Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.

ABSTRACT:

Introduction

Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.

Research design and methods

Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative sco

SUBMITTER: Dawnbringer J 

PROVIDER: S-EPMC11381645 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature