To establish the incidence and patterns of renal fusion anomalies based on Ultrasonography (USG) in Western region of Nepal. In 2 years period, patients undergoing abdominal USG at Gandaki Medical College between 2010 and 2012 were screened for renal fusion anomalies. After identification, incidence and male:female ratio were stratified for total renal fusion anomalies, horseshoe kidney, crossed fused ectopia and fused pelvic kidney. Out of 31498 patients who underwent abdominal USG, there were 71(1:444) cases of renal fusion anomalies, 61 (1:516) of horseshoe kidneys, 9 (1:3500) of crossed-fused ectopia and 1 (1:31498) of fused pelvic kidney. Male:Female ratio was 1:2 for horseshoe kidney and 1.25:1 for crossed fused ectopia. Renal fusion anomalies are rare congenital malformation. USG is a sensitive and reliable modality for its detection. Horseshoe kidney is the most common renal fusion anomaly followed by crossed fused ectopia. Our ultrasonograhic evaluation for incidence of renal fusion anomalies closely matches past autopsy and radiographic data.

To compare abdominal visceral fat with subcutaneous fat in relation to their association with type 2 diabetes. Abdominal fat distribution was measured using Computed Tomography in 60 subjects (30 diabetics and 30 non-diabetics). Computed tomography images obtained at two intervertebral locations L2-L3 and L4-L5 were used to measure areas of total fat, visceral fat and subcutaneous fat using slice thickness of 5mm and attenuation range of -190 to -30 Hounsfield units. Data were analyzed using logistic regression. At L2-L3 level, taking visceral fat and subcutaneous fat as predictor variables, diabetes was correctly classified at 78.0% and 66.10% respectively. At L4-L5 level, taking visceral fat and subcutaneous fat as predictor variables, diabetes was correctly classified at 72.88% and 67.80% respectively. Regardless of the measurement site, visceral fat has significantly stronger association with diabetes, compared to subcutaneous fat. Visceral fat at L2-L3 level alone may be a better predictor of diabetes. Abdominal fat distribution, visceral fat, subcutaneous fat, type 2 diabetes.