Background: The highest concentrations of
blood glucose during the day are usually found
postprandialy. Postprandial hyperglycemia (PPH)
is likely to promote or aggravate fasting
hyperglycemia. Evidence in recent years suggests
that PPH may play an important role in functional
& structural disturbances in different body organs
particularly the cardiovascular system.
Objective: To evaluate the effect of (PPH) as a
risk factor for coronary Heart disease in Type 2
diabetic patients.
Methods: Sixty-three type2 diabetic patients
were included in this study. All have controlled
fasting blood glucose, with HbA1c correlation.
They were all followed for five months period
(from May to October 2008). A two hour
postprandial glucose (PPG) was done for all. Other
risk factors were taken in consideration such as
hypertension, obesity, and dyslipidemia. The study
was performed on those patients after at least three
months of controlled fasting blood glucose. ECG
was done to all of them.
Results : Out of the 63 type 2 diabetic patients,
20 had normal PPG and HbA1c levels, one of them
(5%), has ischemic changes on ECG twenty
patients had normal HbA1c & High PPG with 7
(35%) of them showed ischemic changes on ECG
17 patients showed a high PPG and a high HbA1c
with four of them showed ischemic changes on
ECG P<0.05. The remaining 6 patients had normal
PPG but high HbA1c & also only one of them
showed ischemic changes on ECG.
Conclusion This study showed that PPH is a
significant risk factor for ischemic heart disease
(IHD).
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Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
... Show MoreGenerally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co
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