الهه غضنفری

Aims: Marriage attitude is a cognitive phenomenon that has a considerable influence on willingness to get married, age when married and the stability of marriage. This study was done with the aim of exploration affecting factors on marriage attitude pattern.
Instrument & This cross sectional study was done with using two-stage cluster sampling in year 2015-2016, on 750 Tehran, Iran, police personnel. Self-made questionnaire on marital attitude was used to data collection. Data was analyzed using factor analysis Spearman correlation coefficient and path analysis in SPSS 23 and AMOS 23.
Findings: The number of siblings, work experience and the ideal number of children indicators had a positive significant correlation and the ideal age had a significant negative correlation with the marital attitude. The correlation between age and economic situation indicators with marital attitude was not significant (p>0.05). The goodness of fit index with values of RMSEA=0.00, GFI=0.99, NFI=0.99 and CMIN/DF=0.73, showed that the path model is suitable. In the path analysis test it was determined that gender, the ideal age for marriage and the number of siblings had direct effects and age, years of work experience, the ideal number of children and the economic situation had indirect effects on marital attitude.
Creating the culture of having more children in the family, stabilize the employment situation and having appropriate work experience increase attitudes toward marriage.

Coronary artery disease is one of the most prevalent causes of death. A coronary artery bypass surgery is a common treatment for this disease. In addition, renal dysfunction can lead to increased mortality and post-operative complications. This study aimed to identify the most important factors influencing the mortality of patients who suffer from coronary artery disease and to introduce a classification approach according to Classification Tree (CART) model for predicting the mortality from this disease. This research was conducted based on the information gathered from a cross-sectional study on 1390 patients (except dialysis-dependent) who undergone coronary artery bypass grafting, admitted to Cardiology ward of Shariati hospital during the years 2007-2010. The ordinary logistic regression model and a classification tree were utilized for predicting the probability of death in these patients. The SPSS version 18.0 and CART version 6.0 were used for data analysis. In this study, the classification tree model (CART) resulted in an accuracy of 90%. The patients with renal insufficiency, intra-aortic balloon pump placement during and after surgery, prolonged ventilation, and perfusion time over 160 were shown as the high-risk groups, while those patients with heart ventricular post-operative complications regarded as the medium-risk group. The sensitivity and specificity indices for this model were 82% and 89%, respectively, while it was 80.4% and 88%, respectively, for logistic model. In the present study, the logistic and decision tree models led to nearly similar results, however, the decision tree model seemed to be more accurate. The IABP (Intra-Aortic Balloon Pump) was the most effective factor for mortality. The mortality rate due to this factor during and after surgery for all patients was 19% and 54.1%, respectively.