Training and Evaluation of a Breath-Based Glucose Estimation Algorithm in People With Type 2 Diabetes: The BOYDSense-GM Study.

ABSTRACT:

Background

Type 2 diabetes (T2D) is a growing global health concern, with self-monitoring of blood glucose (SMBG) being essential for optimal management. Current SMBG methods are invasive and often underutilized due to discomfort and inconvenience. Non-invasive alternatives, such as breath-based glucose estimation using volatile organic compounds (VOC), could improve compliance and quality of life.

Methods

A prospective, cross-sectional, single-center clinical study enrolled 130 adults with T2D not requiring prandial insulin. The study was conducted in two phases: algorithm training (n = 100) and validation (n = 30). Participants underwent a standardized meal test with venous, capillary, and breath VOC measurements at seven time points. A portable VOC analyzer

SUBMITTER: Gourdy P 

PROVIDER: S-EPMC12945738 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature