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

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.

A preliminary study of telemedicine for patients with hepatic glycogen storage disease and their healthcare providers: from bedside to home site monitoring.

BACKGROUND: The purpose of this project was to develop a telemedicine platform that supports home site monitoring and integrates biochemical, physiological, and dietary parameters for individual patients with hepatic glycogen storage disease (GSD). METHODS AND RESULTS: The GSD communication platform (GCP) was designed with input from software developers, GSD patients, researchers, and healthcare providers. In phase 1, prototyping and software design of the GCP has occurred. The GCP was composed of a GSD App for patients and a GSD clinical dashboard for healthcare providers. In phase 2, the GCP was tested by retrospective patient data entry. The following software functionalities were included (a) dietary registration and prescription module, (b) emergency protocol module, and (c) data import functions for continuous glucose monitor devices and activity wearables. In phase 3, the GSD App was implemented in a pilot study of eight patients with GSD Ia (n = 3), GSD IIIa (n = 1), and GSD IX (n = 4). Usability was measured by the system usability scale (SUS). The mean SUS score was 64/100 [range: 38-93]. CONCLUSIONS: This report describes the design, development, and validation process of a telemedicine platform for patients with hepatic GSD. The GCP can facilitate home site monitoring and data exchange between patients with hepatic GSD and healthcare providers under varying circumstances. In the future, the GCP may support cross-border healthcare, second opinion processes and clinical trials, and could possibly also be adapted for other diseases for which a medical diet is the cornerstone.

Clinical and biochemical heterogeneity between patients with glycogen storage disease type IA: the added value of CUSUM for metabolic control.

OBJECTIVE: To study heterogeneity between patients with glycogen storage disease type Ia (GSD Ia), a rare inherited disorder of carbohydrate metabolism caused by the deficiency of glucose-6-phosphatase (G6Pase). STUDY DESIGN: Descriptive retrospective study of longitudinal clinical and biochemical data and long-term complications in 20 GSD Ia patients. We included 11 patients with homozygous G6PC mutations and siblings from four families carrying identical G6PC genotypes. To display subtle variations for repeated triglyceride measurements with respect to time for individual patients, CUSUM-analysis graphs were constructed. RESULTS: Patients with different homozygous G6PC mutations showed important differences in height, BMI, and biochemical parameters (i.e., lactate, uric acid, triglyceride, and cholesterol concentrations). Furthermore, CUSUM-analysis predicts and displays subtle changes in longitudinal blood triglyceride concentrations. Siblings in families also displayed important differences in biochemical parameters (i.e., lactate, uric acid, triglycerides, and cholesterol concentrations) and long-term complications (i.e., liver adenomas, nephropathy, and osteopenia/osteoporosis). CONCLUSIONS: Differences between GSD Ia patients reflect large clinical and biochemical heterogeneity. Heterogeneity between GSD Ia patients with homozygous G6PC mutations indicate an important role of the G6PC genotype/mutations. Differences between affected siblings suggest an additional role (genetic and/or environmental) of modifying factors defining the GSD Ia phenotype. CUSUM-analysis can facilitate single-patient monitoring of metabolic control and future application of this method may improve precision medicine for patients both with GSD and remaining inherited metabolic diseases.

A Prospective Study on Continuous Glucose Monitoring in Glycogen Storage Disease Type Ia: Toward Glycemic Targets.

CONTEXT: Although previous research has shown the benefit of continuous glucose monitoring (CGM) for hepatic glycogen storage diseases (GSDs), current lack of prospectively collected CGM metrics and glycemic targets for CGM-derived outcomes in the hepatic GSD population limits its use. OBJECTIVE: To assess CGM metrics for glycemic variation and glycemic control in adult patients with GSDIa as compared to matched healthy volunteers. DESIGN: Prospective CGM data were collected during the ENGLUPRO GSDIa trial (NCT04311307) in which a Dexcom G6 device was used. Ten adult patients with GSDIa and 10 age-, sex- and body mass index-matched healthy volunteers were enrolled. Capillary blood glucose was concurrently measured during 2 standardized 2-hour time intervals. Descriptive [eg, glycemic variability (GV), time below range, time in range (TIR), time above range (TAR)] and advanced (ie, first- and second-order derivatives, Fourier analysis) CGM outcomes were calculated. For each descriptive CGM outcome measure, 95% CIs were computed in patients with GSDIa and healthy volunteers, respectively. RESULTS: CGM overestimation was higher under preprandial and level 1 hypoglycemia (ie, capillary glucose values ≥ 3.0 mmol/L and < 3.9 mmol/L) conditions. GV and TAR were higher while TIR was lower in patients with GSDIa compared to healthy volunteers (P < 0.05). Three patients with GSDIa showed descriptive CGM outcomes outside the calculated 95% CI in GSDIa patients. Advanced CGM analysis revealed a distinct pattern (ie, first- and second-order derivatives and glucose curve amplitude) in each of these 3 patients within the patients group. CONCLUSIONS: This is the first study to prospectively compare CGM outcomes between adult patients with GSDIa and matched healthy volunteers. The generation of a set of CGM metrics will provide guidance in using and interpreting CGM data in GSDIa and will be useful for the definition of glycemic targets for CGM in patients with GSDIa. Future studies should investigate the prognostic value of CGM outcomes and their major determinants in patients with GSDIa.