An increasing proportion of perinephric to subcutaneous fat is associated with adverse perioperative outcomes of robotic partial nephrectomy

Jay D. Raman, Christopher Reynolds, Michael Hannon

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

To investigate the association of perinephric fat (PF) thickness and the ratio of perinephric to subcutaneous fat (PF:SF) thickness on perioperative outcomes following robotic partial nephrectomy (RPN), 240 patients undergoing RPN with preoperative computed tomography (CT) axial imaging were included. Perinephric and subcutaneous fat thickness was measured at the level of the renal vein and umbilicus, respectively. The association between PF thickness and PF:SF ratio and perioperative outcomes was determined by Spearman correlation and logistic regression. 121 men and 119 women with a median age of 55 years, BMI of 32, tumor size of 2.6 cm, and RENAL nephrometry score of 6 were included. On preoperative imaging, median PF thickness was 2.2 cm, SF thickness was 3.1 cm, and PF:SF ratio was 0.63. There were statistically significant positive correlations between PF thickness (Spearman correlation coefficient = 0.26, p = 0.001) and PF:SF ratio (Spearman correlation coefficient = 0.33, p < 0.0001) with longer operative duration of RPN. In addition, an increasing PF:SF ratio was associated with a greater risk of perioperative complications (OR = 1.82, 95 % CI 1.1–3.0, p = 0.02). No association was observed with respect to ischemia time, blood loss, length of stay, or margin status. PF thickness is associated with longer OR duration, and a greater PF:SF ratio correlated with increased OR duration and complications following RPN. These easily measured indices of fat distribution are likely more accurate in predicting perioperative outcomes after RPN than BMI alone.

Original languageEnglish (US)
Pages (from-to)255-259
Number of pages5
JournalJournal of Robotic Surgery
Volume10
Issue number3
DOIs
StatePublished - Sep 1 2016

All Science Journal Classification (ASJC) codes

  • Surgery
  • Health Informatics

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