Login / Signup

Advances in Automated Insulin Delivery with the Medtronic 780G: The Australian Experience.

Bella HalimMary Binsu AbrahamGeorgina ManosArcelia ArrietaZheng DaiSara VogrinJean LuRichard MacIsaacElif I EkinciElizabeth A DavisAndrzej S JanuszewskiJohn ShinRobert A VigerskyTimothy W JonesDavid Norman O'Neal
Published in: Diabetes technology & therapeutics (2024)
Aim: To assess the real-world performance of MiniMed™ 780G for Australians with type 1 diabetes (T1D) following advanced hybrid closed loop (AHCL) activation and to evaluate the effect of changing from MiniMed 670/770G to 780G. Methods: We analyzed deidentified Carelink™ continuous glucose monitoring (CGM) data from Australian users from January 2020 to December 2022, including the proportion attaining three major consensus targets: Glucose management indicator (GMI <7.0%), time in range (TIR 70-180 mg/dL >70%), and time below range (TBR 70 mg/dL <4%). Results: Comparing 670/770G users ( n  = 5676) for mean ± standard deviation 364 ± 244 days with 780G users ( n  = 3566) for 146 ± 145 days, the latter achieved a higher TIR (72.6% ± 10.6% vs. 67.3% ± 11.4%; P  < 0.001), lower time above range (TAR) (25.5% ± 10.9% vs. 30.6% ± 11.7%; P  < 0.001), and lower GMI (6.9% ± 0.4% vs. 7.2% ± 0.4%; P  < 0.001) without compromising TBR (1.9% ± 1.8% vs. 2.0% ± 1.8%; P  = 0.0015). Of 1051 670/770G users transitioning to 780G, TIR increased (70.0% ± 10.7% to 74.0% ± 10.2%; P  < 0.001), TAR decreased (28.1% ± 10.9% to 24.0% ± 10.7%; P  < 0.001), and TBR was unchanged. The percentage of users attaining all three CGM targets was higher in 780G users (50.1% vs. 29.5%; P  < 0.001). CGM metrics were stable at 12 months post-transition. Conclusion: Real-world data from Australia shows that a higher proportion of MiniMed 780G users meet clinical targets for CGM consensus metrics compared to MiniMed 670/770G users and glucose control was sustained over 12 months.
Keyphrases
  • type diabetes
  • electronic health record
  • machine learning
  • clinical practice
  • big data
  • blood glucose
  • metabolic syndrome
  • deep learning
  • insulin resistance
  • skeletal muscle
  • glycemic control