Objective: The aim of this study was to compare the outcomes of in vitro fertilization (IVF) in patients with a poor ovarian response who used methyltestosterone, versus those using a placebo, in an infertility clinic setting. Methods: This clinical trial included 120 women who had undergone IVF with intracytoplasmic sperm injection due to poor ovarian reserve and infertility. The study took place at the Yas Infertility Center in Tehran, Iran, between January 1, 2018 and January 1, 2019. In the intervention group, 25 mg of methyltestosterone was administered daily for 2 months prior to the initiation of assisted reproductive treatment. The control group was given placebo tablets for the same duration before starting their cycle. Each group was randomly assigned 60 patients. All analyses were performed using SPSS ver. 23 (IBM Corp.). Results: The endometrial thickness in the intervention group was 7.57±1.22 mm, whereas in the control group, it was 7.11±1.02 (p=0.028). The gonadotropin number was significantly higher in the control group (64.7±13.48 vs. 57.9±9.25, p=0.001). However, there was no significant difference between the two groups in the antral follicular count. The chemical and clinical pregnancy rates in the intervention group were 18.33% and 15% respectively, compared to 8.33% and 6.67% in the control group. The rate of definitive pregnancy was marginally higher in the intervention group (13.3% vs. 3.3%, p=0.05). Conclusion The findings of this study suggest that pretreatment with methyltestosterone significantly increases endometrium thickness and is associated with an increase in the definitive pregnancy rate.

Objective: To determine the temporal patterns of cumulative incidence of brucellosis using autoregressive integrated moving average models. Methods: This cross-sectional study employed yearly and monthly data of 1 117 laboratory-confirmed human brucellosis cases from January 2013 to December 2018 using the Yazd brucellosis national surveillance system. The monthly incidences constructed a timeseries model. The trend of cumulative incidence was perceived by tracing a line plot, which displayed a seasonal trend with periodicity. Thus, the ARIMA models were selected. Thereafter, Akaike information criteria (AIC) and Bayesian information criterion (BIC) values among different models indicated a preferable model from models which were expanded by diverse lags [(3, 0, 3), (2, 0, 3), (3, 0, 2), (4, 0, 3) and (3, 0, 4)]. Then, the achieved ARIMA model was applied to the forecasting cumulative incidence of monthly brucellosis incidences. All analyses were performed using Stata, version 11.2. Results: For the ARIMA (3, 0, 4) model, MAPE value was 56.20% with standard error 0.009-0.016, and white noise diagnostic check (Q=19.79, P=0.975) for the residuals of the selected model showed that the data were completely modelled. The monthly incidences that were fitted by the ARIMA (3, 0, 4) model, with AIC (25.7) and BIC (43.35) with a similar pattern of actual cases from 2013 to 2018 and forecasting incidences from January 2019 to December 2019 were, respectively, 0.50, 0.44, 0.45, 0.49, 0.55, 0.58, 0.56, 0.51, 0.46, 0.44, 0.45 and 0.49 per 100 000 people. Conclusions: In summary, the study showed that the ARIMA (3, 0, 4) model can be applied to forecast human brucellosis patterns in Yazd province, supplementing present surveillance systems, and may be better for health policy-makers and planners.