Simone Del Favero1, Federico Boscari2, Mirko Messori3, Ivana Rabbone4, Riccardo Bonfanti5, Alberto Sabbion6, Dario Iafusco7, Riccardo Schiaffini8, Roberto Visentin1, Roberta Calore1, Yenny Leal Moncada1, Silvia Galasso2, Alfonso Galderisi9, Valeria Vallone2, Federico Di Palma3, Eleonora Losiouk10, Giordano Lanzola10, Davide Tinti4, Andrea Rigamonti5, Marco Marigliano6, Angela Zanfardino7, Novella Rapini11, Angelo Avogaro2, Daniel Chernavvsky12, Lalo Magni3, Claudio Cobelli13, Daniela Bruttomesso2. 1. Department of Information Engineering, University of Padua, Padua, Italy. 2. Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua, Italy. 3. Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy. 4. Department of Pediatrics, University of Turin, Turin, Italy. 5. Pediatric Department and Diabetes Research Institute, Scientific Institute, Hospital San Raffaele, Milan, Italy. 6. Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy. 7. Department of Pediatrics, Second University of Naples, Naples, Italy. 8. Unit of Endocrinology and Diabetes, Bambino Gesù Children's Hospital, Rome, Italy. 9. Department of Women's and Children's Health, University of Padua, Padua, Italy. 10. Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy. 11. Pediatric Diabetology Unit, Policlinico di Tor Vergata, University of Rome Tor Vergata, Rome, Italy. 12. Center for Diabetes Technology, University of Virginia, Charlottesville, VA. 13. Department of Information Engineering, University of Padua, Padua, Italy cobelli@dei.unipd.it.
Abstract
OBJECTIVE: The Pediatric Artificial Pancreas (PedArPan) project tested a children-specific version of the modular model predictive control (MMPC) algorithm in 5- to 9-year-old children during a camp. RESEARCH DESIGN AND METHODS: A total of 30 children, 5- to 9-years old, with type 1 diabetes completed an outpatient, open-label, randomized, crossover trial. Three days with an artificial pancreas (AP) were compared with three days of parent-managed sensor-augmented pump (SAP). RESULTS:Overnight time-in-hypoglycemia was reduced with the AP versus SAP, median (25(th)-75(th) percentiles): 0.0% (0.0-2.2) vs. 2.2% (0.0-12.3) (P = 0.002), without a significant change of time-in-target, mean: 56.0% (SD 22.5) vs. 59.7% (21.2) (P = 0.430), but with increased mean glucose 173 mg/dL (36) vs. 150 mg/dL (39) (P = 0.002). Overall, the AP granted a threefold reduction of time-in-hypoglycemia (P < 0.001) at the cost of decreased time-in-target, 56.8% (13.5) vs. 63.1% (11.0) (P = 0.022) and increased mean glucose 169 mg/dL (23) vs. 147 mg/dL (23) (P < 0.001). CONCLUSIONS: This trial, the first outpatient single-hormone AP trial in a population of this age, shows feasibility and safety of MMPC in young children. Algorithm retuning will be performed to improve efficacy.
RCT Entities:
OBJECTIVE: The Pediatric Artificial Pancreas (PedArPan) project tested a children-specific version of the modular model predictive control (MMPC) algorithm in 5- to 9-year-old children during a camp. RESEARCH DESIGN AND METHODS: A total of 30 children, 5- to 9-years old, with type 1 diabetes completed an outpatient, open-label, randomized, crossover trial. Three days with an artificial pancreas (AP) were compared with three days of parent-managed sensor-augmented pump (SAP). RESULTS: Overnight time-in-hypoglycemia was reduced with the AP versus SAP, median (25(th)-75(th) percentiles): 0.0% (0.0-2.2) vs. 2.2% (0.0-12.3) (P = 0.002), without a significant change of time-in-target, mean: 56.0% (SD 22.5) vs. 59.7% (21.2) (P = 0.430), but with increased mean glucose 173 mg/dL (36) vs. 150 mg/dL (39) (P = 0.002). Overall, the AP granted a threefold reduction of time-in-hypoglycemia (P < 0.001) at the cost of decreased time-in-target, 56.8% (13.5) vs. 63.1% (11.0) (P = 0.022) and increased mean glucose 169 mg/dL (23) vs. 147 mg/dL (23) (P < 0.001). CONCLUSIONS: This trial, the first outpatient single-hormone AP trial in a population of this age, shows feasibility and safety of MMPC in young children. Algorithm retuning will be performed to improve efficacy.
Authors: Laya Ekhlaspour; Gregory P Forlenza; Daniel Chernavvsky; David M Maahs; R Paul Wadwa; Mark D Deboer; Laurel H Messer; Marissa Town; Jennifer Pinnata; Geoff Kruse; Boris P Kovatchev; Bruce A Buckingham; Marc D Breton Journal: Pediatr Diabetes Date: 2019-05-23 Impact factor: 4.866
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Authors: Boris Kovatchev; Stacey M Anderson; Dan Raghinaru; Yogish C Kudva; Lori M Laffel; Carol Levy; Jordan E Pinsker; R Paul Wadwa; Bruce Buckingham; Francis J Doyle; Sue A Brown; Mei Mei Church; Vikash Dadlani; Eyal Dassau; Laya Ekhlaspour; Gregory P Forlenza; Elvira Isganaitis; David W Lam; John Lum; Roy W Beck Journal: Diabetes Care Date: 2020-01-14 Impact factor: 19.112
Authors: Stacey M Anderson; Eyal Dassau; Dan Raghinaru; John Lum; Sue A Brown; Jordan E Pinsker; Mei Mei Church; Carol Levy; David Lam; Yogish C Kudva; Bruce Buckingham; Gregory P Forlenza; R Paul Wadwa; Lori Laffel; Francis J Doyle; J Hans DeVries; Eric Renard; Claudio Cobelli; Federico Boscari; Simone Del Favero; Boris P Kovatchev Journal: Diabetes Technol Ther Date: 2019-01-16 Impact factor: 6.118
Authors: Boris P Kovatchev; Laura Kollar; Stacey M Anderson; Charlotte Barnett; Marc D Breton; Kelly Carr; Rachel Gildersleeve; Mary C Oliveri; Christian A Wakeman; Sue A Brown Journal: Lancet Digit Health Date: 2020-01-03
Authors: Jennifer L Sherr; Neha S Patel; Camille I Michaud; Miladys M Palau-Collazo; Michelle A Van Name; William V Tamborlane; Eda Cengiz; Lori R Carria; Eileen M Tichy; Stuart A Weinzimer Journal: Diabetes Care Date: 2016-05-05 Impact factor: 19.112