Nimri AI insulin dosing

Insulin Dose Optimization Using an Automated Artificial Intelligence-Based Decision Support System in Youths with Type 1 Diabetes (ADVICE4U)

Patient / Population Intervention / Exposition Comparaison Critère de jugement

In 108 youths aged 10–21 years with type 1 diabetes on insulin pump therapy, remote insulin dose adjustment every three weeks guided by an automated AI-based decision support system was non-inferior to physician-guided adjustment for time in target glucose range (70–180 mg/dL) over six months.

N
108
Schéma
Multicentre, multinational, parallel-group non-inferiority RCT, 6 months
Critère
Percentage of time in target glucose range 70–180 mg/dL
Pertinence
2
RésultatTime in range 50.2 ± 11.1% vs 51.6 ± 11.3% (non-inferior); readings <54 mg/dL 1.3 ± 1.4% vs 1.0 ± 0.9% (non-inferior, P<0.0001). Three severe diabetes-related adverse events (two severe hypoglycaemia, one DKA) in the physician arm, none with the AI-DSS.
Nimri R, et al. Nat Med. 2020;26(9):1380-1384. 10.1038/s41591-020-1045-7
Discussion et critique

First randomised evidence that an automated algorithm can titrate insulin pump settings as well as specialists at academic diabetes centres — the case for scaling scarce expertise. Non-inferiority against expert physicians in 108 youths over six months; neither arm reached glycaemic targets (time in range around 50%), so the tool matched rather than surpassed specialist care.