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Background: The proliferation of digital technology has the potential to transform diabetes management. One of the critical aspects of modern diabetes management remains the achievement of glycemic targets to avoid acute and long-term complications., Objective: This study aims to describe the landscape of evidence pertaining to the relative effectiveness or efficacy and safety of various digital interventions for the self-management of type 2 diabetes mellitus (T2DM), with a primary focus on reducing glycated hemoglobin A 1c (HbA 1c ) levels., Methods: A systematic literature review (SLR) was conducted by searching Embase, MEDLINE, and CENTRAL on April 5, 2022. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. Eligibility criteria for the SLR included randomized controlled trials (RCTs) and comparative observational studies evaluating interventions containing both human (eg, coaching) and digital components (eg, glucose meter) in adult patients with T2DM. The primary meta-analysis was restricted to studies that reported laboratory-measured HbA 1c . In secondary analyses, meta-regression was performed with the intensity of coaching in the digital intervention as a categorical covariate., Results: In total, 28 studies were included in this analysis. Most studies (23/28, 82%) used the reduction of HbA 1c levels as the primary end point, either directly or as a part of a multicomponent outcome. In total, 21 studies reported statistically significant results with this primary end point. When stratified into 3 intervention categories by the intensity of the intervention supporting the digital health technology (analyzing all 28 studies), the success rate appeared to be proportional to the coaching intensity (ie, higher-intensity studies reported higher success rates). When the analysis was restricted to RCTs using the comparative improvement of HbA 1c levels, the effectiveness of the interventions was less clear. Only half (12/23, 52%) of the included RCTs reported statistically significant results. The meta-analyses were broadly aligned with the results of the SLR. The primary analysis estimated a greater reduction in HbA 1c associated with digital interventions compared with usual care (-0.31%, 95% CI -0.45% to -0.16%; P<.001). Meta-regression estimated reductions of -0.45% (95% CI -0.81% to -0.09%; P=.02), -0.29% (95% CI -0.48% to -0.11%; P=.003), and -0.28% (95% CI -0.65% to 0.09%; P=.20) associated with high-, medium-, and low-intensity interventions, respectively., Conclusions: These findings suggest that reducing HbA 1c levels in individuals with T2DM with the help of digital interventions is feasible, effective, and acceptable. One common feature of effective digital health interventions was the availability of timely and responsive personalized coaching by a dedicated health care professional., (©David Kerr, David Ahn, Kayo Waki, Jing Wang, Boris Breznen, David C Klonoff. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.07.2024.)

The widespread adoption of mobile technologies offers an opportunity for a new approach to post-discharge care for patients with heart failure (HF). By enabling non-invasive remote monitoring and two-way, real-time communication between the clinic and home-based patients, as well as a host of other capabilities, mobile technologies have a potential to significantly improve remote patient care. This literature review summarizes clinical evidence related to virtual healthcare (VHC), defined as a care team + connected devices + a digital solution in post-release care of patients with HF. Searches were conducted on Embase (06/12/2020). A total of 171 studies were included for data extraction and evidence synthesis: 96 studies related to VHC efficacy, and 75 studies related to AI in HF. In addition, 15 publications were included from the search on studies scaling up VHC solutions in HF within the real-world setting. The most successful VHC interventions, as measured by the number of reported significant results, were those targeting reduction in rehospitalization rates. In terms of relative success rate, the two most effective interventions targeted patient self-care and all-cause hospital visits in their primary endpoint. Among the three categories of VHC identified in this review (telemonitoring, remote patient management, and patient self-empowerment) the integrated approach in remote patient management solutions performs the best in decreasing HF patients' re-admission rates and overall hospital visits. Given the increased amount of data generated by VHC technologies, artificial intelligence (AI) is being investigated as a tool to aid decision making in the context of primary diagnostics, identifying disease phenotypes, and predicting treatment outcomes. Currently, most AI algorithms are developed using data gathered in clinic and only a few studies deploy AI in the context of VHC. Most successes have been reported in predicting HF outcomes. Since the field of VHC in HF is relatively new and still in flux, this is not a typical systematic review capturing all published studies within this domain. Although the standard methodology for this type of reviews was followed, the nature of this review is qualitative. The main objective was to summarize the most promising results and identify potential research directions., Competing Interests: KCSL and AU report employment by Sanofi and may hold shares and/or stock options in the company. BB reports contract employment by Evidinno Outcomes Research Inc. FK is currently employed by Charité – Universitätsmedizin and has an ownership interest in Zentrum für kardiovaskuläre Telemedizin GmbH. FK has received research funding grants from the German Federal Ministry of Education and Research and grants from the Federal Ministry of Economic Affairs and Energy for conducting research and clinical trials in remote patient management. FK has received personal fees (honoraria) for lectures from Boston Scientific, Sanofi-Aventis Deutschland GmbH, Biotronik SE & Co. KG, Novartis, Linde/Saúde, Roche Pharma AG, Amgen GmbH and Astra Zeneca outside the submitted work. FK is co-holder of the patents PCT/EP2020/058700, European Patent Application No. 19166382.2, No. 19166425.9, No. 19175720.2. FK has received personal fees for advisory boards from Abbott, Sanofi-Aventis Deutschland GmbH and Biotronik Se & Co. KG. FK is a member of the European Society of Cardiology (ESC), German Cardiac Society (DGK), German Society for Internal Medicine (DGIM) and German Centre for Cardiovascular Research (DHZK). SSM is supported by the American Heart Association (20SFRN35380046 and COVID19-811000), PCORI (ME-2019C1-15328), NIH (P01 HL108800), the Aetna Foundation, the David and June Trone Family Foundation, the Pollin Digital Innovation Fund, the PJ Schafer Cardiovascular Research Fund, Sandra and Larry Small, CASCADE FH, Apple, Google, and Amgen. Under a license agreement between Corrie Health and the Johns Hopkins University, the University owns equity in Corrie Health, and the University and SSM are entitled to royalty distributions related to the technology. In addition, SSM is a co-founder of, and holds equity in Corrie Health. This arrangement has been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. SSM reports consulting in the last 36 months with Amgen, AstraZeneca, DalCor, Esperion, iHealth, Kaneka, Novartis, Novo Nordisk, Sanofi, Regeneron, REGENXBIO, and 89bio., (© 2023 Lee, Breznen, Ukhova, Martin and Koehler.)