OptimAAPP, a smartphone insulin dose calculator for carbohydrate, fat, and protein: A cross-over, randomised controlled trial in adolescents and adults with type 1 diabetes using multiple daily injection therapy

Diabet Med. 2024 Dec 9:e15487. doi: 10.1111/dme.15487. Online ahead of print.

Abstract

Aims: To (1) evaluate the efficacy of OptimAAPP, a smartphone insulin dose calculator for carbohydrate, fat, and protein in managing glycaemia compared with carbohydrate counting in adolescents and adults with type 1 diabetes using flexible multiple daily injection therapy (MDI, ≥4 injections/day) and (2) assess user acceptability of OptimAAPP.

Methods: In this free-living trial, participants aged 12-50 years were randomised to use carbohydrate counting or OptimAAPP for meal insulin dose calculation for 3 months, then use the alternate method for 3 months. The primary outcome, time-in-range (3.9-10.0 mmol/L) was measured in weeks 3-4 of each arm using continuous glucose monitoring. The acceptability of OptimAAPP was assessed at end intervention using a purpose-designed questionnaire.

Results: An intention-to-treat analysis of 41 participants, mean age 28 ± 12 years and HbA1c 56 ± 10 mmol/mol (7.3 ± 0.9%) found no significant difference in glycaemic outcomes when using OptimAAPP compared with carbohydrate counting including time-in-range (70.5 vs. 67.6%, p = 0.102), above range (24.5% vs. 28.0%, p = 0.068), below range (4.9% vs. 4.4%, p = 0.318), and coefficient of variation (32.2% vs. 33.3%, p = 0.136). There was no severe hypoglycaemia. Participants reported that OptimAAPP was easy to use (79%), and they were confident in giving the recommended doses (82%). Barriers to use were the small food database and the time associated with food entry.

Conclusions: In adolescents and adults using flexible MDI therapy, OptimAAPP use did not produce glycaemic outcomes that were significantly different from carbohydrate counting. Participant views of OptimAAPP indicate a high level of acceptability. Increasing the size of the food database will likely enhance the user experience.

Keywords: blood glucose; child; continuous glucose monitoring; diabetes mellitus; nutrients; smartphone; type 1.