Treatment non-adherence results in treatment failure, prolonged transmission of disease and emergence of drug resistance. Although the problem widely investigated, there remains an information gap on the effectiveness of different methods to improve treatment adherence and the predictors of non-adherence in resource limited countries based on theoretical models. This study aimed to evaluate the impact of psychological counseling and educational intervention on tuberculosis (TB) treatment adherence based on Health Belief Model (HBM). A cluster randomized control trial was conducted in Addis Ababa from May to December, 2014. Patients were enrolled into study consecutively from 30 randomly selected Health Centers (HCs) (14 HCs intervention and 16 HCs control groups). A total of 698 TB patients, who were on treatment for one month to two months were enrolled. A structured questionnaire was administered to both groups of patients at baseline and endpoint of study. Control participants received routine directly-observed anti-TB therapy and the intervention group additionally received combined psychological counseling and adherence education. Treatment non-adherence level was the main outcome of the study, and multilevel logistic regression was employed to assess the impact of intervention on treatment adherence. At enrollment, the level of non-adherence among intervention (19.4%) and control (19.6%) groups was almost the same. However, after intervention, non-adherence level decreased among intervention group from 19.4 (at baseline) to 9.5% (at endpoint), while it increased among control group from 19.4% (baseline) to 25.4% (endpoint). Psychological counseling and educational interventions resulted in significant difference with regard to non-adherence level between intervention and control groups (Adjusted OR = 0.31, 95% Confidence Interval (CI) (0.18–0.53), p < 0.001)). Psychological counseling and educational interventions, which were guided by HBM, significantly decreased treatment non-adherence level among intervention group. Provision of psychological counseling and health education to TB patients who are on regular treatment is recommended. This could be best achieved if these interventions are guided by behavioral theories and incorporated into the routine TB treatment strategy. Pan African Clinical Trials Registry PACTR201506001175423

This systematic review intended to combine factors associated vith tuberculosis trea adherence and lo' to follow up among TB patterits with/without ETIV in developing countries. Corriprehensive remote electronic databases (MEDLINE, (PMC, Pub Med Central), Google scholar and Web cif science) search AVaS crrnducted using the followirig key\vords: Tuberculosis, treatment, ccrmpliarice, adherence, default, behavioural factors and socioeconomic factors. All t)rfres of studies intended to assess TB treatment non-adherence and lost to follo-sv up in developing countries among adult TB patient from 2008 to data extraction date were included. Twenty-six original and one-relrewed articles, which meet inclusion criteria, were reviewed. TB treatment non-adherence and lost to follow up were continued across developin g countries. Tire main factors associated with TB treatment non-adherence and lost to follow up were.. socioeconomic factors: lack of transportation cest, lack of social support, and patients-health care. Behavioural factors were Feeling better after few weeks of treatrrients, tobacco and alcohol use, lmowledge deficit about duration of treatment and corisequerices of non-adherence and lost to follow up. TB treat. merit non-adherence and lost to follow up were continued across developing countnes throughout the publication years of reviewed articles. Numerous, socioeconcrmic and behavioural factors were intliiericing TB treatiTierit adherence and lost to folllow-up Therefore well understanding and minimizing of the effect of these associated factors is very important to enhance treatinerit adherence and follow up completion in developing countries.

Psychological distress and its effect on tuberculosis treatment outcomes in Ethiopia

The diagnoses of active smear negative PTB, remains difficult. As a result, treatment is often carried out empirically relaying on clinical criteria. The distribution and magnitude of smear negative PTB, smear negative MDR-TB and associated factors in the same day diagnosis strategy are not clearly known in the study area. Therefore, this study aimed to determine the prevalence of TB, MDR-TB and associated risk factors among presumptive smear negative pulmonary tuberculosis patients in Addis Ababa, Ethiopia. Analytic cross sectional study design was used. A total of 418 smear negative presumptive pulmonary TB patients were enrolled from selected health facilities since August 01, 2017 to January 5, 2018. Sputum samples were examined by Ziehl Neelsen microscopy, Xpert MTB/RIF assay and Culture. Drug susceptibility testing was performed by line probe assay and BACTEC MGIT 960 system. These laboratory tests were performed in Ethiopian Public Health Institute, National TB Reference Laboratory. Data was analyzed by SPSS Ver.20. From the total of 418 enrolled patients, 27 (6.5%) were Xpert MTB/ RIF and 26 (6.4%) were culture confirmed smear negative PTB patients. The positivity rate among male and female was 10.2 and 3.5% (p = 0.005) respectively. From 26 culture positive isolates 3 (11.54%) were MDR TB; from MDR-TB confirmed isolates 2/23 (8.7%) were among new and 1/3 (33.3%) was among retreatment smear negative presumptive pulmonary TB patients. All Rifampicin resistant smear negative pulmonary TB isolates by Xpert MTB/ RIF assay were found to be MDR TB and 7/26 (26.9%) isolates were INH mono resistant. History of migration found to be a potential factor for developing smear negative pulmonary TB. In this study a significant proportion of smear negative pulmonary TB was diagnosed. Furthermore, a high smear negative multi drug resistant (MDR) TB and other mono drug resistant TB prevalence was confirmed. Due to the limitations of smear microscopy which is used as a primary diagnostic tool, these TB strains are missed to be diagnosed and transmission continues in the community.

To estimate the pooled proportion of extensively drug-resistant tuberculosis (XDR-TB) and pre-extensively drug-resistant tuberculosis (pre-XDR-TB) in patients with multidrug-resistant TB (MDR-TB). We systematically searched articles from electronic databases: MEDLINE (PubMed), ScienceDirect, and Google Scholar. We also searched gray literature from the different literature sources main outcome of the review was either XDR-TB or pre-XDR-TB in patients with MDR-TB. We used the random-effects model, considering the substantial heterogeneity among studies. Heterogeneity was assessed by subgroup analyses. STATA version 14 was used for analysis. A total of 64 studies that reported on 12,711 patients with MDR-TB from 22 countries were retrieved. The pooled proportion of pre-XDR-TB was 26% (95% confidence interval [CI]: 22-31%), whereas XDR-TB in MDR-TB cases was 9% (95% CI: 7-11%) in patients treated for MDR-TB. The pooled proportion of resistance to fluoroquinolones was 27% (95% CI: 22-33%) and second-line injectable drugs was 11% (95% CI: 9-13%). Whereas the pooled resistance proportions to bedaquiline, clofazimine, delamanid, and linezolid were 5% (95% CI: 1-8%), 4% (95% CI: 0-10%), 5% (95% CI; 2-8%), and 4% (95% CI: 2-10%), respectively. The burden of pre-XDR-TB and XDR-TB in MDR-TB were considerable. The high burdens of pre-XDR-TB and XDR-TB in patients treated for MDR-TB suggests the need to strengthen TB programs and drug resistance surveillance.

Background: Although there are several studies reported on factors affecting tuberculosis (TB) treatment non-adherence, there is information gap on psychosocial and patients’ perceptions aspects. Therefore, this study was aimed to investigate the effect of psychosocial factors and patients’ perceptions on TB treatment non-adherence in Ethiopia. Methods: A cross sectional study was conducted in Addis Ababa from May to December, 2014. Thirty one health facilities were randomly selected and 698 TB patients, who had been on treatment, were enrolled consecutively using patient registration number. Structured questionnaire was used to collect data on demographics, knowledge, psychological distress, alcohol use, tobacco smoking and six HBM domains. Treatment adherence level was the main outcome variable, and it measured using visual analog scale. Statistical Package for Social Sciences version 20 was used for data analysis. Results: Non-adherence level within last one month prior to the study was 19.5%. After controlling for all potential confounding variables, Antiretroviral Therapy (ART) status (Adjusted Odds Ratio (AOR) = 1.79, 95% Confidence interval (CI) (1.09 -2.95)), alcohol use (AOR = 2.11, 95% CI (1.33-3.37)), economic status (AOR = 0.53, 95% CI (0.33-0.82)), perceived barriers (AOR = 1.21, 95% CI (1.10-1.47)) and psychological distress (AOR = 1.83, 95% CI (1.47-2.29)) were independently associated with TB treatment non-adherence. Conclusion: ART status, economic status, alcohol use, perceived barrier and psychological distress are the major areas that need to be targeted with health promotion intervention to enhance TB treatment adherence. Keywords: Treatment Non-adherence, Determinants of treatment non-adherence, Health Belief Model, Tuberculosis