The correlation between obesity and coronary artery disease (CAD) has been well-documented in the literature. Body mass index, waist–height ratio, waist–hip ratio, body adiposity index, body shape index, waist circumference, and hip circumference are traditional obesity parameters used to measure obesity. This study aimed to investigate the role of these traditional obesity parameters in the prediction of the number of stenosed coronary arteries (≥ 60%) among patients undergoing cardiac catheterization. A descriptive cross-sectional study was conducted among 220 hospitalized patients undergoing cardiac catheterization in two hospitals in Jordan. Bivariate Pearson’s correlation and forward linear regression analysis were used in the current study. Hip circumference was identified as being the best predictor of CAD (r = 0.5), with the best cut-off value of 103 cm (sensitivity = 0.92, specificity = 0.58). Hip circumference had significant regression levels with the number of stented coronary arteries (P = 0.002) and the number of severe stenosed coronary arteries (P = 0.04). The second-best obesity parameter in predicting CAD was waist circumference (r = 0.4), with a cut-off value of 0.95 m (sensitivity = 0.76, specificity = 0.68). High-sensitivity C-reactive protein (HS-CRP), triglycerides, and smoking had significant positive correlations with the number of stented coronary arteries (P < 0.05). Hip circumference of ≥ 103 cm, increased serum level of triglycerides, HS-CRP, and being a smoker are all factors which can predict CAD or the risk of developing it.

Background. Obesity has been reported to be associated with frailty and coronary artery disease (CAD). Objective. The present study aimed to investigate the role of the seven traditional obesity parameters body mass index (BMI), waist-height ratio (WHtR), waist-hip ratio (WHR), body adiposity index (BAI), body shape index (BSI), waist circumference (WC), and hip circumference (HC) in the prediction of frailty among CAD patients undergoing cardiac catheterization. Design. A secondary data analysis was conducted. Setting. Three main hospitals were located at the northern and middle regions of Jordan. Participants. 220 hospitalized patients undergoing cardiac catheterization were recruited. Measurements. The traditional obesity parameters were measured using an anthropometric tape and weight scale and frailty was measured using the Tilburg Frailty Indicator (TFI). Data were analyzed using bivariate Pearson’s correlation and forward linear regression analysis. Results. Total cholesterol, HC, triglycerides, age, random blood sugar, and WC had significant positive associations with and were predictors of frailty ( p < 0.05 ). The model of the seven predictors explained 32.4% of the variance in frailty ( p = 0.02 ). Conclusion. The incidence of frailty can be predicted by the increase in total cholesterol, HC, triglycerides, age, random blood sugar, and WC. The results of this study may help healthcare providers, including nurses, to identify the factors that could lead to frailty among CAD patients undergoing cardiac catheterization.

Abstract-Machine translation (MT) allows direct communication between two persons without the need for the third party or via dictionary in your pocket, which could bring significant and per formative improvement. Since most traditional translational way is a wordsensitive, it is very important to consider the word order in addition to word selection in the evaluation of any machine translation. To evaluate the MT performance, it is necessary to dynamically observe the translation in the machine translator tool according to word order, and word selection and furthermore the sentence length. However, applying a good evaluation with respect to all previous points is a very challenging issue. In this paper, we first summarize various approaches to evaluate machine translation. We propose a practical solution by selecting an appropriate powerful tool called iBLEU to evaluate the accuracy degree of famous MT tools (i.e. Google, Bing, Systranet and Babylon). Based on the solution structure, we further discuss the performance order for these tools in both directions Arabic to English and English to Arabic. After extensive testing, we can decide that any direction gives more accurate results in translation based on the selected machine translations MTs. Finally, we proved the choosing of Google as best system performance and Systranet as the worst one.

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D. Differences in the number of stented coronary arteries based on the seven traditional obesity parameters among patients with coronary artery diseases undergoing cardiac catheterization.