Abstract

Malnutrition is widely prevalent in patients with chronic kidney disease. Our primary objective was to assess the utility of subjective global assessment (SGA) as an indicator of malnutrition in patients with diabetic nephropathy. This pilot study evaluated the extent of malnutrition, using a combination of SGA, anthropometric, and biochemical parameters. Malnutrition, although commonly noticed in patients during routine clinical observation of diabetic nephropathy patients, has not been estimated. Moreover, there is no single "gold standard" method to identify malnutrition. The SGA method was performed to evaluate nutritional status in 40 patients with diabetic nephropathy (23 men and 17 women) examined consecutively in the out patient department of Government Medical College and Hospital (Chandigarh, India). Patients with kidney disease not attributable to diabetes, and with conditions leading to acute morbidity such as infections, elevated body temperature, respiratory and gastrointestinal distress, or wounds, were excluded. Anthropometric parameters such as body mass index, triceps skinfold (TSF), biceps skinfold (BSF), midarm circumference (MAC), and midarm muscle circumference (MAMC), along with biochemical parameters such as hemoglobin, fasting blood sugar, serum albumin, and lipid profile, were measured. Malnutrition was identified in 63% of patients: mild to moderate in 48%, and severe in 15%. The measured parameters showed no significant gender-based differences. In SGA grade C patients (severely malnourished), TSF, MAC, and MAMC were significantly reduced. Biochemical parameters did not show any significant change across nutritional grades, except for hemoglobin, which showed a significant reduction with advanced malnutrition. Nutritional status as determined by SGA is a useful and reliable index for identifying patients at risk for malnutrition. Our data confirm that a high degree of malnutrition was prevalent in patients with diabetic nephropathy, as shown by anthropometric and biochemical variables. Therefore, we suggest that these parameters be integrated in regular assessment to determine malnutrition.

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