Biases in Glucose Metrics Are Directly Related to Low Coverage of Continuous Glucose Monitoring: Insights from Diverse Populations
Year: 2025
Type: article
Study design: Observational Study
Abstract: The aim was to investigate the association between continuous glucose monitoring (CGM) data coverage and glycemic metrics. This study included over 97,000 clinical study participants and real-world data from type 1 or type 2 diabetes treated with multiple daily insulin injections, closed-loop systems, or basal-only insulin regimens. Over 35 million days of CGM data were analyzed with multilevel modeling. Low coverage was observed in 6.4%–10.1% of days and was significantly associated with lower time in range (TIR) across sources ( P < 0.001). Each 1% increase in coverage was associated with a within-person increase of 0.07%–0.13% in mean daily TIR ( P < 0.001). Our analysis shows that higher daily sensor coverage is significantly associated with higher daily TIR, suggesting that missing CGM data may be missing not-at-random. Although low-coverage days are included in TIR calculations, they contribute fewer measurements and may underrepresent periods of poor glycemic control, potentially leading to a systematic overestimation and bias of overall TIR.
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Novo Nordisk
OpenAlex ID: W4413972138