Abstract

Text-Size + –

• INTRODUCTION:

  Obese patients are at increased risk for renal stones as well as treatment failures due to increased skin-to-stone distances (SSD) and harder stone compositions. We investigated the relationships between obesometric parameters (body mass index [BMI], body fat distribution and obesity-related hormone levels) with SSD and stone hardness.

  MATERIALS AND METHODS:

  We prospectively enrolled patients undergoing stone interventions at our institution. Computed tomography (CT) scans were analyzed; adipose tissue was identified according to Hounsfield units (HU) and separated into subcutaneous (SAT) and visceral (VAT) components. The pixels were averaged at three levels to calculate fat distribution: %VAT = (VAT)/(VAT + SAT). SSD was measured and HU were used as a surrogate for stone hardness. Obesity-related hormones leptin and adiponectin were measured by ELISA.

  RESULTS:

  Seventy-nine patients were prospectively enrolled. Mean BMI and %VAT were 30.02 kg/m2 and 40.13 kg/m2. Mean leptin and adiponectin levels were 17.5 ng/mL and 7.67 mcg/mL indicating high risk for metabolic consequences of obesity. Females had greater proportions of subcutaneous fat than males (%VAT 28.4 versus 46.94, p < 0.001) and greater SSD (11.26 cm versus 9.86 cm, p = 0.025). Among obese patients, subcutaneous fat correlated with SSD independently of BMI (r = 0.454, p = 0.008). Obese patients with %VAT > 40 versus < 40 had SSD of 11.35 cm versus 13.7 cm (p = 0.005). Diabetics had harder stone compositions as measured by HU than non-diabetics (982.86 versus 648.86, p = 0.001).

  CONCLUSION:

  Obesometric parameters such as BMI, body fat distribution, and the presence of diabetes mellitus are important considerations in the management of renal stone disease. A large proportion of subcutaneous fat, which can be estimated by physical examination, predicts SSD among obese patients and may aid treatment decisions in patients, particularly those without pre-treatment CT scans. Further studies are needed to refine the role of obesometrics in personalizing treatment decisions.