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Updated: Aug 11, 2026

Generation of Hypoparathyroid Rats via Carbon-Nanoparticle-Assisted Parathyroidectomy
Published on: July 14, 2023
Body composition changes in haemodialysis patients with secondary hyperparathyroidism after parathyroidectomy
B S E Peters1, V Jorgetti, L A Martini
1Nutrition Department, School of Public Health, Sao Paulo University, Av. Dr. Arnaldo, 715, Cerqueira César, CEP 01 246-904, São Paulo, Brazil.
Abstract:
Considering the negative effects of secondary hyperparathyroidism (SHPT) in patients with chronic renal failure (CRF), the objective of the present study was to evaluate body composition changes using conventional and vector bioimpedance analysis in patients before and after parathyroidectomy (PTX). Twelve adult patients, mean age 43.4 (sd 12.7) years, were evaluated prior to and 6 months after PTX. Diets were assessed with 3 d dietary records, and mean energy, protein, calcium and phosphorus intake were estimated from these inventories. Weight, height, BMI and bioelectrical impedance were measured; and biochemical markers of nutritional status (albumin and total protein) and bone metabolism (calcium, phosphorus and intact parathyroid hormone) were determined. No significant differences were observed in mean energy, protein and phosphorus after surgery. There was a significant increase in calcium intake after PTX (382.3 (sd 209.6) mg to 656.6 (sd 313.8) mg; P<0.05). Mean weight, BMI, conventional bioelectrical impedance measurements, total body fat, lean body mass and total body water were unaffected by surgery. However, the phase angle and reactance significantly increased after PTX (5.0 degrees (sd 1.4) to 5.6 degrees (sd 1.3); 44.1 (sd 15.6) Omega to 57.1 (sd 14.4) Omega, respectively). The high levels of intact parathyroid hormone before surgery had a negative effect on total body fat (r -0.69, P<0.05). After PTX, the mean albumin significantly increased (3.9 (sd 0.4) g/dl to 4.2 (sd 0.6) g/dl; P<0.05). PTX for SHPT is associated with certain changes in laboratory values, dietary intake and body composition. The latter is best seen with bioimpedance vector analysis.
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