Introduction: Tuberculosis treatment interruption increases the risk of poor treatment outcomes and the occurrence of drug resistant Tuberculosis. However, data on the incidence and predictors of tuberculosis treatment interruption are still scarce in Ethiopia, as well as in the study area. Therefore, this study aimed to assess the incidence and predictors of treatment interruption among patients on tuberculosis treatment in Nekemte public healthcare facilities, Oromia region, Western Ethiopia, from July 1, 2017, to June 30, 2021.

Methods: A retrospective cohort study design was conducted among 800 patients enrolled in anti-tuberculosis treatment during the study period. Data were collected from patient cards who were enrolled in treatment from July 1, 2017 to June 30, 2021. Epidata version 3.2 was used for data entry, and STATA version 14 was used for analysis. A multivariable Cox regression model with a 95% confidence interval (CI) and adjusted hazard ratio (AHR) was used to identify the significant predictors at a value < 0.05. Finally, the log likelihood ratio, and a Cox-Snell residual graph was used to check the adequacy of the model.

Results: A total of 800 patients were followed for a median time of 2.3 (95% CI: 2.20-2.36) months, and with a maximum follow-up time of 11.7 months. The overall incidence rate of treatment interruption was 27.4 per 1000 (95% CI: 22.8-32.8) person-month observations. Age 18-34 years (AHR = 1.8, 95% CI: 1.02-3.18), male (AHR = 1.63, 95% CI: 1.1-2.42), rural residence (AHR = 3, 95% CI: 1.98-4.64), presence of comorbidity (AHR = 10, 95% CI: 5.47-18.27) and lack of treatment supporters on the treatment follow-up (AHR = 2.82, 95% CI: 1.9-4.41) were found to be significant predictors of treatment interruption.

Conclusion: A high incidence rate of interruption was observed among TB patients in public health facilities in Nekemte town. Health facilities should provide supportive care for patients with co-morbidities and consider interventions that target middle-aged patients from rural areas that reduce treatment interruptions.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910942PMC
http://dx.doi.org/10.3389/fepid.2023.1234865DOI Listing

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