Literature DB >> 35308155

Home Telemonitoring of Patients With Type 2 Diabetes: A Meta-Analysis and Systematic Review.

Xu Zhu1,2, Myia Williams1,2,3,4, Kayla Finuf1,2, Vidhi Patel1,2, Liron Sinvani1,2,3,4,5, Gisele Wolf-Klein2,3, Allison Marziliano2,3,4, Christian Nouryan1,2,3,4, Amgad Makaryus3,4,6,7, Roman Zeltser3,4,6,7, Leanne Tortez8, Tanya Shkolnikov1, Alyson Myers2,3,4,9, Renee Pekmezaris1,2,3,4,10.   

Abstract

Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (-0.10 mmHg [P = 0.0041] and -0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.
© 2022 by the American Diabetes Association.

Entities:  

Year:  2022        PMID: 35308155      PMCID: PMC8914593          DOI: 10.2337/ds21-0023

Source DB:  PubMed          Journal:  Diabetes Spectr        ISSN: 1040-9165


  37 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

2.  A Randomized Trial on Home Telemonitoring for the Management of Metabolic and Cardiovascular Risk in Patients with Type 2 Diabetes.

Authors:  Antonio Nicolucci; Stefania Cercone; Alberto Chiriatti; Fabrizio Muscas; Gianfranco Gensini
Journal:  Diabetes Technol Ther       Date:  2015-07-08       Impact factor: 6.118

Review 3.  Does telemedicine improve treatment outcomes for diabetes? A meta-analysis of results from 55 randomized controlled trials.

Authors:  Dejun Su; Junmin Zhou; Megan S Kelley; Tzeyu L Michaud; Mohammad Siahpush; Jungyoon Kim; Fernando Wilson; Jim P Stimpson; José A Pagán
Journal:  Diabetes Res Clin Pract       Date:  2016-04-26       Impact factor: 5.602

4.  Effects of telemonitoring on glycaemic control and healthcare costs in type 2 diabetes: A randomised controlled trial.

Authors:  Robin Warren; Karen Carlisle; Gabor Mihala; Paul A Scuffham
Journal:  J Telemed Telecare       Date:  2017-08-16       Impact factor: 6.184

5.  Web-based telemedicine for management of type 2 diabetes through glucose uploads: a randomized controlled trial.

Authors:  Peiru Zhou; Lingli Xu; Xueyan Liu; Jiewei Huang; Wanping Xu; Weiju Chen
Journal:  Int J Clin Exp Pathol       Date:  2014-12-01

6.  A randomized controlled trial of a nurse short-message service by cellular phone for people with diabetes.

Authors:  Hee-Seung Kim
Journal:  Int J Nurs Stud       Date:  2006-04-17       Impact factor: 5.837

7.  Shared care combined with telecare improves glycemic control of diabetic patients in a rural underserved community.

Authors:  Jhao-Kun Liou; Maw-Soan Soon; Ching-Hui Chen; Tzu-Fan Huang; Yi-Ping Chen; Yen-Po Yeh; Chun-Ju Chang; Shou-Jen Kuo; Ming-Chia Hsieh
Journal:  Telemed J E Health       Date:  2013-12-09       Impact factor: 3.536

8.  Effect of Internet therapeutic intervention on A1C levels in patients with type 2 diabetes treated with insulin.

Authors:  Hugh D Tildesley; Adel B Mazanderani; Stuart A Ross
Journal:  Diabetes Care       Date:  2010-08       Impact factor: 19.112

9.  Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control.

Authors:  Charlene C Quinn; Michelle D Shardell; Michael L Terrin; Erik A Barr; Shoshana H Ballew; Ann L Gruber-Baldini
Journal:  Diabetes Care       Date:  2011-07-25       Impact factor: 19.112

10.  The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method.

Authors:  Joanna IntHout; John P A Ioannidis; George F Borm
Journal:  BMC Med Res Methodol       Date:  2014-02-18       Impact factor: 4.615

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