ArticleeLife2026
Association between continuous glucose monitoring-derived metrics and coronary plaque vulnerability: A retrospective exploratory analysis.
Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Technology in Diabetes: A Year in Review.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026Review
- Use of continuous glucose monitoring to stratify individuals without diabetes.Communications medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Background: Impaired glucose homeostasis leads to numerous complications, with coronary artery disease (CAD) being a major contributor to healthcare costs worldwide. Because continuous glucose monitoring (CGM) captures multidimensional features of glucose regulation beyond average glycemia, we evaluated whether CGM-derived indices better predict coronary plaque vulnerability than conventional measures. Methods: We examined associations between CGM-derived indices and coronary plaque vulnerability assessed by virtual histology-intravascular ultrasound, focusing on the necrotic core (%NC) in humans. We analyzed 14 CGM-derived indices, including average daily risk ratio (ADRR) and autocorrelation-based metrics (AC_Mean and AC_Var), alongside commonly used measures, such as fasting blood glucose (FBG), hemoglobin A1c (HbA1c), and 120 min plasma glucose during oral glucose tolerance testing (PG120). Factor analysis was used to identify latent components underlying glucose dynamics and to relate these components to %NC. Findings were validated across independent datasets from Japan (n=64), the United States (n=53), and China (n=100). Results: CGM-derived indices, particularly ADRR and AC_Var, demonstrated stronger predictive capability for %NC than FBG, HbA1c, and PG120. Factor analysis identified three independent components of glucose dynamics: mean, variance, and autocorrelation, each showing an independent association with %NC. ADRR reflected both mean and variance components, whereas AC_Var primarily captured the autocorrelation component. In contrast, FBG, HbA1c, and PG120 primarily reflected the mean component alone and were, therefore, insufficient for %NC prediction. Conclusions: CGM-derived indices reflecting the three components of glucose dynamics can serve as more effective screening tools for CAD risk assessment, complementing or possibly replacing traditional diabetes diagnostic methods. Funding: This study was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI (JP21H04759), CREST, the Japan Science and Technology Agency (JST) (JPMJCR2123), The Uehara Memorial Foundation, and The Takeda Science Foundation.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.