AI-enabled CGM app shows promise for glycemic control, weight management

Arvind Veluvali

Credit: January AI

A new retrospective cohort study in NPJ Digital Medicine examines the role of a January V2, a flexible, artificial intelligence–supported continuous glucose monitoring (CGM) mobile app in improving glycemic control and weight management for individuals across a range of metabolic health statuses.

Titled “Impact of digital health interventions on glycemic control and weight management,” and published on Jan. 9, the research analyzes data from 944 users — comprising healthy individuals as well as those with prediabetes or type 2 diabetes (T2D) — who engaged with the app during a 14-day period.

The authors, including Arvind Veluvali, Ashkan Dehghani Zahedani, Amir Hosseinian and more, found that participants experienced meaningful improvements in time in range (TIR), a key indicator of glucose stability. Users with lower baseline TIR showed the most pronounced benefits; healthy users’ TIR rose from 74.7% to 85.5%, while T2D users’ TIR increased from 49.7% to 57.4%. Moreover, the investigators observed a correlation between higher app engagement and greater TIR improvements, suggesting that active interaction with the AI-driven technology can contribute to better metabolic outcomes. The study also reports an average weight reduction of 3.3 pounds over 33 days.

“Relative to a previous study that used a structured program with specific daily regimented tasks, the current study employed a more flexible and self directed approach in which users engaged with the platform at their own pace, and explored and utilized features based on their unique needs and preferences,” the authors wrote. “The results presented here demonstrate that, even in a less structured environment, digital interventions can effectively support glycemic control and weight management.”

The researchers note that type 2 diabetes prevalence is on the rise globally, with 1.3 billion individuals projected to be living with the condition by 2050. Traditional prevention and management programs, such as the Diabetes Prevention Program, have been effective but face barriers related to cost, accessibility and user engagement. The authors posit that digital health interventions—particularly AI-based systems capable of delivering personalized insights and encouraging lifestyle modifications—offer a scalable option for easing CGM burden, extending access beyond insulin users, and potentially enhancing adherence among people seeking to better manage or prevent metabolic disease.

Building on earlier research, the investigators observed clinically meaningful improvements in time in range (TIR) and weight loss across user groups with varied metabolic health statuses. Although the study did not include a control group—a limitation common to real-world investigations—the results mirrored those from previous controlled studies that also documented significant benefits from digital interventions.

A key theme is user engagement. The study authors identified “power users,” whose higher interaction with the platform correlated with greater increases in TIR and more substantial weight loss. According to the researchers, this finding underscores the importance of active, sustained participation in digital health programs—particularly when the platform is self-directed. The investigation also highlighted that participants reporting lower baseline TIR appeared to benefit substantially, with improvements that align with existing literature emphasizing clinical benefits of higher TIR levels.

In addition to enhanced glucose metrics, users in the prediabetes cohort and those who were highly engaged saw noteworthy reductions in body weight — an outcome that may help reduce the risk of diabetes progression. Researchers believe these results could be partly attributed to personalized app features that encouraged healthier dietary choices, increased protein and fiber intake, and reduced carbohydrate consumption. Although improvements in low glucose episodes and the small rise in last-meal sleep gap were noted, the study team acknowledged questions remain about the long-term implications for various population subgroups, including individuals with type 2 diabetes.

The authors also pointed to potential avenues for further investigation, including extended follow-up periods to evaluate whether participants can sustain health gains over time. Additional work is needed to clarify the role of medication usage, other concurrent interventions, and unmeasured confounders that may influence outcomes. Future research goals include large-scale, multi-center randomized controlled trials that measure long-term effectiveness, cost outcomes and the impact on clinical endpoints such as hemoglobin A1c and cardiovascular events.

“The broader implications of this study suggest that digital health platforms like January V2 have the potential to play a crucial role in the future of chronic disease management,” the authors write. “By providing continuous, personalized support, these tools have the potential to reduce the burden of diabetes and prediabetes on both individuals and healthcare systems. As digital health continues to evolve, it will be essential to refine these interventions to maximize their efficacy and accessibility.”