Time above range for predicting the development of type 2 diabetes

Marco, Alejandra; Pazos-Couselo, Marcos; Moreno-Fernández, Jesús; Díez‐Fernández, Ana; Alonso-Sampedro, Manuela; Fernández-Merino, Carmen; González‐Quintela, Arturo; Gudé, Francisco

doi:10.3389/fpubh.2022.1005513

Cited by 3 publications

(1 citation statement)

References 53 publications

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“…19 A CGM-derived index has demonstrated the ability to identify individuals with a high risk of progressing to T2DM. 20 Some CGM-derived indices also correlate with insulin secretion, insulin sensitivity, or the disposition index (DI). 19,[21][22][23][24] While various glycemic variability indices derived from CGM have been reported, their relationship to glucose handling capacity and their potential for identifying individuals with reduced glucose handling, particularly in a population predominantly composed of healthy individuals, remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Improved Detection of Decreased Glucose Handling Capacities via Novel Continuous Glucose Monitoring-Derived Indices: AC_Mean and AC_Var

Sugimoto,

Hironaka,

Nakamura

et al. 2023

Preprint

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Background: Efficiently detecting impaired glucose control abilities is a pivotal challenge in public health. This study assessed the utility of relatively easy-to-measure continuous glucose monitoring (CGM)-derived indices in estimating glucose handling capacities calculated from resource-intensive clamp tests. Methods: We conducted a prospective, single-center, observational cohort study of 64 individuals without prior diabetes diagnosis. The study utilized CGM, oral glucose tolerance test, and hyperglycemic and hyperinsulinemic-euglycemic clamp tests. We validated CGM-derived indices characteristics using an independent dataset and mathematical model with simulated data. Findings: A novel CGM-derived index, AC_Var, was significantly correlated with insulin sensitivity (r = -0.31; 95% CI: -0.52 to -0.06), insulin clearance (r = -0.31; 95% CI: -0.54 to -0.06), and disposition index (DI) (r = -0.31; 95% CI: -0.52 to -0.07) calculated from clamp tests. AC_Var was also significantly correlated with insulin resistance (r = 0.48; 95% CI: 0.23 to 0.68) in an independent dataset. Multivariate analyses indicated AC_Var's contribution to predicting reduced blood glucose control abilities independent from conventional CGM-derived indices. The prediction model's accuracy utilizing CGM-measured glucose standard deviation and AC_Var as input variables, with clamp-derived DI as the outcome, closely matched that of predicting clamp- from OGTT-derived DI. Mathematical simulations also underscored AC_Var's association with insulin clearance and DI. Interpretation: CGM-derived indices, including AC_Var, can be useful for screening decreased blood glucose control ability. We developed a web application that calculates these indices (https://cgm-ac-mean-std.streamlit.app/). Funding: The Japan Society for the Promotion of Science KAKENHI, CREST, Japan Science and Technology Agency, and Uehara Memorial Foundation.

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Section: Introductionmentioning

confidence: 99%

Improved Detection of Decreased Glucose Handling Capacities via Novel Continuous Glucose Monitoring-Derived Indices: AC_Mean and AC_Var

Sugimoto,

Hironaka,

Nakamura

et al. 2023

Preprint

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From Stability to Variability: Classification of Healthy Individuals, Prediabetes, and Type 2 Diabetes Using Glycemic Variability Indices from Continuous Glucose Monitoring Data

Cichosz,

Kronborg,

Laugesen

et al. 2024

Diabetes Technology & Therapeutics

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Defining Continuous Glucose Monitor Time in Range in a Large, Community-Based Cohort Without Diabetes

Spartano,

Sultana,

Lin

et al. 2024

The Journal of Clinical Endocrinology &Amp; Metabolism

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Context Continuous glucose monitor (CGM) companies are beginning to market these sensors to populations without diabetes, but the range of CGM values clinicians should expect to see for this population is unclear because there have been no large studies reporting these ranges. Objective This work aimed to report the physiological range of CGM time in range values observed across glycemic status, including individuals without diabetes, to serve as a reference for clinicians. Methods The Framingham Heart Study, a prospective cohort study, was conducted among community-dwelling adults with normoglycemia (n = 560), prediabetes (n = 463), and diabetes (n = 152). We conducted a cross-sectional investigation in participants who wore a Dexcom G6 Pro CGM (in blinded mode) for 7 or more complete days. Main outcome measures included CGM metrics including mean glucose and time spent in glucose ranges. Results Normoglycemic participants (mean age 58.5 years, 64.5% women, 93.3% non-Hispanic White) spent 87.0% time in the 70 to 140 mg/dL CGM range, and, on average, more than 15 minutes/day (1.2% time) at more than 180 mg/dL. Furthermore, normoglycemic participants spent approximately 3 hours/day (12.1% time) with CGM glucose at more than 140 mg/dL. On average, participants with prediabetes and diabetes spent 77.1% and 46.2% of time in the 70 to 140 mg/dL range, respectively. Conclusion Our results contribute to the understanding of the physiological CGM range in more than 1000 participants without diabetes. These results are also important for clinicians to reference as CGM sensors become more widely accessible to people without known diabetes.

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Time above range for predicting the development of type 2 diabetes

Cited by 3 publications

References 53 publications

Improved Detection of Decreased Glucose Handling Capacities via Novel Continuous Glucose Monitoring-Derived Indices: AC_Mean and AC_Var

Improved Detection of Decreased Glucose Handling Capacities via Novel Continuous Glucose Monitoring-Derived Indices: AC_Mean and AC_Var

From Stability to Variability: Classification of Healthy Individuals, Prediabetes, and Type 2 Diabetes Using Glycemic Variability Indices from Continuous Glucose Monitoring Data

Defining Continuous Glucose Monitor Time in Range in a Large, Community-Based Cohort Without Diabetes

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