Artificial pancreas (AP) systems have proven efficacy and superiority in glucose control compared with other insulin delivery methods in patients with type 1 diabetes (1,2). Patients with type 2 diabetes (T2D) requiring intensive insulin therapy are difficult to treat and could potentially benefit from AP. Two published reports have addressed AP and T2D in hospitalized patients, with overall results favoring AP (2,3). We aimed to test the applicability of a single-hormone (SH) (insulin only) AP algorithm in patients with T2D who require multiple daily injections (MDI) of insulin.

We conducted an open-label, randomized, crossover study to compare glucose control under SH-AP and MDI in adults with T2D (≥55 years old, BMI >25 kg/m2, on ≥3 insulin injections/day). Exclusion criteria were change in hypoglycemic agents within 6 weeks prior to or during the study, creatinine clearance <30 mL/min, macrovascular event within the past 6 months, infections and hospitalization within the past 2 months, severe hypoglycemia in the past 2 weeks, or morning basal insulin. Participants were recruited at diabetes clinics of three Canadian (Quebec) participating centers. Respective ethics committees approved the study with written informed consent. Dexcom G4 Platinum (Dexcom, San Diego, CA) was inserted 24 h before interventions and calibrated 2–3 times/day. In a crossover design, each participant underwent two 24-h intervention visits using SH-AP and MDI in randomized order (separated by at least 3 days). Schedules were identical between these interventions: arrival at the research center at 6:30 p.m. (dinner and insulin bolus prior to that at home), standardized evening snack, next day’s breakfast at 8:00 a.m., lunch at 12:00 p.m., dinner at 5:00 p.m., 15-min walks at 10:00 a.m. and 3:00 p.m., and discharge at 9:00 p.m. Blood samples were collected every 20 min starting at 9:00 p.m. for 24 h. During MDI visits, patients decided their insulin basal and premeal doses without research team interference. For AP visits, glucose was controlled by algorithm only for both rapid insulin analog rate and announced premeal boluses using a subcutaneous pump (Accu-Chek Combo; Roche, Mannheim, Germany). AP, as previously reported (4), used a model predictive algorithm initiated with the participant’s weight and 70% of usual basal and bolus insulin doses and was of a hybrid type that required meal announcement. A linear mixed-effects model suited for repeated observations was used for analysis (R software, version 3.4.1).

The study was completed by 15 patients (11 males, mean ± SD 63.6 ± 6.7 years old, BMI 33.4 ± 5.6 kg/m2, HbA1c 7.85 ± 0.6% [62.0 ± 4.9 mmol/mol]).

Over the 24-h period, a trend was observed for an improved median plasma glucose (PG) time in target range (72–180.0 mg/dL 2 h postmeal and 72–144 mg/dL otherwise), from 78.9% (interquartile range [IQR] 63.3–85.5%) with MDI to 86.2% (IQR 76.5–91.7%) with AP (P = 0.057) (mean values in Table 1). With AP, there was a trend for decrease of time in hyperglycemia and lower mean PG (not significant). No differences in time in hypoglycemia nor in number of participants with hypoglycemia events were observed between AP and MDI. Lower insulin doses (−31.7%, P < 0.001) were administered by the AP algorithm, which resulted in lower plasma insulin levels in comparison with MDI.

Table 1

Comparison of AP and MDI

Outcome24 h (9:00 p.m.–9:00 p.m.)Overnight (11:00 p.m.–7:00 a.m.)
APMDIPaired difference; P valueAPMDIPaired difference; P value
Time spent at PG (%) 
 In target* 84.2 (11.5) 74.0 (17.0) 10.2; P = 0.057 92.5 (11.6) 70.9 (27.1) 21.6; P = 0.010 
 72–180 mg/dL 92.3 (7.2) 85.2 (11.8) 7.1; P = 0.046 97.3 (7.6) 84.8 (11.7) 12.5; P = 0.001 
 Below 72 mg/dL 0 (0–0) 0 (0–6.2) 0; P = 0.217 0 (0–0) 0 (0–2.0) 0; P = 0.450 
 Below 63 mg/dL 0 (0–0) 0 (0–0.5) 0; P = 0.685 0 (0–0) 0 (0–0) 0; P = 0.923 
 Above 144 mg/dL 21.8 (13.5–29.9) 26.9 (12.8–47.9) −5.1; P = 0.111 0 (0–0.5) 4.6 (0–49.4) −4.6; P = 0.024 
 Above 180 mg/dL 4.2 (0–9.1) 7.4 (1.6–18.6) −3.2; P = 0.109 0 (0–0) 0 (0–17.8) 0; P = 0.012 
Total insulin daily dose (units) 84.0 (40.9) 115.7 (51.6) −31.7; P < 0.001    
Insulin concentration (mU/L) 459.7 (296.5) 567.4 (294.4) −107.7; P = 0.010    
PG (mg/dL) 120.6 (14.4) 127.8 (19.8) −7.2; P = 0.137 100.8 (16.2) 120.6 (30.6) −19.8; P = 0.021 
SD of PG (mg/dL) 28.8 (5.4) 32.4 (9.0) −3.6; P = 0.260 12.6 (7.2) 19.8 (10.8) −7.2; P = 0.058 
Coefficient of variation in PG (%) 24.0 (4.1) 25.0 (5.8) −1.0; P = 0.535 13.0 (5.9) 16.0 (7.4) −3.0; P = 0.203 
AUC (mg/dL × min/h)       
 AUC of PG <72 mg/dL 0 (0–0) 0 (0–18.0) 0; P = 0.450 0 (0–0) 0 (0–676.8) 0; P = 0.441 
 AUC of PG <63 mg/dL 0 (0–0) 0 (0–0) 0; P = 0.923 0 (0–0) 0 (0–0) 0; P = 0.908 
 AUC of PG >144 mg/dL 0 (0–9.0) 82.8 (0–889.2) −82.8; P = 0.024 0 (0–36.6) 82.8 (0–1,780.8) −82.2; P = 0.050 
 AUC of PG >180 mg/dL 0 (0–0) 0 (0–320.4) 0; P = 0.012 0 (0–0) 0 (0–6,166.8) 0; P = 0.036 
Hypoglycemic events <63 mg/dL       
 Participants with at least one event requiring treatment, n (%)** 3 (20.0) 5 (33.3) −2; P = 0.253 1 (6.7) 3 (20.0) −2; P = 0.253 
 Total events, n – – 
Outcome24 h (9:00 p.m.–9:00 p.m.)Overnight (11:00 p.m.–7:00 a.m.)
APMDIPaired difference; P valueAPMDIPaired difference; P value
Time spent at PG (%) 
 In target* 84.2 (11.5) 74.0 (17.0) 10.2; P = 0.057 92.5 (11.6) 70.9 (27.1) 21.6; P = 0.010 
 72–180 mg/dL 92.3 (7.2) 85.2 (11.8) 7.1; P = 0.046 97.3 (7.6) 84.8 (11.7) 12.5; P = 0.001 
 Below 72 mg/dL 0 (0–0) 0 (0–6.2) 0; P = 0.217 0 (0–0) 0 (0–2.0) 0; P = 0.450 
 Below 63 mg/dL 0 (0–0) 0 (0–0.5) 0; P = 0.685 0 (0–0) 0 (0–0) 0; P = 0.923 
 Above 144 mg/dL 21.8 (13.5–29.9) 26.9 (12.8–47.9) −5.1; P = 0.111 0 (0–0.5) 4.6 (0–49.4) −4.6; P = 0.024 
 Above 180 mg/dL 4.2 (0–9.1) 7.4 (1.6–18.6) −3.2; P = 0.109 0 (0–0) 0 (0–17.8) 0; P = 0.012 
Total insulin daily dose (units) 84.0 (40.9) 115.7 (51.6) −31.7; P < 0.001    
Insulin concentration (mU/L) 459.7 (296.5) 567.4 (294.4) −107.7; P = 0.010    
PG (mg/dL) 120.6 (14.4) 127.8 (19.8) −7.2; P = 0.137 100.8 (16.2) 120.6 (30.6) −19.8; P = 0.021 
SD of PG (mg/dL) 28.8 (5.4) 32.4 (9.0) −3.6; P = 0.260 12.6 (7.2) 19.8 (10.8) −7.2; P = 0.058 
Coefficient of variation in PG (%) 24.0 (4.1) 25.0 (5.8) −1.0; P = 0.535 13.0 (5.9) 16.0 (7.4) −3.0; P = 0.203 
AUC (mg/dL × min/h)       
 AUC of PG <72 mg/dL 0 (0–0) 0 (0–18.0) 0; P = 0.450 0 (0–0) 0 (0–676.8) 0; P = 0.441 
 AUC of PG <63 mg/dL 0 (0–0) 0 (0–0) 0; P = 0.923 0 (0–0) 0 (0–0) 0; P = 0.908 
 AUC of PG >144 mg/dL 0 (0–9.0) 82.8 (0–889.2) −82.8; P = 0.024 0 (0–36.6) 82.8 (0–1,780.8) −82.2; P = 0.050 
 AUC of PG >180 mg/dL 0 (0–0) 0 (0–320.4) 0; P = 0.012 0 (0–0) 0 (0–6,166.8) 0; P = 0.036 
Hypoglycemic events <63 mg/dL       
 Participants with at least one event requiring treatment, n (%)** 3 (20.0) 5 (33.3) −2; P = 0.253 1 (6.7) 3 (20.0) −2; P = 0.253 
 Total events, n – – 
Results according to sensor readings and parameters as defined in AP consensus guidelines***
Time spent at sensor glucose (%) 
 Below 70 mg/dL 0 (0–0.7) 0 (0–4.3) 0; P = 0.45 0 (0–0.70) 0 (0–1.4) 0; P = 0.50 
 70–140 mg/dL 68.3 (14.5) 58.8 (16.7) 9.5; P = 0.05 87.8 (14.4) 55.5 (29.6) 32.3; P = 0.002 
 70–180 mg/dL 90.4 (8.1) 84.2 (13.2) 6.2; P = 0.11 95.2 (8.2) 84.3 (25.5) 10.9; P = 0.13 
 Above 180 mg/dL 4.5 (0.7–10.7) 8.2 (1.2–17.9) −3.7; P = 0.25 0 (0–0) 0 (0–0) 0; P = 0.22 
Mean glucose (mg/dL) 126.0 (16.2) 133.2 (21.6) −7.2; P = 0.23 102.6 (18.0) 127.8 (34.2) −25.2; P = 0.01 
Results according to sensor readings and parameters as defined in AP consensus guidelines***
Time spent at sensor glucose (%) 
 Below 70 mg/dL 0 (0–0.7) 0 (0–4.3) 0; P = 0.45 0 (0–0.70) 0 (0–1.4) 0; P = 0.50 
 70–140 mg/dL 68.3 (14.5) 58.8 (16.7) 9.5; P = 0.05 87.8 (14.4) 55.5 (29.6) 32.3; P = 0.002 
 70–180 mg/dL 90.4 (8.1) 84.2 (13.2) 6.2; P = 0.11 95.2 (8.2) 84.3 (25.5) 10.9; P = 0.13 
 Above 180 mg/dL 4.5 (0.7–10.7) 8.2 (1.2–17.9) −3.7; P = 0.25 0 (0–0) 0 (0–0) 0; P = 0.22 
Mean glucose (mg/dL) 126.0 (16.2) 133.2 (21.6) −7.2; P = 0.23 102.6 (18.0) 127.8 (34.2) −25.2; P = 0.01 

Data are presented as median (IQR) or mean (SD) unless otherwise indicated. Paired difference is AP vs. MDI value. AUC, area under the curve.

*

Primary end point: time in target range is defined as PG 72–144 mg/dL at all times except in the 2 h postmeal, when the range is set at 72–180 mg/dL.

**

Hypoglycemia treated with 16-g glucose tablets.

***

Study design and outcomes were set before the publication of AP consensus guidelines, but we calculated these values at study conclusion (4).

For overnight control (11:00 p.m.–7:00 a.m.), AP resulted in higher time in target range at 100% (IQR 85.6–100%) vs. 78.0% (IQR 50.6–95.7%) (P = 0.01), lower mean PG (100.8 ± 16.2 vs. 120.6 ± 30.6 mg/dL, P = 0.02), and a trend toward lower glucose variability (SD).

Our findings confirm AP applicability under a controlled setting in patients with T2D on intensive insulin. Glucose control was significantly improved overnight (+21.6% for median time in target range) with a similar trend over 24 h (+7.3%). Overnight, tighter control was achieved without increasing hypoglycemia risk with AP (1 vs. 3 patients). In comparison with published results in hospitalized patients, which also favored AP, percentages of time in target range in our study were higher in both AP and control arms (2). This could be attributed to the compromised health status, absence of meal boluses, and sensor reporting (versus PG) in the hospitalized patients’ trials. As seen in patients with type 1 diabetes, AP systems have better overnight performances due to persistent challenges of postprandial glucose control with available devices and insulin analogs (5). The observed improvement in glucose time in target range could have important clinical implications in the light of accumulating evidence linking time in target range to complications such as the prevalence and severity of retinopathy and microalbuminuria in patients with T2D (6). Interestingly, less insulin was needed with AP, but this could partly be due to the continuous infusion approach and not solely explained by algorithm dosing. These data could allow fine-tuning of the SH-AP algorithm in this population.

This first pilot trial testing an AP algorithm in MDI-treated patients with T2D had some limitations: a small number of participants, short duration, and no prior treatment optimization. Whether AP would outperform optimized T2D treatment with multiple alternative options (glucagon-like peptide 1 agonists, sodium–glucose cotransporter 2 inhibitors, ultralong-acting basal insulins, continuous or flash glucose monitoring, etc.) is worth investigating for this population in larger and longer trials under free-living conditions. The potential clinical benefits of this technology in patients with advanced T2D will have to be weighed against complexity and costs of AP systems.

Acknowledgments. The authors thank all the participants for their valuable time and the nurses and clinical research personnel Jennifer René, Danijela Bovan, Marie Raffray, Annie Gaumond, and Valérie Parent, Institut de recherches cliniques de Montréal, and Caroll-Lynn Thibodeau, Maude Gérard Christophe Noll, and Frédérique Frisch, Université de Sherbrooke, for their valuable contribution to the conduct of the study.

Funding. This work was supported by funds held by R.R.-L. from the J.A. DeSève Research Chair; Cardiometabolic Health, Diabetes and Obesity Research Network (CMDO); and a Canadian Institutes of Health Research (CIHR) foundation grant. N.T. is the recipient of a CIHR scholarship and Fonds de la Recherche en Santé du Québec (FRSQ) scholarships. A.C.C. is the recipient of the GlaxoSmithKline Chair in Diabetes of the Université de Sherbrooke and Canada Research Chair in Molecular Imaging of Diabetes.

Duality of Interest. A.C.C. declares research funding from CIHR, Canadian Diabetes Association, Fonds de recherche du Quebec–Santé, Janssen, Merck, UniQure, Caprion, Eli Lilly, Novo Nordisk, GlaxoSmithKline, Novartis, Pfizer, Philips, Sanofi, Siemens, and Amgen and consulting/advisory panel participation or conference fees from Merck, Amgen, Janssen, UniQure, Servier, Novo Nordisk, and Novartis. V.M. declares purchase fees related to AP from Eli Lilly. M.L. received consulting fees from Institut de recherches cliniques de Montréal. A.H. has received consulting fees from Eli Lilly, research support from Eli Lilly and AgaMatrix, and AP purchase fees from Eli Lilly. R.R.-L. declares research grants from AstraZeneca, Eli Lilly, Merck, Novo Nordisk, and Sanofi; consulting/advisory panel participation with Abbott, Amgen, AstraZeneca, Boehringer, Carlina Technology, Eli Lilly, Janssen, Medtronic, Merck, Neomed, Novo Nordisk, Roche, and Sanofi; honoraria for conferences from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Medtronic, Merck, Novo Nordisk, and Sanofi; consumable gifts (in-kind) from Abbott, Animas, Medtronic, and Roche; unrestricted grants for clinical and educational activities from Eli Lilly, LifeScan, Medtronic, Merck, Novo Nordisk, and Sanofi; patents for T2D risk biomarkers, catheter life, and AP; and purchase fees related to AP from Eli Lilly. No other potential conflicts of interest relevant to this articles were reported.

Authors Contributions. N.T., V.M., M.L., A.H., and R.R.-L. designed the study. N.T., A.C.C., and V.M. acquired data. N.T. and M.L. performed data analysis. N.T., M.L., and R.R.-L. interpreted results. The algorithm was conceived by A.H. N.T. drafted the manuscript and A.C.C., V.M., M.L., A.H., and R.R.-L. revised it critically. All authors approved the final submitted version. R.R.-L. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the 77th Scientific Sessions of the American Diabetes Association, San Diego, CA, 9–13 June 2017, and at the 2018 Canadian Society of Endocrinology and Metabolism/Diabetes Canada Professional Conference and Annual Meetings, Halifax, Nova Scotia, Canada, 10–13 October 2018.

Clinical trials reg. no. NCT02490085, clinicaltrials.gov

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