A Bayesian decision support system for automated insulin doses in adults with type 1 diabetes on multiple daily injections: a randomized controlled trial

A Alessandra Kobayati A Anas El Fathi N Natasha Garfield L Laurent Legault A Adnan Jafar J Jean-François Yale M Michael A. Tsoukas A Ahmad Haidar

Abstract

Abstract Achieving optimal glycemic control remains challenging for many individuals with type 1 diabetes using multiple daily injections. We report results from a 12-week, open-label, randomized controlled trial evaluating a decision support system (DSS) consisting of a mobile application and a titration algorithm that provides weekly basal and prandial insulin recommendations. Eighty-four adults with type 1 diabetes and suboptimal glycemic control (HbA1c ≥ 7.5%) are randomized 1:1 to receive the DSS or a non-adaptive bolus calculator (control), alongside Freestyle Libre glucose sensors. The primary endpoint is change in HbA1c from baseline; secondary endpoints include additional glycemic and insulin-related metrics. The DSS reduces mean HbA1c from 8.6% (SD 1.1) to 8.1% (0.8) (p = 0.0002), while the control reduces HbA1c from 8.6% (1.0) to 8.5% (1.0) (p = 0.22); yielding a treatment effect of –0.40% (95% CI: –0.75 to –0.051; p = 0.025). There are no reported severe hypoglycemia or diabetic ketoacidosis events. Our DSS improves HbA1c in this population without compromising safety. ClinicalTrials.gov: NCT04123054 .

Article Details

Volume / Issue Vol. 16, Issue 1
Published September 29, 2025
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (8)

A

Alessandra Kobayati

A

Anas El Fathi

N

Natasha Garfield

L

Laurent Legault

A

Adnan Jafar

J

Jean-François Yale

M

Michael A. Tsoukas

A

Ahmad Haidar