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Published on: July 19, 2018
24-h Glycaemic profiles in peritoneal dialysis patients and non-dialysis controls with advanced kidney disease
Jennifer Williams1, Mark Gilchrist1, William David Strain1
1Diabetes and Vascular Medicine Research Centre, NIHR Exeter Clinical Research Facility, University of Exeter College of Medicine and Health, UK.
Background:
For patients on peritoneal dialysis (PD), the deleterious effects of high concentrations of dialysate glucose on the peritoneal membrane are well-documented. Systemic effects of peritoneally absorbed glucose are more poorly defined. Using continuous glucose monitoring (CGM), we aimed to describe 24-h glycaemic profiles of PD patients without diabetes and compare with non-dialysis controls with stage 5 chronic kidney disease (CKD-5).
Methods:
In this cross-sectional, case-control study, 15 patients on PD (9 automated PD (APD) and 6 continuous ambulatory PD (CAPD)) and 16 CKD-5 controls underwent 72 h of CGM and metabolic profiling. CGM was used to derive average glucose concentrations and within-participant standard deviation (SD) of glucose. Data were analysed for the whole 72-h monitoring period and as daytime (09.00 to 21.00) and night-time (21.00 to 09.00).
Results:
Average glucose concentrations and within-participant SD of glucose for the whole monitoring period were not different between the three groups (p ≥ 0.5). Daytime average glucose concentrations were also similar across the three groups (p = 0.729). APD was associated with a significantly higher nocturnal glucose than CAPD (5.25 mmol/L ± 0.65 vs. 4.28 ± 0.5, p = 0.026). A significant drop in nocturnal glucose compared with daytime average seen in both CAPD patients and controls was absent in APD patients.
Conclusions:
Systematically different glycaemic patterns were observed in non-diabetic APD and CAPD patients, including an absence of physiological nocturnal glucose dipping in patients on APD. Comprehensive CGM data sets highlight subtleties not appreciated by traditional metabolic biomarkers; this has implications when choosing the most appropriate outcome measures in future research addressing the metabolic impact of PD.
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