ESPE2022 Rapid Free Communications Early Life and Multisystem Endocrinology (6 abstracts)
Background and Objective: Continuous Glucose Monitoring (CGM) is gaining in popularity for patients with paediatric hypoglycaemia disorders such as Congenital Hyperinsulinism (CHI), but no standard measures of accuracy or associated clinical risk are available. A small number of studies have shown suboptimal accuracy of CGM in CHI but assessments have been inconsistent, incomplete and offer no measure of clinical application. Error grids that categorise clinical risk from use of CGM were designed for use in diabetes and have no applicability to patients with hypoglycaemia disorders. We aimed to develop a novel Hypoglycaemia Error Grid (HEG) for CGM assessment for those with CHI based on expert consensus opinion and apply this to a large paired (CGM/blood glucose) dataset to derive expert-informed clinical risk.
Design and Methods: Paediatric endocrinologists managing CHI in the two UK centres of excellence were asked to complete a questionnaire regarding glucose cutoffs and associated anticipated risks of CGM errors in a hypothetical model. Collated information was processed to calculate risk for 10,000 theoretical CGM vs glucometer combinations and, from these, the HEG was computationally generated before final expert confirmation of risk boundaries. Ten patients with CHI underwent 12 weeks of monitoring with a Dexcom G6 CGM and self-monitored blood glucose (SMBG) with a Contour Next One glucometer to test application of the HEG and provide data for accuracy calculations.
Results: Based on 1441 paired values of CGM and SMBG (mean absolute time difference 1.3 minutes), device accuracy was suboptimal: Mean Absolute Relative Difference (MARD) of 19.3%, mean absolute difference of 0.93mmol/l and hypoglycaemia (glucose <3.5mmol/L) sensitivity of only 45%. Mean difference between CGM and SMBG was 0.43mmol/l demonstrating a mean over-reading of CGM devices. The HEG provided clinical context to CGM errors and contrasting risk profiles with existing diabetes error grids, reinforcing its utility in hypoglycaemia.
Conclusions: The HEG, based on UK expert consensus opinion, offers a standardised method for CGM accuracy analysis in patients with hypoglycaemia disorders and can be applied to historic and future datasets. Application in the largest ever paired CGM and SMBG dataset in patients with CHI has demonstrated inadequate accuracy of CGM to recommend as a standalone tool for routine clinical use. However, suboptimal accuracy of CGM relative to SMBG does not detract from the use as a digital phenotyping tool.
15 Sep 2022 - 17 Sep 2022