Real-Time AI-Assisted Insulin Titration System for Glucose Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial
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View abstract on PubMed
Summary
This summary is machine-generated.An artificial intelligence system for insulin titration in type 2 diabetes (T2D) showed results noninferior to physicians. This AI tool offers a promising approach for improving glycemic control in hospitalized T2D patients.
Area Of Science
- Endocrinology
- Artificial Intelligence
- Clinical Decision Support Systems
Background
- Type 2 diabetes (T2D) is a global health challenge requiring effective glycemic control.
- Insulin titration is critical for T2D management but often lacks personalized, real-time tools.
- Current methods for insulin adjustment in hospitalized patients may not be optimal.
Purpose Of The Study
- To evaluate the noninferiority of an artificial intelligence-based insulin clinical decision support system (iNCDSS) compared to senior physicians for insulin titration in hospitalized T2D patients.
- To assess the efficacy and safety of AI-guided insulin therapy.
Main Methods
- A multicenter, single-blind, parallel randomized clinical trial (RCT) involving 149 adult T2D patients.
- Participants were randomized 1:1 to receive insulin titration via iNCDSS or by senior endocrinology physicians for 5 days.
- The primary outcome was the proportion of time within the target glucose range (70-180 mg/dL).
Main Results
- The iNCDSS group achieved a mean time in target glucose range of 76.4%, compared to 73.6% in the physician group, meeting the noninferiority criterion.
- No significant differences in adverse events were observed between the iNCDSS and physician groups.
- Physicians reported satisfaction with the iNCDSS, noting its clarity, time-saving, effectiveness, and safety.
Conclusions
- The iNCDSS demonstrated noninferiority to expert physician management for insulin titration in hospitalized T2D patients.
- This AI-powered system shows potential as a valuable tool for optimizing insulin therapy and glycemic control.
- The findings support the integration of AI decision support systems into clinical practice for T2D management.
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