Context The number of tuberculosis (TB) patients and multidrug-resistant species of Mycobacterium tuberculosis are increasing worldwide. Effective treatment is still the key factor to control TB in the society. Aims The aim of the study was to compare the efficacy of fixed-dose combination (FDC) and separate drug (SD) in the treatment of TB. Settings and design The study was a randomized, clinical trial carried out on 331 smear-positive TB patients in the Golestan province, Iran. Patients and methods Diagnosis and monitoring method was direct observation of sputum smears under a light microscope, which was used at the end of the second, third, fourth, fifth, or sixth months during the treatment. Statistical analysis used Sputum smear conversion rate at the end of second months and therapy outcome at the end of the treatment period were compared in both groups of the study by using the Poisson regression model and calculation incidence rate ratio. Results Sputum smear conversion rate at the end of the second month of the treatment had no significant difference between two groups. Success rate at the end of the treatment period was 89.36% in the intervention group and 95.65% in the nonintervention group which had significant difference (P=0.03). Adverse event incidence rate was 5.44% in all studied cases during the period of treatment. It had significant difference between the group who received FDC (8.93%) and the other who received SD (1.86%). Conclusion SD had better efficacy than FDC drugs in the treatment of TB patients.

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Background: Suicide risk factors can be used to develop tools for suicide attempt prediction and prevention. Objectives: We aimed to design a model to evaluate the risk of suicide related to socio-economic, demographic, health, and drug dependency factors. Methods: This case-control study was conducted in a 15-65-year-old population of Golestan province, Iran. The case group included 414 individuals with a history of suicide in 2019, and the control group had 408 individuals without suicide attempts. Demographic, psychosocial health, and drug dependency data were collected. Modeling was carried out using multivariate logistic regression. The performance of suicide-predicting models was assessed, and a nomogram for the probability of suicide was drawn. Results: A multivariate logistic regression model with age, gender, education level, mother's education level, marital status, life satisfaction, membership in cyberspace, sleep disorders, alcohol abuse, having suicidal thoughts, the interaction of gender with life satisfaction, and the interaction of gender with mother's education level was the best predicting model of suicide attempt (AUC = 0.934, CI: 0.91 - 0.95). The variables of father's education level, occupation, job satisfaction, household size, financial status, regular exercise, guardianship status, history of self-harm, history of suicide attempt in the family, smoking and drug abuse had no significant relationship with suicide attempt. 5.1. Conclusions: The results suggest that designed models can help mental health service providers to identify high-risk individuals early. So we can better manage suicide and reduce its economic, social, and health burdens.

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