Trial reportJournal of diabetes science and technology2017
A Randomized Controlled Study of an Insulin Dosing Application That Uses Recognition and Meal Bolus Estimations.
Trial report in Journal of diabetes science and technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 20 citations in OpenAlex.
- Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus.Diabetes technology & therapeutics · 2018Trial
- The effect of the modified fat-protein unit algorithm compared with that of carbohydrate counting on postprandial glucose in adults with type-1 diabetes when consuming meals with differing macronutrient compositions: a randomized crossover trial.Nutrition & metabolism · 2023Article
- Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.Sensors (Basel, Switzerland) · 2020Review
- App-Based Insulin Calculators: Current and Future State.Current diabetes reports · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThroughout the insulin pump therapy, decisions of prandial boluses programming are taken by patients individually a few times every day, and, moreover, this complex process requires numerical skills and knowledge in nutrition components estimation. The aim of the study was to determine the impact of the expert system, supporting the patient's decision on meal bolus programming, on the time in range of diurnal glucose excursion in patients treated with continuous subcutaneous insulin infusion (CSII).
methodsThe crossover, randomized study included 12 adults, aged 19 to 53, with type 1 diabetes mellitus, duration ranging from 7 to 30 years. Patients were educated in complex food counting, including carbohydrate units (CU) and fat-protein units (FPU). Subsequently, they were randomly allocated to the experimental group (A), which used the expert software named VoiceDiab, and the control group (B), using a manual method of meal-bolus estimation.
resultsIt was found that 66.7% of patients within the A group statistically reported a relevant increase in the percentage (%) of sensor glucose (SG) in range (TIR 70-180 mg/dl), compared to the B group. TIR (median) reached 53.9% in the experimental group (A) versus 44% within the control group (B), P < .05. The average difference in the number of hypoglycemia episodes was not statistically significant (-0.2%, SD 11.6%, P = .93). The daily insulin requirement in both groups was comparable-the average difference in total daily insulin dose between two groups was 0.26 (SD 7.06 IU, P = .9).
conclusionThe expert system in meal insulin dosing allows improvement in glucose control without increasing the rates of hypoglycemia or the insulin requirement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.