What Is a Continuous Glucose Monitor, and What Can It Add to Your Study?

A continuous glucose monitor (CGM) is a small wearable device that collects real-time blood sugar data continuously, rather than at a single point in time with a finger prick. CGMs are often thought of as a management tool for Type 1 diabetes, but the data they generate—glucose levels and glycemic variability over time—is relevant well beyond diabetes care. For researchers, a CGM offers a direct window into metabolic and digestive outcomes that individual blood tests cannot.

A continuous glucose monitor (CGM) is a 24/7 sensor that gives researchers real-time, comprehensive insight into how the body processes glucose without a single fingerstick. It does this by measuring the glucose in your body's interstitial fluid through your arm. This post covers what CGMs measure, when they're a good fit for a study, and how to configure one in Alethios.

What is a CGM?

A continuous glucose monitor (CGM) is a small wearable device that collects real-time blood sugar data continuously, rather than at a single point in time with a finger prick. CGMs are often thought of as a management tool for diabetes, but the data they generate, glucose levels and glycemic variability over time, is relevant well beyond diabetes care. For researchers, a CGM offers a direct window into metabolic and digestive outcomes that individual blood tests cannot.

Why Track Glucose?

High glucose can lead to health issues, but a deficiency makes it hard for your muscles to work. Balancing glucose levels is key to feeling good, performing well, and staying healthy. Just as a CGM gives the wearer valuable insight into their wellbeing, it gives researchers important information about a protocol, intervention, or habit's influence.

When is CGM a Good Fit?

CGM data tracks glucose trends and identifies patterns in how the body processes sugar over time, which makes it useful whenever a study is looking at how an intervention influences metabolic or glycemic outcomes. Common use cases include:

Supplement studies. Measuring how a supplement—whether it's a fiber blend, a probiotic, or a glucose-management formula—affects post-meal glucose response or overall glycemic variability. A 2020 randomized controlled trial of a novel probiotic formulation in adults with type 2 diabetes found significant reductions in postprandial glucose AUC and A1c using serial glucose measurements—exactly the kind of continuous, longitudinal signal a CGM captures automatically, without repeat blood draws.
Nutritional or food studies. Understanding how a specific food, ingredient, or diet pattern affects metabolic processes over the course of a study, not just at a single checkpoint. A 2025 observational study had 48 healthy adults wear a CGM for one week alongside food diaries and activity tracking, correlating glucose metrics directly with glycemic load and macronutrient intake.
Exercise or habit studies. Tracking how physical activity, sleep, or other daily habits correlate with glucose stability, which is useful for studies on metabolic health, weight management, or general wellness. The CGM-HYPE study (2025) had healthy young adults wear a CGM for 14 days through standardized diet, exercise, and stress conditions, finding that anaerobic exercise produced significantly larger glucose excursions than aerobic exercise.

From Disease Management to Healthy Population Research

Most of the clinical evidence base for CGM—including the probiotic trial above—comes from disease-state research: managing or treating diagnosed conditions like type 2 diabetes. That's where CGM technology was validated first, and where regulatory and reimbursement pathways were built.

But the same signal that helps clinicians manage diabetes is just as informative in people without any diagnosed condition. Researchers are increasingly turning CGM toward healthy and at-risk (not diagnosed) populations:

A multicenter study in The Journal of Clinical Endocrinology & Metabolism established normative CGM profiles—average glucose, time-in-range—for healthy, nondiabetic adults, giving researchers a baseline to measure interventions against.
A 2025 systematic review examined how CGM is being used in non-diabetic individuals specifically to guide lifestyle interventions and assess cardiovascular risk.

This is a meaningful shift in how CGM gets used in research: from a monitoring tool for an existing condition to a discovery tool for prevention and optimization. Glycemic variability, post-meal spikes, and recovery time are relevant to anyone studying metabolic health, weight management, sleep, or athletic performance—not just diagnosed populations.

How to Add a CGM to Your Study on Alethios

Alethios has integrated Dexcom, Abbott, and Libre CGMs directly into the platform, so adding one to a study is as easy as clicking a button.

What Researchers Receive

Once a study is live, researchers get continuous glucose and glycemic variability data streamed directly into the platform, alongside any survey, biomarker, or other wearable data collected in the same study, all on the same participant timeline.

Glucose data doesn't just tell you what happened at one moment; it tells you the story of how a body responded over time. That's exactly the kind of evidence Alethios is built to make easier to collect.

‍

Perraudeau F, McMurdie P, Bullard J, et al. Improvements to postprandial glucose control in subjects with type 2 diabetes: a multicenter, double blind, randomized placebo-controlled trial of a novel probiotic formulation. BMJ Open Diabetes Res Care. 2020;8(1):e001319. doi:10.1136/bmjdrc-2020-001319. https://pubmed.ncbi.nlm.nih.gov/32675291/

Ong L, Lamoth CJ, van Beek A, Cao M, Verkerke GJ, Wilhelm E. Continuous Glucose Measurements for Diet Monitoring in Healthy Adults. J Diabetes Sci Technol. 2025. doi:10.1177/19322968251361555. https://pmc.ncbi.nlm.nih.gov/articles/PMC12343543/

Kinny F, Läer S, Obarcanin E. Continuous Glucose Monitoring under standardised conditions regarding diet, exercise and stress in Healthy Young People (CGM-HYPE study): An exploratory clinical trial. PLOS Digit Health. 2025. doi:10.1371/journal.pdig.0001087. https://pmc.ncbi.nlm.nih.gov/articles/PMC12617953/

Shah VN, DuBose SN, Li Z, et al. Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study. J Clin Endocrinol Metab. 2019;104(10):4356-4364. doi:10.1210/jc.2018-02763. https://academic.oup.com/jcem/article/104/10/4356/5479355

Ahmed N, Elzein Ali MF, Hamed Mohamed MN, et al. Use of Continuous Glucose Monitoring in Non-diabetic Individuals for Cardiovascular Prevention: A Systematic Review of Its Impact on Guiding Lifestyle Interventions. Cureus. 2025;17(10):e94460. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12612783/‍

Rodríguez García J, Camiña Darriba F, Ortolá Devesa JB, Rodríguez-Segade Villamarín S, Valle Rodríguez A. Parameters of glycemic variability in continuous glucose monitoring as predictors of diabetes: a prospective evaluation in a non-diabetic general population. Adv Lab Med. 2025;6(1):46-51. doi:10.1515/almed-2025-0011. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949551/