Background: To evaluate the efficacy of a run-to-run (R2R) adaptive wearable artificial pancreas (AP) after 1 month of closed-loop glucose control in subjects with type 1 diabetes (T1D) under free-living conditions. Methods: Eighteen adults, who had previously completed a 1-month closed-loop study with a non-adaptive artificial pancreas (NA-AP), volunteered for an additional 1-month extension study in which the AP was equipped with an adaptive model predictive control algorithm (R2R-AP). Continuous glucose monitoring data were analyzed on an intention-to-treat basis by comparing the last week of R2R-AP versus the last week of NAAP. The primary endpoint was the time in target range (3.9–10 mmol/L) over 24 h. Results: Time in target with R2R-AP is higher than with the NA-AP, although the increase was not significant: mean 66.90% (standard deviation: 13.34) versus 61.82% (11.12), P = 0.10. The increase was significant during the night: 74.01% (14.61) versus 64.31% (15.71), P = 0.03, and at wake-up time: median 92.43% (25th; 75th percentiles: 78.22; 99.53) versus 84.54% (57.14; 88.52), P = 0.02. Time above target (>10 mmol/L) during the whole day was 30.98% (13.22) versus 36.17% (11.53), P = 0.10. The decrease was significant during the night: 24.23% (15.03) versus 34.49% (16.25), P = 0.03, and at wake-up time: 7.57% (0.00; 14.29) versus 14.29% (8.25; 42.86), P = 0.05. Time spent below target (<3.9 mmol/L) was low and similar to the two treatments. Conclusions: R2R-AP improves glucose control over NA-AP in subjects with T1D during the night, and it maintains equivalent control performance during the day in a 1-month trial under free-living conditions.

Individually Adaptive Artificial Pancreas in Subjects with Type 1 Diabetes: A One-Month Proof-of-Concept Trial in Free-Living Conditions

Messori, Mirko;Del Favero, Simone;Toffanin, Chiara;Di Palma, Federico;Lanzola, Giordano;Magni, Lalo;
2017

Abstract

Background: To evaluate the efficacy of a run-to-run (R2R) adaptive wearable artificial pancreas (AP) after 1 month of closed-loop glucose control in subjects with type 1 diabetes (T1D) under free-living conditions. Methods: Eighteen adults, who had previously completed a 1-month closed-loop study with a non-adaptive artificial pancreas (NA-AP), volunteered for an additional 1-month extension study in which the AP was equipped with an adaptive model predictive control algorithm (R2R-AP). Continuous glucose monitoring data were analyzed on an intention-to-treat basis by comparing the last week of R2R-AP versus the last week of NAAP. The primary endpoint was the time in target range (3.9–10 mmol/L) over 24 h. Results: Time in target with R2R-AP is higher than with the NA-AP, although the increase was not significant: mean 66.90% (standard deviation: 13.34) versus 61.82% (11.12), P = 0.10. The increase was significant during the night: 74.01% (14.61) versus 64.31% (15.71), P = 0.03, and at wake-up time: median 92.43% (25th; 75th percentiles: 78.22; 99.53) versus 84.54% (57.14; 88.52), P = 0.02. Time above target (>10 mmol/L) during the whole day was 30.98% (13.22) versus 36.17% (11.53), P = 0.10. The decrease was significant during the night: 24.23% (15.03) versus 34.49% (16.25), P = 0.03, and at wake-up time: 7.57% (0.00; 14.29) versus 14.29% (8.25; 42.86), P = 0.05. Time spent below target (<3.9 mmol/L) was low and similar to the two treatments. Conclusions: R2R-AP improves glucose control over NA-AP in subjects with T1D during the night, and it maintains equivalent control performance during the day in a 1-month trial under free-living conditions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1209549
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