Background: Automatization of insulin delivery by closed-loop systems represents a major step in type 1 diabetes management. The aim of this study was to analyze the effect of the commercialized hybrid closed-loop system, the MiniMed 670G system, on glycemic control, glycemic variability, and patient satisfaction. Methods: A prospective study, including type 1 diabetes patients consecutively starting on the 670G system in one adult and two pediatric hospitals, was performed. Baseline and 3-month visits were documented. Two weeks of data from the system were downloaded. Glycemic variability measures were calculated. Adults and adolescents completed a set of questionnaires (Gold and Clarke scores, Hypoglycemia Fear Survey, Diabetes Quality of Life [DQoL], Diabetes Treatment Satisfaction [DTS], Diabetes Distress Scale, Pittsburgh Sleep Quality Index). Results: Fifty-eight patients were included (age: 28 ± 15 years [7-63], <18 years old: 38% [n = 22], 59% [n = 34] females, previous use of SAP-PLGS [predictive low-glucose suspend]: 60% [n = 35]). HbA1c was reduced from 57 ± 10 to 53 ± 7 mmol/L (7.4% ± 0.9% to 7.0% ± 0.6%) (P < 0.001) and time in range 70-180 mg/dL was increased from 63.0% ± 11.4% to 72.7% ± 8.7% (P < 0.001). In patients with high baseline hypoglycemia risk, time <54 and <70 mg/dL were reduced from 0.9% ± 1.1% to 0.45% ± 0.7% (P = 0.021) and from 3.3% ± 2.8% to 2.1% ± 2.1% (P = 0.019), respectively. Glycemic variability measures improved. Time in auto mode was 85% ± 17%, the number of auto mode exits was 0.6 ± 0.3 per day, and the number of alarms was 8.5 ± 3.7 per day. Fear of hypoglycemia, DQoL, DTS, and diabetes distress improved, while the percentage of patients with poor sleep quality was reduced. The discontinuation rate was 3%. Conclusion: The commercialized hybrid closed-loop system improves glycemic control and glycemic variability in children and adults, reducing the burden of living with type 1 diabetes.
Background: Automatization of insulin delivery by closed-loop systems represents a major step in type 1 diabetes management. The aim of this study was to analyze the effect of the commercialized hybrid closed-loop system, the MiniMed 670G system, on glycemic control, glycemic variability, and patient satisfaction. Methods: A prospective study, including type 1 diabetespatients consecutively starting on the 670G system in one adult and two pediatric hospitals, was performed. Baseline and 3-month visits were documented. Two weeks of data from the system were downloaded. Glycemic variability measures were calculated. Adults and adolescents completed a set of questionnaires (Gold and Clarke scores, Hypoglycemia Fear Survey, Diabetes Quality of Life [DQoL], Diabetes Treatment Satisfaction [DTS], Diabetes Distress Scale, Pittsburgh Sleep Quality Index). Results: Fifty-eight patients were included (age: 28 ± 15 years [7-63], <18 years old: 38% [n = 22], 59% [n = 34] females, previous use of SAP-PLGS [predictive low-glucose suspend]: 60% [n = 35]). HbA1c was reduced from 57 ± 10 to 53 ± 7 mmol/L (7.4% ± 0.9% to 7.0% ± 0.6%) (P < 0.001) and time in range 70-180 mg/dL was increased from 63.0% ± 11.4% to 72.7% ± 8.7% (P < 0.001). In patients with high baseline hypoglycemia risk, time <54 and <70 mg/dL were reduced from 0.9% ± 1.1% to 0.45% ± 0.7% (P = 0.021) and from 3.3% ± 2.8% to 2.1% ± 2.1% (P = 0.019), respectively. Glycemic variability measures improved. Time in auto mode was 85% ± 17%, the number of auto mode exits was 0.6 ± 0.3 per day, and the number of alarms was 8.5 ± 3.7 per day. Fear of hypoglycemia, DQoL, DTS, and diabetes distress improved, while the percentage of patients with poor sleep quality was reduced. The discontinuation rate was 3%. Conclusion: The commercialized hybrid closed-loop system improves glycemic control and glycemic variability in children and adults, reducing the burden of living with type 1 diabetes.
Authors: Bruno Bombaci; Stefano Passanisi; Angela Alibrandi; Giulia D'Arrigo; Serena Patroniti; Simona Averna; Giuseppina Salzano; Fortunato Lombardo Journal: Int J Environ Res Public Health Date: 2022-08-18 Impact factor: 4.614
Authors: Arcelia Arrieta; Tadej Battelino; Andrea E Scaramuzza; Julien Da Silva; Javier Castañeda; Toni L Cordero; John Shin; Ohad Cohen Journal: Diabetes Obes Metab Date: 2022-05-12 Impact factor: 6.408
Authors: Susan Kohl Malone; Amy J Peleckis; Laura Grunin; Gary Yu; Sooyong Jang; James Weimer; Insup Lee; Michael R Rickels; Namni Goel Journal: J Diabetes Res Date: 2021-02-12 Impact factor: 4.011
Authors: Anders L Carlson; Jennifer L Sherr; Dorothy I Shulman; Satish K Garg; Rodica Pop-Busui; Bruce W Bode; David R Lilenquist; Ron L Brazg; Kevin B Kaiserman; Mark S Kipnes; James R Thrasher; John H Chip Reed; Robert H Slover; Athena Philis-Tsimikas; Mark Christiansen; Benyamin Grosman; Anirban Roy; Melissa Vella; Richard A M Jonkers; Xiaoxiao Chen; John Shin; Toni L Cordero; Scott W Lee; Andrew S Rhinehart; Robert A Vigersky Journal: Diabetes Technol Ther Date: 2021-11-16 Impact factor: 6.118