Speaker
Nestoras Mathioudakis, MD, MHS
Associate Professor of Medicine
Johns Hopkins University School of Medicine
Keywords
Artificial Intelligence; Diabetes; Prevention; Coaching; Automation
Key Points
- Of the nearly 100 million U.S. adults with prediabetes, approximately 70% will progress to type 2 diabetes in their lifetime. The Diabetes Prevention Program (DPP), a gold-standard program focused on lifestyle interventions, has demonstrated a 58% reduction in diabetes incidence. However, an effort to implement the program nationally fails to reach 99% of eligible individuals.
- The research team sought to investigate whether a fully automated, AI-based DPP could effectively replicate the outcomes of the human coach-based DPP and potentially bridge this access gap. This was the first trial comparing a fully automated versus human DPP. It adds to a limited evidence base evaluating AI interventions against established standards in medicine.
- The research team found that the AI-driven DPP delivered without human intervention was non-inferior to the traditional human coach-based DPP. Participants in the AI-driven DPP arm had comparable health outcomes and adequate engagement – though they were less likely to express a preference for their intervention than those in the human coach-based arm. The study team concluded that diabetes prevention remains an implementation challenge, not an efficacy problem.
Discussion Themes
While absolute weight loss was modest when compared to the effect of new medications like GLP-1s, Dr. Dakis argued that lifestyle interventions remain more cost-effective and that future automation efforts may bridge the effectiveness gap.
In the future, large language models could bolster the trust and human connection lacking in fully automated digital interventions.
In this Friday’s Rethinking Clinical Trials Grand Rounds, Nestoras Mathioudakis of the Johns Hopkins University School of Medicine will present “