Literature DB >> 24139705

Telemedicine and type 1 diabetes: is technology per se sufficient to improve glycaemic control?

S Franc1, S Borot2, O Ronsin3, J-L Quesada4, D Dardari5, C Fagour6, E Renard7, A-M Leguerrier8, C Vigeral9, F Moreau10, P Winiszewski11, A Vambergue12, H Mosnier-Pudar13, L Kessler10, S Reffet14, B Guerci15, L Millot16, S Halimi17, C Thivolet14, P-Y Benhamou18, A Penfornis2, G Charpentier19, H Hanaire20.   

Abstract

AIM: In the TELEDIAB-1 study, the Diabeo system (a smartphone coupled to a website) improved HbA1c by 0.9% vs controls in patients with chronic, poorly controlled type 1 diabetes. The system provided two main functions: automated advice on the insulin doses required; and remote monitoring by teleconsultation. The question is: how much did each function contribute to the improvement in HbA1c?
METHODS: Each patient received a smartphone with an insulin dose advisor (IDA) and with (G3 group) or without (G2 group) the telemonitoring/teleconsultation function. Patients were classified as "high users" if the proportion of "informed" meals using the IDA exceeded 67% (median) and as "low users" if not. Also analyzed was the respective impact of the IDA function and teleconsultations on the final HbA1c levels.
RESULTS: Among the high users, the proportion of informed meals remained stable from baseline to the end of the study 6months later (from 78.1±21.5% to 73.8±25.1%; P=0.107), but decreased in the low users (from 36.6±29.4% to 26.7±28.4%; P=0.005). As expected, HbA1c improved in high users from 8.7% [range: 8.3-9.2%] to 8.2% [range: 7.8-8.7%] in patients with (n=26) vs without (n=30) the benefit of telemonitoring/teleconsultation (-0.49±0.60% vs -0.52±0.73%, respectively; P=0.879). However, although HbA1c also improved in low users from 9.0% [8.5-10.1] to 8.5% [7.9-9.6], those receiving support via teleconsultation tended to show greater improvement than the others (-0.93±0.97 vs -0.46±1.05, respectively; P=0.084).
CONCLUSION: The Diabeo system improved glycaemic control in both high and low users who avidly used the IDA function, while the greatest improvement was seen in the low users who had the motivational support of teleconsultations.
Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Decision support software; Telemedicine; Telemonitoring; Type 1 diabetes

Mesh:

Substances:

Year:  2013        PMID: 24139705     DOI: 10.1016/j.diabet.2013.09.001

Source DB:  PubMed          Journal:  Diabetes Metab        ISSN: 1262-3636            Impact factor:   6.041


  15 in total

1.  Data-Driven Personalized Feedback to Patients with Type 1 Diabetes: A Randomized Trial.

Authors:  Stein Olav Skrøvseth; Eirik Årsand; Fred Godtliebsen; Ragnar M Joakimsen
Journal:  Diabetes Technol Ther       Date:  2015-03-09       Impact factor: 6.118

Review 2.  Evidence-based Mobile Medical Applications in Diabetes.

Authors:  Andjela Drincic; Priya Prahalad; Deborah Greenwood; David C Klonoff
Journal:  Endocrinol Metab Clin North Am       Date:  2016-10-08       Impact factor: 4.741

Review 3.  The empirical evidence for the telemedicine intervention in diabetes management.

Authors:  Rashid L Bashshur; Gary W Shannon; Brian R Smith; Maria A Woodward
Journal:  Telemed J E Health       Date:  2015-03-25       Impact factor: 3.536

4.  Remote Monitoring of Diabetes: A Cloud-Connected Digital System for Individuals With Diabetes and Their Health Care Providers.

Authors:  Michael Joubert; Pierre-Yves Benhamou; Pauline Schaepelynck; Hélène Hanaire; Bogdan Catargi; Anne Farret; Pierre Fontaine; Bruno Guerci; Yves Reznik; Nathalie Jeandidier; Alfred Penfornis; Sophie Borot; Lucy Chaillous; Sylvia Franc; Pierre Serusclat; Yacine Kherbachi; Eric Bavière; Bruno Detournay; Pierre Simon; Guillaume Charpentier
Journal:  J Diabetes Sci Technol       Date:  2019-03-12

5.  A Randomized Controlled, Treat-to-Target Study Evaluating the Efficacy and Safety of Insulin Glargine 300 U/mL (Gla-300) Administered Using Either Device-Supported or Routine Titration in People With Type 2 Diabetes.

Authors:  Melanie Davies; Steve Bain; Guillaume Charpentier; Frank Flacke; Harmonie Goyeau; Michael Woloschak; Christoph Hasslacher; Giacomo Vespasiani; Steven Edelman
Journal:  J Diabetes Sci Technol       Date:  2019-01-15

6.  Tele-diabetology to Screen for Diabetes and Associated Complications in Rural India: The Chunampet Rural Diabetes Prevention Project Model.

Authors:  Viswanathan Mohan; Vijayaraghavan Prathiba; Rajendra Pradeepa
Journal:  J Diabetes Sci Technol       Date:  2014-02-27

7.  Clinical evaluation of the use of a multifunctional remotely controlled insulin pump: multicenter observational study.

Authors:  Robert Boizel; Michel Pinget; Karim Lachgar; Christopher G Parkin; Hervé Grulet; Françoise Guillon-Metz; Joerg Weissmann
Journal:  J Diabetes Sci Technol       Date:  2014-08-07

Review 8.  Rapid Evidence Review of Mobile Applications for Self-management of Diabetes.

Authors:  Stephanie Veazie; Kara Winchell; Jennifer Gilbert; Robin Paynter; Ilya Ivlev; Karen B Eden; Kerri Nussbaum; Nicole Weiskopf; Jeanne-Marie Guise; Mark Helfand
Journal:  J Gen Intern Med       Date:  2018-05-08       Impact factor: 5.128

Review 9.  Commercial Smartphone-Based Devices and Smart Applications for Personalized Healthcare Monitoring and Management.

Authors:  Sandeep Kumar Vashist; E Marion Schneider; John H T Luong
Journal:  Diagnostics (Basel)       Date:  2014-08-18

10.  Quality of Life Differences in Pre- and Post-Educational Treatment in Type 1 Diabetes Mellitus During COVID-19.

Authors:  Nur Rochmah; Muhammad Faizi; Yuni Hisbiyah; Ike Wahyu Triastuti; Garindra Wicaksono; Anang Endaryanto
Journal:  Diabetes Metab Syndr Obes       Date:  2021-06-28       Impact factor: 3.168

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