Using electronic medication monitoring to guide differential management of tuberculosis patients at the community level in China

Table 1 Factors associated with refusing to use the EMM among eligible TB patients in the study city (n = 231)

Factors	Total		Refused to use EMM		OR	(95% CI)	aOR^f	(95% CI)
Factors	n	(%)^a	n	(%)^b	OR	(95% CI)	aOR^f	(95% CI)
Sex
Male	164	71.0	18	11.0	ref		ref
Female	67	29.0	8	11.9	1.1	0.5–2.7	1.3	0.5–3.3
Age^c
< 44	54	23.4	4	7.4	ref		ref
45–64	82	35.5	8	9.8	1.6	0.6–4.0	1.5	0.6–3.9
> =65	95	41.1	14	14.7	2.2	0.7–6.9	1.7	0.5–6.1
Occupation
Farmer/migrant worker	142	61.5	17	12.0	1.2	0.5–2.8	1.2	0.5–3.0
Other	89	38.5	9	10.1	ref		ref
Migrant^d
No	160	69.3	18	11.3	ref		ref
Yes	71	30.7	8	11.3	1.0	0.4–2.4	1.6	0.5–2.9
Category
New	206	89.2	22	10.7	ref		ref
Retreated	25	10.8	4	16.0	1.6	0.5–5.1	1.0	0.3–3.5
Classification
Bacteriologically confirmed	115	49.8	20	17.4	3.9^e	1.5–10.0	3.7^e	1.4–9.8
Clinically diagnosed	116	50.2	6	5.2	ref		ref

TB Tuberculosis, EMM Electronic medication monitor, OR Odds ratio, aOR Adjusted odds ratio, CI Confidence interval
^aColumn percentages
^bRow percentages
^cOnly one patient was under 15 years old, so < 15 group was merged into < 44 group
^dMigrant defined as patient coming from another county
^eStatistically significant
^fEven though some variables didn’t show statistical significance in univariate analysis, considering the important influence of patient’s background and diagnosis in the treatment management, we included all the variables in the multivariable analysis

ISSN: 1471-2334