Objective: To determine the effectiveness of hypothermia on renal functions for patients undergoing
coronary artery bypass graft CABG surgery.
Methodology: A purposive (non-probability) sample of (50) patients undergoing Isolated coronary artery
bypass graft surgery consecutively admitted to the surgical ward, and they were followed up in the
intraoperative, Intensive Care Unit (ICU) and in the postoperative (surgical ward). Post-operative renal function
test (glumeruler filteration rate (GFR) by using the Crockroft-Gault formula and serum creatinine level) was
determined first week post operative and post operative renal function was classified on the base of peak of
the serum creatinine level and decline of glomeruler filteration rate(GFR) as following : normal renal function
serum creatinine concentration and decline in(GFR) less than 25% from preoperative, moderate renal
dysfunction increase serum creatinine concentration and decline in(GFR) 25%-50% from preoperative, sever
renal dysfunction increase serum creatinine concentration and decline in(GFR) more than 50% from
preoperative test.
Results: results of this study show that (78%) from the sample develop post operative renal dysfunction and
the highly percentage of them are male (50%), advance age 60-70 (60%), smoking (47.0%), diabetes mellitus
DM (68%), cardiopulmonary bypass 180 and more (57.20%), New York Heart Association calcification NYHA
class III(47.5%) and patient without Intra Aortic Balloon Pump IABP(50,0%) . We conclude from the study that
highly percentage of patient undergoing isolated CABG may develop postoperative renal dysfunction even
when using hypothermic strategy as a protective measure and the patients with DM, male, advance age,
smoker, prolong time of CPB (more than 180 minutes), NYHA class III and patient without IABP are considered
as patient at high risk to develop postoperative renal dysfunction.
Recommendations: The researcher recommended that to find addition strategy rather than hypothermia
to protect renal function especially with the high risk patients during isolated CABG surgery.
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
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Background: Varicose vein (VV) is a common problem that mostly occurs in legs. This medical condition can influence the quality of life and working condition of nurses. Aim of the study: To estimate the prevalence of lower limbs varicosity and its associated risk factors among nurses. Methods: This a cross-sectional descriptive study was carried out among 100 nurses working Baghdad Teaching Hospital, Surgical Specialties Hospital, and Al- Kidney Teaching Hospital, Baghdad, Iraq from January 1st to May 10th, 2022. The participants were recruited in the study using systematic random sampling. The Occupational Sitting and Physical Activity and Aberdeen Varicose Vein Questionnaires were used for data gathering. Results: The prevalence o
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This paper aims to find new analytical closed-forms to the solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func