[ effect of two methods, follow-up care by telephone and short message services on prothrombin time in patients with valve replacement surgery in hospitals of Tehran]

The aim of anticoagulant therapies is maintaining the blood level of drug for prevention of thrombotic accident without bleeding. One of the main components in coagulation system management after cardiac valve replacement surgery is to increase patients' knowledge about thess drugs. The aim of this study was to compare the effectiveness of two methods of follow-up: short message service and telephone follow-up care on prothrombin time in patients after cardiac valve replacement surgery. This clinical trial study was done on patients admitted for valve replacement in Tehran selected hospitals in 2011. 99 patients were selected through purposive sampling and then were randomly allocated to telephone, short message services and control groups. In each group 33 patients were studied. After completing the demographic questionnaire, patients' prothrombin time was measured and recorded at discharge time and 3 months later. The booklet and oral training were presented to all of the patients before discharge. Telephone follow-up group were called within the first month twice a week and in the second and third month once a week. One message was sent daily to the patients in Short message services followup group. For data analysis SPSS 17, descriptive statistical test, Chi-square, paired TTest and one way ANOVA were used. The one way ANOVA test showed no significant difference between the means of prothrombin time in telephone follow-up, short message services follow-up and control groups after intervention [P=0.87]. Results showed that the effect of two methods in controlling the prothrobin time was the same, but according to low cost and easiness of SMS, the application of this method should be considered in cardiac center.

Urban expansion simulation using geospatial information system and artificial neural networks

Urban Expansion Model [UEM] was adapted to simulate urbanization which implements Geospatial Information Systems [GIS], Artificial Neural Networks [ANNs] and Remote Sensing [RS]. Two satellite imageries with specific time interval, socio-economic and environmental variables have been employed in order to simulate urban expansion. Socio-economic and environmental variables were used as inputs while construction and non-construction areas were used as outputs to train the neural network. Calibration of proposed model was performed with area under the ROC Curve [AROC] and Kappa Statistic [KS] which are non-shape performance metric. A real-life case study of Tehran Metropolitan Area [TMA] is presented to demonstrate the process. This paper presents a version of the UEM which parameterized for TMA and explores how factors such as road, building area, service centre, green space, elevation, aspect and slope can influence urbanization. Having urban expansion model with specific time interval and assuming the existence of the same rate of urbanization, new construction areas of region can be predicted. The overall accuracy of the model to predict new construction areas was 80% and 78% with AROC and KS, respectively