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      Interactive Remote Patient Monitoring Devices for Managing Chronic Health Conditions: Systematic Review and Meta-analysis

      review-article
      , BSc, MSc, PhD 1 , 2 , , BSc, MSc, PhD 1 , 2 , , MRes, MBChB 3 , , BSc, MSc, PhD 1 , 2 , , BSc, MSc, PhD 4 , , MD 1 , 2 , , MBChB, MD 2 , , BSc, PhD 1 , 2 , , the TAILOR investigators 5
      (Reviewer), (Reviewer), (Reviewer)
      Journal of Medical Internet Research
      JMIR Publications
      chronic condition, telemonitoring, telemedicine, eHealth, self-monitoring, systematic review, meta-analysis

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          Abstract

          Background

          Telemedicine is an expanding and feasible approach to improve medical care for patients with long-term conditions. However, there is a poor understanding of patients’ acceptability of this technology and their rate of uptake.

          Objective

          The aim of this study was to systematically review the current evidence on telemonitoring in the management of patients with long-term conditions and evaluate the patients’ uptake and acceptability of this technology.

          Methods

          MEDLINE, Scopus, and CENTRAL (the Cochrane Central Register of Controlled Trials) were searched from the date of inception to February 5, 2021, with no language restrictions. Studies were eligible for inclusion if they reported any of the following outcomes: intervention uptake and adherence; study retention; patient acceptability, satisfaction, and experience using the intervention; changes in physiological values; all-cause and cardiovascular-related hospitalization; all-cause and disease-specific mortality; patient-reported outcome measures; and quality of life. In total, 2 reviewers independently assessed the articles for eligibility.

          Results

          A total of 96 studies were included, and 58 (60%) were pooled for the meta-analyses. Meta-analyses showed a reduction in mortality (risk ratio=0.71, 95% CI 0.56-0.89; P=.003; I 2=0%) and improvements in blood pressure (mean difference [MD]=−3.85 mm Hg, 95% CI −7.03 to −0.68; P=.02; I 2=100%) and glycated hemoglobin (MD=−0.33, 95% CI −0.57 to −0.09; P=.008; I 2=99%) but no significant improvements in quality of life (MD=1.45, 95% CI −0.10 to 3; P=.07; I 2=80%) and an increased risk of hospitalization (risk ratio=1.02, 95% CI 0.85-1.23; P=.81; I 2=79%) with telemonitoring compared with usual care. A total of 12% (12/96) of the studies reported adherence outcomes, and 9% (9/96) reported on satisfaction and acceptance outcomes; however, heterogeneity in the assessment methods meant that a meta-analysis could not be performed.

          Conclusions

          Telemonitoring is a valid alternative to usual care, reducing mortality and improving self-management of the disease, with patients reporting good satisfaction and adherence. Further studies are required to address some potential concerns regarding higher hospitalization rates and a lack of positive impact on patients’ quality of life.

          Trial Registration

          PROSPERO CRD42021236291; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=236291

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          Most cited references178

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            RoB 2: a revised tool for assessing risk of bias in randomised trials

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              ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

              Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                November 2022
                3 November 2022
                : 24
                : 11
                : e35508
                Affiliations
                [1 ] Department of Cardiovascular and Metabolic Medicine Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences University of Liverpool Liverpool United Kingdom
                [2 ] Liverpool Centre for Cardiovascular Science University of Liverpool and Liverpool Heart & Chest Hospital Liverpool United Kingdom
                [3 ] School of Medicine University of Liverpool Liverpool United Kingdom
                [4 ] Department of Musculoskeletal Ageing Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences University of Liverpool Liverpool United Kingdom
                [5 ] See acknowledgements
                Author notes
                Corresponding Author: Deirdre A Lane Deirdre.Lane@ 123456liverpool.ac.uk
                Author information
                https://orcid.org/0000-0002-0709-3073
                https://orcid.org/0000-0002-1479-8872
                https://orcid.org/0000-0003-4356-5231
                https://orcid.org/0000-0002-8846-0946
                https://orcid.org/0000-0002-3720-5152
                https://orcid.org/0000-0002-7566-1626
                https://orcid.org/0000-0002-5783-6648
                https://orcid.org/0000-0002-5604-9378
                Article
                v24i11e35508
                10.2196/35508
                9673001
                36326818
                5a8acfd7-62b3-4368-bf9a-83cfb70a2452
                ©Donato Giuseppe Leo, Benjamin J R Buckley, Mahin Chowdhury, Stephanie L Harrison, Masoud Isanejad, Gregory Y H Lip, David J Wright, Deirdre A Lane, the TAILOR investigators. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.11.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 9 December 2021
                : 18 February 2022
                : 7 April 2022
                : 29 April 2022
                Categories
                Review
                Review

                Medicine
                chronic condition,telemonitoring,telemedicine,ehealth,self-monitoring,systematic review,meta-analysis

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