Effect of frequency of sensor use on glycaemic control in individuals on sensor-augmented pump therapy with and without Predictive Low Glucose Management System

Mary B Abraham; Grant J Smith; Jennifer A Nicholas; Janice M Fairchild; Bruce R King; Geoffrey R Ambler; Fergus J Cameron; Elizabeth A Davis; Timothy W Jones; PLGM study group

doi:10.1016/j.diabres.2019.107989

Effect of frequency of sensor use on glycaemic control in individuals on sensor-augmented pump therapy with and without Predictive Low Glucose Management System

Diabetes Res Clin Pract. 2020 Jan:159:107989. doi: 10.1016/j.diabres.2019.107989. Epub 2019 Dec 19.

Authors

Affiliations

¹ Children's Diabetes Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia; Department of Endocrinology and Diabetes, Perth Children's Hospital, Perth, Australia; Division of Paediatrics, within the Medical School, The University of Western Australia, Perth, Australia. Electronic address: [email protected].
² Department of Endocrinology and Diabetes, Perth Children's Hospital, Perth, Australia.
³ Children's Diabetes Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia; Department of Endocrinology and Diabetes, Perth Children's Hospital, Perth, Australia.
⁴ Department of Endocrinology and Diabetes, Women's and Children's Hospital, Adelaide, Australia.
⁵ Department of Endocrinology and Diabetes, John Hunter Children's Hospital, Newcastle, Australia.
⁶ Institute of Endocrinology and Diabetes, The Children's Hospital at Westmead, The University of Sydney, Sydney, Australia.
⁷ Department of Endocrinology and Diabetes, Royal Children's Hospital, Melbourne, Australia.
⁸ Children's Diabetes Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia; Department of Endocrinology and Diabetes, Perth Children's Hospital, Perth, Australia; Division of Paediatrics, within the Medical School, The University of Western Australia, Perth, Australia.
⁹ Children's Diabetes Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia; Department of Endocrinology and Diabetes, Women's and Children's Hospital, Adelaide, Australia; Department of Endocrinology and Diabetes, John Hunter Children's Hospital, Newcastle, Australia; Institute of Endocrinology and Diabetes, The Children's Hospital at Westmead, The University of Sydney, Sydney, Australia; Department of Endocrinology and Diabetes, Royal Children's Hospital, Melbourne, Australia.

PMID: 31866529
DOI: 10.1016/j.diabres.2019.107989

Abstract

Improved frequency of sensor use improves glycaemic control. Furthermore, there is no deterioration of glycaemic control with increased sensor use in individuals on Predictive Low Glucose Management (PLGM) system. Younger children are more likely to have better sensor uptake than older children.

Keywords: Continuous glucose monitoring; Glycated haemoglobin; Predictive Low Glucose Management; Sensor; Sensor-augmented pump therapy; Time in range.

Publication types

Multicenter Study
Randomized Controlled Trial

MeSH terms

Adolescent
Adult
Biosensing Techniques / instrumentation
Biosensing Techniques / methods
Biosensing Techniques / statistics & numerical data
Blood Glucose / analysis*
Blood Glucose / metabolism
Blood Glucose Self-Monitoring / instrumentation
Blood Glucose Self-Monitoring / methods
Blood Glucose Self-Monitoring / statistics & numerical data
Child
Diabetes Mellitus, Type 1* / blood
Diabetes Mellitus, Type 1* / diagnosis
Diabetes Mellitus, Type 1* / drug therapy
Diabetes Mellitus, Type 1* / epidemiology
Female
Humans
Hyperglycemia / blood
Hyperglycemia / diagnosis
Hyperglycemia / drug therapy
Hyperglycemia / epidemiology
Hypoglycemia / chemically induced
Hypoglycemia / diagnosis*
Hypoglycemia / epidemiology
Hypoglycemia / therapy*
Incidence
Insulin / administration & dosage*
Insulin / adverse effects
Insulin Infusion Systems / standards
Insulin Infusion Systems / statistics & numerical data*
Male
Pancreas, Artificial / standards
Pancreas, Artificial / statistics & numerical data
Prognosis
Time Factors
Young Adult

Substances

Blood Glucose
Insulin