Literature DB >> 26886163

Expert Study: Utility of an Automated Bolus Advisor System in Patients with Type 1 Diabetes Treated with Multiple Daily Injections of Insulin-A Crossover Study.

Cintia Gonzalez1,2, María José Picón3, Monica Tomé3, Isabel Pujol1, Jose Carlos Fernández-García3, Ana Chico1,2.   

Abstract

OBJECTIVE: This study was designed to assess the impact of the use of an automated bolus advisor (ABA) on glycemic control, quality of life, and satisfaction in adult patients with type 1 diabetes mellitus treated with multiple daily injections of insulin.
MATERIALS AND METHODS: A crossover, prospective, randomized, controlled, multicenter study of 36 weeks duration was conducted. Patients were randomized to start in either control phase (CP) using a traditional blood glucose meter to calculate insulin doses (Accu-Chek(®) Aviva Nano; Roche Diagnostics, Indianapolis, IN) or intervention phase (IP) using an ABA meter (Accu-Chek Aviva Expert; Roche Diagnostics) and switched to the other phase after a washout period. Each phase was 12 weeks in duration.
RESULTS: Significant glycated hemoglobin (HbA1c) reduction was observed in both phases (CP, initial HbA1c of 8.05 ± 0.7%, final HbA1c of 7.59 ± 0.7% [P < 0.001]; IP, initial HbA1c of 8.13 ± 1%, final HbA1c of 7.61 ± 0.8% [P < 0.001]). Although the trend was to a higher HbA1c reduction in IP, no statistically significant differences were observed between phases (CP, HbA1c -0.39%; IP, HbA1c -0.52% [P = 0.8]). During IP, the number of daily glucose measurements was greater (4.28 ± 1.2 vs. 4.01 ± 1.1 [P < 0.006]), the rate of postprandial hypoglycemia was lower, and an improvement in quality of life and higher satisfaction were observed.
CONCLUSIONS: In this first crossover study comparing the use of an ABA with the standard usual care, the use of an ABA was effective and well accepted. Furthermore, reduction in hypoglycemic events, improvement in adherence and quality of life, and higher treatment satisfaction were observed.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 26886163     DOI: 10.1089/dia.2015.0383

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  5 in total

1.  Bolus Calculator Safety Mandates a Need for Standards.

Authors:  John Walsh; Guido Freckmann; Ruth Roberts; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2016-12-20

2.  Role of Automation/Technology in Day-to-Day Diabetes Care.

Authors:  Vikash Dadlani; Yogish C Kudva
Journal:  Diabetes Technol Ther       Date:  2016-03-30       Impact factor: 6.118

3.  Bolus Calculator Reduces Hypoglycemia in the Short Term and Fear of Hypoglycemia in the Long Term in Subjects with Type 1 Diabetes (CBMDI Study).

Authors:  María Del Rosario Vallejo Mora; Mónica Carreira; María Teresa Anarte; Francisca Linares; Gabriel Olveira; Stella González Romero
Journal:  Diabetes Technol Ther       Date:  2017-06-08       Impact factor: 6.118

Review 4.  Hypoglycaemia in type 1 diabetes: technological treatments, their limitations and the place of psychology.

Authors:  Pratik Choudhary; Stephanie A Amiel
Journal:  Diabetologia       Date:  2018-02-08       Impact factor: 10.122

Review 5.  Improving patient self-care using diabetes technologies.

Authors:  Valeria Alcántara-Aragón
Journal:  Ther Adv Endocrinol Metab       Date:  2019-01-28       Impact factor: 3.565

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.