A retrospective in‐depth analysis of continuous glucose monitoring datasets for patients with hepatic glycogen storage disease: Recommended outcome parameters for glucose management

Abstract

Continuous glucose monitoring (CGM) systems have great potential for real‐time assessment of glycemic variation in patients with hepatic glycogen storage disease (GSD). However, detailed descriptions and in‐depth analysis of CGM data from hepatic GSD patients during interventions are scarce. This is a retrospective in‐depth analysis of CGM parameters, acquired in a continuous, real‐time fashion describing glucose management in 15 individual GSD patients. CGM subsets are obtained both in‐hospital and at home, upon nocturnal dietary intervention (n = 1), starch loads (n = 11) and treatment of GSD Ib patients with empagliflozin (n = 3). Descriptive CGM parameters, and parameters reflecting glycemic variation and glycemic control are considered useful CGM outcome parameters. Furthermore, the combination of first and second order derivatives, cumulative sum and Fourier analysis identified both subtle and sudden changes in glucose management; hence, aiding assessment of dietary and medical interventions. CGM data interpolation for nocturnal intervals reduced confounding by physical activity and diet. Based on these analyses, we conclude that in‐depth CGM analysis can be a powerful tool to assess glucose management and optimize treatment in individual hepatic GSD patients.

Glycogen Storage Disease Type Ia: Current Management Options, Burden and Unmet Needs

“…CGM is an increasingly accurate and powerful tool for monitoring daily fluctuations in blood glucose levels widely used in patients with type I diabetes [49,66]. Several published studies have assessed the utility of CGM in a number of GSDs, including a clinical trial of patients with GSD type I [56,61,[66][67][68][69]. Of note, studies performed pre-2015 used first-or second-generation CGM devices; these were less accurate than newer models, and results should be interpreted with caution.…”

“…Of note, studies performed pre-2015 used first-or second-generation CGM devices; these were less accurate than newer models, and results should be interpreted with caution. Measurement errors and physiological differences between capillary blood and interstitial fluid glucose levels affect CGM accuracy, and both prospective and validation studies must be performed to determine reference values for CGM outcome parameters and to correct for intra-patient variation [56]. The amount of subcutaneous fat affects the accuracy of CGM, which is an important consideration when monitoring infants and patients with increased BMI [56].…”

“…Measurement errors and physiological differences between capillary blood and interstitial fluid glucose levels affect CGM accuracy, and both prospective and validation studies must be performed to determine reference values for CGM outcome parameters and to correct for intra-patient variation [56]. The amount of subcutaneous fat affects the accuracy of CGM, which is an important consideration when monitoring infants and patients with increased BMI [56]. CGM may alleviate some of the burden of glucose monitoring by fingertip prick tests, but these remain the standard approach in many countries at present.…”

“…Blood glucose monitoring most often takes the form of capillary blood glucose tests (self-monitoring of blood drop samples, usually collected from fingertip pricks [55], 3-6 times per day) or 24-h continuous glucose monitoring (CGM) via a disposable sensor placed on the back of the arm or abdomen. However, CGM may be limited by regional availability and/or reimbursement by insurance or government-funded health care [55,56]. Blood glucose monitoring should be performed to establish the initial diet prescription.…”

The Need to Pair Molecular Monitoring Devices with Molecular Imaging to Personalize Health

“…As another example, glucose monitoring is critical to diabetes management and the role of glucose utilization as a pathogenic biomarker for of a variety of diseases, including kidney diseases, [31,32] neurological conditions, [33,34] and hepatic diseases [35] is well characterized. Through the facile immobilization and implementation of glucose oxidase (GOx) for electrochemical sensing, a range of architectures for electrochemical glucose biosensing have been implemented, including transdermal glucose monitoring.…”