04	8.46	2.39	0.002	1.38	4.14
Diarrhea	4.04	0.023	1.21	13.50
Otalgia	3.77	0.076	0.87	16.37
Sputum production	8.71	0.000	3.51	21.58
Other exposition	1.60	0.131	0.87	2.95
Exposition to patient	1.79	0.003	1.21	2.62	1.72	0.031	1.05	2.81
Exposition to private contact	1.59	0.125	0.88	2.86
Fatigue	5.76	0.000	3.11	10.67
Fever	9.25	0.000	6.14	13.92	5.78	0.000	3.11	10.74
Headache	5.24	0.000	3.20	8.59
Joint pain	15.27	0.000	7.83	29.79
Anosmia/Ageusia	9.36	0.000	4.72	18.56	4.17	0.001	1.78	9.78
Lymphadenopathy	9.65	0.001	2.68	34.73
Muscle pain	12.43	0.000	6.74	22.95	6.24	0.001	2.16	18.03
Nausea/Emesis	7.26	0.000	2.45	21.56
Rhinorrhea	4.88	0.000	3.36	7.08
Shortness of breath	2.21	0.067	0.95	5.15
Sore throat	1.85	0.003	1.23	2.78

Univariable analysis of clinical signs and epidemiological features associated with COVID-19 with p < 0.2 and multivariable logistic regression of selected variables

ISSN: 1471-2334