Seyed Ehsan Saffari

Comparison of combined treatment with desmopressin plus oxybutynin and desmopressin plus tolterodine in treatment of children with primary nocturnal enuresis

Introduction: Nocturnal enuresis (enuresis) is one of the most common developmental problems of childhood, which has often a familial basis, causes mental and psychological damage to the child and disrupts family solace. Objectives: In this study, we compared therapeutic effects of combination therapy of desmopressin plus oxybutynin with desmopressin plus tolterodine, in the treatment of children with primary nocturnal enuresis. Patients and Methods: The present study is a clinical trial study, where 59 patients with primary nocturnal enuresis in the age range of 5 to 14 years old were selected from the visitors of nephrology clinic of Dr. Sheikh pediatrics hospital (Mashhad, Iran). Patients were divided into 2 treatment groups where the first group received combined therapy with desmopressin and oxybutynin, and the second group received combined therapy with desmopressin and tolterodine. Data was analyzed using SPSS 16 software and descriptive and analytical statistics (chi-square test). Results: The mean of age of patients in total was 2.55 ± 7.90 years. In the treatment group with desmopressin and oxybutynin, 26 of 30 patients (86.7%) achieved a complete remission and 4 patients (13.3%) still suffered from enuresis during a 3-month evaluation. The comparison of 2 groups, in terms of the outcome of the 3-month treatment, showed significant differences between the remission and recovery of 2 groups, where the recovery in the group with desmopressin plus tolterodine was higher than the group with desmopressin plus oxybutynin (P = 0.001). Conclusion: The results showed that combined treatment with desmopressin plus tolterodine performs better than desmopressin plus oxybutynin .

Robust PC with wild bootstrap estimation of linear model in the presence of outliers, multicollinearity and heteroscedasticity error variance

The regression model estimator is considered efficient if it is robust and resistant to the presence of heteroscedasticity variance, multicollinearity or unusual observations called outliers. However, in regard to these problems, the wild bootstrap and robust wild bootstrap are no longer efficient since they could not produce the smallest variance. Hence this research investigates the use of robust PC with wild bootstrap techniques on regression model as an estimator for real and simulation data in a situation where multicollinearity, heteroscedasticity and multiple outliers are present. This paper proposed a robust procedure based on the weighted residuals which combined the Tukey bisquare weighted function, principal component analysis (PCA) to remedy the multicollinearity problems, least trimmed squares (LTS) estimator, robust location and scale, and the wild bootstrap sampling procedure of Wu and Liu that remedy the heteroscedasticity error variance. RPCWBootWu and RPCWBootLiu were obtained through a modified version of RBootWu and RBootLiu. Finally, based on the real data and simulation study, the performance of the RPCWBootWu and RPCWBootLiu is compared with the existing RBootWu, RBootLiu and also with BootWu, BootLiu using the biased, RMSE and standard error. The numerical example and simulation study shows that the RPCWBootWu and RPCWBootLiu techniques have proven to be a good alternative estimator for regression model with lower standard error values.