الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Increased BMI is a major health problem all over the world. Obesity is defined as an excess body fat and BMI is the best and the most commonly used method to assess overweight and obesity worldwide. Metabolic syndrome is one of the major consequences of obesity. Both obesity and metabolic syndrome can affect the kidneys leading to an ESRD by inducing podocytopathy.
In this study the aim was to assess the relation between podocytopathy and high body mass index in metabolic syndrome patients with normal or impaired kidney functions by using urinary podocalyxin and urinary nephrin for early detection and disease progression.
This cross-sectional study was conducted on 80 subjects taken from Alexandria Main University Hospitals inpatient ward and outpatient clinics. They were divided into two groups group A: 40 patients with body mass index equal or above 25 with metabolic syndrome and with normal renal functions and group B: 40 patients the same as group A but with nephropathy with further subdivision into group BI and BII, where group BI (24 patients) had normal serum creatinine and taking ACEi or ARBs with previous history of proteinuria or currently proteinuric with UACR more than 30 and group BII (16 patients) had increased serum creatinine with reduction of GFR till stage 4 CKD with or without proteinuria and with or without being on ACEi or ARBs medications.
All groups were subjected to full detailed history taking, complete physical examination (vital signs, head and neck, chest, abdomen and pelvis, extremities and checking for lymph nodes) with assessment of body mass index and laboratory investigation (CBC, ESR, HbA1C, total serum cholesterol, HDL, LDL, serum triglycerides, blood urea, serum creatinine, ALT, AST, complete urine analysis, UACR, urinary Nephrin and urinary podocalyxin) to assess the inclusion and exclusion criteria.
The results of this study showed that:
UACR can statistically differentiate between group A and either of group BI or BII at the cut point 30 with 77 % sensitivity and 100 % specificity with PPV 100% and NPV 81.6% by using ROC analysis with p value < 0.001. it also can differentiate between group BI and group BII but at the cut point 17 with 90 % sensitivity and 82.5 % specificity with PPV 83.7 % and NPV 89.2% by using ROC analysis with p value < 0.031. While PCX showed that it can statistically differentiate between group BI and BII at the suggested cut point 285 pg/ml with 52% sensitivity and 45 % specificity with low PPV 48.8% and NPV 48.6% by using ROC analysis with p value 0.008, but it can’t statistically differentiate between group A and neither of group BI nor BII as it was 100% positive in all patient groups with p value 0.6.