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24-h Glycaemic profiles in peritoneal dialysis patients and non-dialysis controls with advanced kidney disease

Williams, Jennifer, Gilchrist, Mark, Strain, William David, Fraser, Donald ORCID: and Shore, Angela 2022. 24-h Glycaemic profiles in peritoneal dialysis patients and non-dialysis controls with advanced kidney disease. Peritoneal Dialysis International 42 (5) , pp. 497-504. 10.1177/08968608211047787

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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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Additional Information: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (
Publisher: SAGE
ISSN: 0896-8608
Date of First Compliant Deposit: 16 March 2022
Date of Acceptance: 29 August 2021
Last Modified: 23 May 2023 15:15

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