Automated insulin dosing guidance to optimise insulin management in patients with type 2 diabetes: a multicentre, randomised controlled trial

Abstract

Background: Insulin therapy is most effective if dosage titrations are done regularly and frequently, which is seldom practical for most clinicians, resulting in an insulin titration gap. The d-Nav Insulin Guidance System (Hygieia, Livonia, MI, USA) is a handheld device that is used to measure glucose, determine glucose patterns, and automatically determine the appropriate next insulin dose. We aimed to determine whether the combination of the d-Nav device and health-care professional support is superior to health-care professional support alone.

Methods: In this multicentre, randomised, controlled study, we recruited patients from three diabetes centres in the USA (in Detroit MI; Minneapolis, MN; and Des Moines IA). Patients were eligible if they were aged 21-70 years, diagnosed with type 2 diabetes with a glycated haemoglobin (HbA_1c) concentration of 7·5% or higher (≥58 mmol/mol) and 11% or lower (≤97 mmol/mol), and had been using the same insulin regimen for the previous 3 months. Exclusion criteria included body-mass index of 45 kg/m² or higher; severe cardiac, hepatic, or renal impairment; and more than two severe hypoglycaemic events in the past year. Eligible participants were randomly assigned (1:1), with randomisation blocked within each site, to either d-Nav and health-care professional support (intervention group) or health-care professional support alone (control group). Both groups were contacted seven times (three face-to-face and four phone visits) during 6 months of follow-up. The primary objective was to compare average change in HbA_1c from baseline to 6 months. Safety was assessed by the frequency of hypoglycaemic events. The primary objective and safety were assessed in the intention-to-treat population. We used Student's t test to assess the primary outcome for statistical significance. This study was registered with ClinicalTrials.gov, number NCT02424500.

Findings: Between Feb 2, 2015, and March 17, 2017, 236 patients were screened for eligibility, of whom 181 (77%) were enrolled and randomly assigned to the intervention (n=93) and control (n=88) groups. At baseline, mean HbA_1c was 8·7% (SD 0·8; 72 mmol/mol [SD 8·8]) in the intervention group and 8·5% (SD 0·8; 69 mmol/mol [SD 8·8]) in the control group. The mean decrease in HbA_1c from baseline to 6 months was 1·0% (SD 1·0; 11 mmol/mol [SD 11]) in the intervention group, and 0·3% (SD 0·9; 3·3 mmol/mol [9·9]) in the control group (p<0·0001). The frequency of hypoglycaemic events per month was similar between the groups (0·29 events per month [SD 0·48] in the intervention group vs 0·29 [SD 1·12] in the control group; p=0·96).

Interpretation: The combination of automated insulin titration guidance with support from health-care professionals offers superior glycaemic control compared with support from health-care professionals alone. Such a solution facilitated safe and effective insulin titration in a large group of patients with type 2 diabetes, and now needs to be evaluated across large health-care systems to confirm these findings and study cost-effectiveness.

Funding: US National Institutes of Health, National Institute of Digestive and Kidney Diseases.

Figure 1:

Flow of participants through the trial.

Figure 2:

Average HbA1c changes during the study. Results are Mean ± SEM.

Figure 3:

Average weight changes during the study, in percent of the initial weight. Results are Mean ± SEM. Average percentage change in weight was calculated by averaging individual percent weight change.

Figure 4:

Average total daily dose of insulin during the study, normalized to body weight. Results are Mean ± SEM.