SUN-567 Unlocking the Hidden Variables of Pre-Diabetes: CGM Observations in High-Performing, Active Adults (Silicon Valley cohort)

Abstract Disclosure: E. Liu: None. Despite adhering to conventional health guidelines, including regular exercise and low-carbohydrate diets, many high-functioning, active individuals present with pre-diabetic hemoglobin A1c levels (5.6-6.4%). To better understand the nuanced factors affecting glucose regulation, I analyzed CGM data from pre-diabetic patients over a 1-3 month period. Observations from these cases highlight how exercise intensity, stress, sleep quality, and carbohydrate distribution contribute to glucose variability beyond standard recommendations. Exercise Observations In multiple cases, high-intensity exercise contributed to unexpected glucose variability. A marathon runner on a low-carb diet experienced nocturnal and pre-meal hypoglycemia, likely from glycogen mobilization due to physical stress. Another case involved a highly active individual with a body fat percentage in the "fit" range (14-17% for men). Despite being 99% in-range (70-180 mg/dL), the patient had elevated A1c. While most normal glucose targets are set at 70-180 mg/dL, tightening the limit to 150 mg/dL may be necessary for certain pre-diabetic patients aiming to optimize glycemic control. Low-impact exercise, such as walking or yoga, demonstrated improved glucose stabilization compared to high-intensity workouts (>60 minutes), which likely triggered cortisol-related glucose surges. Nutrition Observations Postprandial glucose responses were significantly influenced by carbohydrate load, meal composition, and fiber intake. For example, a patient consuming rice and chicken experienced post-meal glucose spikes >140 mg/dL but adding fiber-rich vegetables (broccoli) consistently reduced the spike to <140 mg/dL. Portion control was a key factor, as excessive consumption of even nutrient-dense foods (e.g., quinoa and lentils) produced higher glucose spikes than smaller, balanced meals with moderate carbohydrate content. Sleep / Stress Observations Sleep deprivation and stress elevated fasting and morning glucose levels. A new mother showed 5-10 mg/dL higher glucose after poor sleep, despite similar diet and activity. CGM data showed that patients in a “fight or flight” state had greater glucose variability, underscoring the role of stress management and restful sleep in glycemic control. Patient Empowerment through CGMs Across cases, CGM data provided real-time, personalized feedback, empowering patients to experiment with dietary and lifestyle modifications. Many initially skeptical patients reported feeling more in control of their glucose management, finding CGM data more actionable than traditional carbohydrate counting. This highlights CGMs as a valuable tool for refining pre-diabetes management, especially in active populations where standard metrics may overlook key variables influencing metabolic health. Presentation: Sunday, July 13, 2025