Diabetes mellitus type 2 (T2DM) is a chronic and progressive condition, which affects people all around the world. The risk of complications increases with age if the disease is not managed properly. Diabetic neuropathy is caused by excessive blood glucose and lipid levels, resulting in nerve damage. Apelin is a peptide hormone that is found in different human organs, including the central nervous system and adipose tissue. The aim of this study is to estimate Apelin levels in diabetes type 2 and Diabetic peripheral Neuropathy (DPN) Iraqi patients and show the extent of peripheral nerve damage. The current study included 120 participants: 40 patients with Diabetes Mellitus, 40 patients with Diabetic peripheral Neuropathy, and 40 healthy persons as control, the age range of 34-66 years, matched in age and sex. For all groups, fasting blood sugar, lipid profile (Cholesterol, Triglyceride, High-density lipoprotein, Low-density lipoprotein, and very-low-density lipoprotein), HbA1c, serum total Apelin levels, BMI, and Waist to Hip Ratio were calculated. The results showed highly increase in Apelin levels in neuropathy patients 670.4 ± 41.67 pg/ml compared to diabetes patients 247.6 ± 20.37 pg/ml nd healthy people 208.02 ± 8.30 pg/ml with a P value=0.001. Body Mass Index showed increase in diabetic and neuropathy patients compared with control group 31.05 ± 1.01 kg/m2, 31.05 ± 0.73 kg/m2, versus 23.92 ± 0.16 kg/m2, respectively, with a P value=0.001. The result showed a significant increase in lipid profile with p≤0.05, except HDL which showed a significant decrease p≤0.05. The present study concluded that incremented Apelin levels have an important role in Neuropathy pathogenesis and could determine the extent of peripheral nerve damage by the high levels in the blood due to their presence in the central nervous system. Also, increasing BMI, excessive lipid, and duration of disease showed a progressive role in DM and neuropathy and cause damage to the nerves, and play roles in the development of complications.
The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
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