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Published on: July 19, 2018
Change in adiposity indices after 1 year of peritoneal dialysis: a single-center cohort study
Zhikai Yang1,2, Jack Kit-Chung Ng1,2, Winston Wing-Shing Fung1
1Carol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Background:
Weight gain is common after starting peritoneal dialysis (PD). Several adiposity indices have been developed recently as potential indicators of visceral adiposity and lipid accumulation. We aim to investigate the prevalence and prognostic implications of the change in adiposity indices after 1 year of PD.
Methods:
We recruited 110 patients treated with PD for 12 months. Adiposity indices, including triglyceride glucose index, lipid accumulation product, visceral adiposity index and conicity index, were measured at baseline and then 1 year after PD started. The relation between their changes (Δ) and other clinical and biochemical parameters, as well as survival and hospitalization rates were analyzed.
Results:
After 1 year of PD, more than half of the patients had increased adiposity indices. The change in adipose tissue mass significantly correlated with the concomitant changes in triglyceride glucose index (ΔTyGI) (r = 0.25, P = .01), lipid accumulation product (ΔLAP) (r = 0.27, P = .007) and visceral adiposity index (ΔVAI) (r = 0.26, P = .01). ΔTyGI significantly correlated with the change in insulin resistance as represented by homeostasis model assessment of insulin resistance (HOMA-IR) (r = 0.22, P = .02), while ΔLAP and change in conicity index (ΔCI) correlated with the changes in various anthropometric parameters. However, no indices variation was associated with patient survival, technique survival or hospitalization rate.
Conclusions:
Increased adiposity indices were common after 1 year of PD. The changes in adiposity indices had variable correlation with the change in adipose tissue mass, insulin resistance and anthropometric parameters. Further studies are required to identify simple metabolic parameters with a prognostic impact that could be suitable for serial monitoring.
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