Novel Glucose Metric "Latest Spike Time" Correlated with Weight Loss at Six Months in People with Obesity Using the Signos System.

Abstract

Introduction: The rise of digital health applications utilizing continuous glucose monitoring (CGM) allows for novel assessments of glucose management and weight changes in people without diabetes. The Signos System incorporates a digital health app paired with a CGM to provide information and prompts aimed to help people without diabetes to manage weight. Objectives: The primary objective of this study was to determine whether the average timing of the latest chronological glucose excursion ("spike") was correlated with amount of weight loss. Methods: This was a retrospective analysis of prospectively obtained glucose and weight data from people without diabetes who enrolled in the Signos System from November 2021 to August 2023. Participants were provided CGMs as well as encouraged to use the Signos app with personalized advice and logging capabilities for weight, food, physical activity, heart rate, sleep, and activities. "Latest spike time" (LST) was retrospectively derived from CGM data and compared with weight changes at 6 months. Results: Nine hundred and twenty-six subjects met the inclusion criteria including sufficient days wearing a CGM and a weight log within 15 days of 6 months from their first weight log. There was a strong correlation between an earlier spike time and increased weight loss. The top quintile of subjects, with an average LST before 5:41 PM, lost over three times as much weight as the bottom quintile of users, with LST after 8:40 PM; this separation was predictable within 1 month of data. Conclusion: In a large population of obese people without diabetes, continuous glucose data, specifically a novel metric "LST," was highly correlated with percentage of total body weight loss at 6 months. This research suggests that for people attempting weight loss, review and alteration of behaviors relating to later glucose excursions may be of specific benefit.