Effectiveness and safety of AI-driven closed-loop systems in diabetes management: a systematic review and meta-analysis

• Published in: Diabetology and metabolic syndrome Vol. 17; no. 1; pp. 238 - 12
• Main Authors: Wang, Xiaoya, Si, Jiayuan, Li, Yihao, Tse, Poki, Zhang, Guoyi, Wang, Xiaojie, Ren, Junming, Xu, Jin, Sun, Jiancui, Yao, Xi
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 23.06.2025; BioMed Central; BMC
• Subjects: Algorithms; Artificial intelligence; Automation; Bias; Cardiovascular diseases; Clinical outcomes; Closed loop systems; Comparative analysis; Dextrose; Diabetes; Diabetes mellitus; Diabetes therapy; Diabetic neuropathy; Disease management; Glucose; Hypoglycemia; Insulin; Insulin delivery; Machine learning; Meta-analysis; Metabolic disorders; Neuropathy; Performance evaluation; Quality of life; Review; Safety and security measures; Trends; Type 2 diabetes; Wearable devices; AI; Closed-loop systems; Diabetes; Wearable devices; Insulin delivery
• ISSN: 1758-5996; 1758-5996
• DOI: 10.1186/s13098-025-01819-0

Diabetes is a metabolic disease that can lead to severe cardiovascular diseases and neuropathy. The associated medical costs and complications make timely and effective management particularly important. Traditional diagnostic and management methods, like frequent glucose sampling and insulin injections, impose physical injuries on subjects. The development of artificial intelligence (AI) has opened new opportunities for diabetes management. We conducted a meta-analysis integrating existing research, identifying a total of 1156 subjects to assess the effectiveness and safety of AI-based wearable devices, specifically closed-loop insulin delivery systems, in diabetes treatment. Compared to standard controls, AI-based closed-loop systems can analyze glucose data in real-time and automatically adjust insulin delivery, resulting in reduced time outside target glucose ranges (SMD = 0.90, 95% CI = 0.69 to 1.10, I  = 58%, P < 0.001). AI-based closed-loop systems enhance the precision and convenience of diabetes treatment. This meta-analysis providing essential references for clinical treatment and policymaking in diabetes care.