Diabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, blood glycated hemoglobin(HbA1c), and serum glucose, creatinine(SCr), lipid profile, CysC, KIM-1 were assayed, and the estimated glomerular filtration rat (eGFR) was calculated. When compared to the normoalbuminuric group, the DKD group had significantly greater prevalence of retinopathy, and significantly elevated HbA1c and total cholesterol values. Also had significantly greater serum levels of KIM-1 and CysC, and there is a significant (P-value< 0.01) positive correlation between them. In contrast, GFR was significantly higher in normoalbuminuric group and was significantly negatively correlated with both CysC and KIM-1. Multiple linear regression analysis, found that there were a significant positive association between CysC, KIM-1 and ACR. ROC analysis reveal that eGFR had the highest area under the curve(AUC=0.717), while SCr had the lowest AUC(0.556). In conclusion, Serum KIM-1 and CysC levels consider as early biomarker for DKD along with eGFR that consider the best diagnostic indicator of DKD, Additionally, there is a strong correlation between serum CysC and KIM-1 as well as other renal measures that indicate deteriorating kidney function.
Water balance as a technique is considered one of the means that is relied upon in solving significant hydrological problems. The soil and water assessment tool (SWAT) model was used in this study to assess the water balance in the Wadi Al-Mohammadi basin located at the eastern edge of the Western Desert. Digital elevation model, soil data, Land use - Land cover, and climate data represent the most important requirements for the SWAT model's input as a database. The Wadi Al-Mohammadi basin delineation results show the overall drainage area was 2286.8 km2 with seven sub-basins. The trend line of climate data indicates a clear increase in the total rainfall, relative humidity, temperature, and solar radiation from 1990-
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