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Many people with Type 2 diabetes (T2D) who could benefit from digital health technologies (DHTs) are either not using DHTs or do use them, but not for long enough to reach their behavioral or metabolic goals. We aimed to identify subgroups within DHT adopters and non-adopters and describe their unique profiles to better understand the type of tailored support needed to promote effective and sustained DHT use across a diverse T2D population. We conducted latent class analysis of a sample of adults with T2D who responded to an internet survey between December 2021 and March 2022. We describe the clinical and psychological characteristics of DHT adopters and non-adopters, and their attitudes toward DHTs. A total of 633 individuals were characterized as either DHT "Adopters" (n = 376 reporting any use of DHT) or "Non-Adopters" (n = 257 reporting never using any DHT). Within Adopters, three subgroups were identified: 21% (79/376) were "Self-managing Adopters," who reported high health activation and self-efficacy for diabetes management, 42% (158/376) were "Activated Adopters with dropout risk," and 37% (139/376) were "Non-Activated Adopters with dropout risk." The latter two subgroups reported barriers to using DHTs and lower rates of intended future use. Within Non-Adopters, two subgroups were identified: 31% (79/257) were "Activated Non-Adopters," and 69% (178/257) were "Non-Adopters with barriers," and were similarly distinguished by health activation and barriers to using DHTs. Beyond demographic characteristics, psychological, and clinical factors may help identify different subgroups of Adopters and Non-Adopters., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Graphical AbstractAdherence to cardiac rehabilitation following a primary event has been demonstrated to improve quality of life, increase functional capacity, and decrease hospitalizations and mortality. Mobile technologies offer an opportunity to improve both the quality and utilization of cardiac rehabilitation, and recent clinical studies investigated this technology. This literature review summarizes the current use of mobile health, wearable activity monitors (WAMs), and other multi-component technologies deployed to support home-based virtual cardiac rehabilitation. The methodology was adapted from the Cochrane Handbook for Systematic Reviews of Interventions . We identified 2094 records, of which 113 were eligible for qualitative analysis. Different virtual cardiac rehabilitation solutions were implemented in the studies: (i) multi-component interventions in 48 studies (42.5%), (ii) WAMs in 27 studies (23.9%), (iii) web-based communications solutions, and (iv) mobile apps, both in 19 studies (16.4%). Functional capacity was the most frequently reported primary outcome ( k = 37, 32.7%), followed by user adherence/compliance ( k = 35, 31.0%), physical activity ( k = 27, 23.9%), and quality of life ( k = 14, 12.4%). Studies provided a mixed assessment of the efficacy of virtual cardiac rehabilitation in attaining either significant improvements over baseline or significant improvements in outcomes compared with conventional rehabilitation. Efficacy outcomes with virtual cardiac rehabilitation sometimes improve on the centre-based outcomes; however, superior clinical efficacy may not necessarily be the only outcome of interest. The promise of virtual cardiac rehabilitation includes the potential for increased user adherence and longer-term patient engagement. If these outcomes can be improved, that would be a significant justification for using this technology., Competing Interests: Conflict of interest: K.C.S.L. and A.U. report employment by Sanofi and may hold shares and/or stock options in the company. B.B. reports contract employment by Evidinno Outcomes Research Inc. F.K. is currently employed by Charité—Universitätsmedizin and has an ownership interest in Zentrum für kardiovaskuläre Telemedizin GmbH. F.K. 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. F.K. 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. F.K. is co-holder of the patents PCT/EP2020/058700, European Patent Application No. 19166382.2, No. 19166425.9, and No. 19175720.2. F.K. has received personal fees for advisory boards from Abbott, Sanofi-Aventis Deutschland GmbH, and Biotronik Se & Co. KG. F.K. 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). S.S.M. reports research support from American Heart Association (20SFRN35380046, 20SFRN35490003, 878924, 882415), PCORI (ME-2019C1-15328), National Institutes of Health (R01AG071032, P01 HL108800), the David and June Trone Family Foundation, and Pollin Digital Health 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 S.S.M. are entitled to royalty distributions related to the technology. In addition, S.S.M. 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. S.S.M. reports consulting in the last 24 months with Amgen, AstraZeneca, DalCor, iHealth, Kaneka, NewAmsterdam, Novartis, Novo Nordisk, Sanofi, and 89bio. The authors report no other conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: To revisit the data analysis used to inform National Institute of Health and Care Excellence (NICE) NG17 guidance for initiating basal insulin in adults with type 1 diabetes mellitus (diabetes)., Methods: We replicated the data, methodology and analysis used by NICE diabetes in the NG17 network meta-analysis (NMA). We expanded this data cohort to a more contemporary data set (extended 2017 NMA) and restricted the studies included to improve the robustness of the data set (restricted 2017 NMA) and in a post hoc analysis, changed the index comparator from neutral protamine Hagedorn (NPH) insulin twice daily to insulin detemir twice daily., Results: The absolute changes in HbA 1c were similar to those reported in the NG17. However, all 95% credible intervals for change in HbA 1c point estimates crossed the line of null effect, except for detemir twice daily (in the NICE and extended 2017 NMAs) and NPH four times daily. In the detemir twice-daily centred post hoc analysis, the 95% credible intervals for change in HbA 1c crossed the line of null effect for all basal therapies, except NPH., Conclusions: In NG17, comparisons of basal insulins were based solely on efficacy of glycaemic control. Many of the trials used in this analysis were treat-to-target, which minimize differences in HbA 1c . In the NMAs, statistical significance was severely undermined by the wide credible intervals. Despite these limitations, point estimates of HbA 1c were used to rank the insulins and formed the basis of NG17 guidance. This study queries whether such analyses should be used to make specific clinical recommendations., (© 2019 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Aim: To conduct an open-label study to provide UK real-world evidence regarding the use of insulin glargine 300 units/ml (U300) in people with Type 1 diabetes mellitus., Methods: People with Type 1 diabetes who had been prescribed U300 ≥6 months before data collection and had HbA 1c levels recorded within 3 months prior to U300 (baseline) were included. The primary endpoint was change in HbA 1c from baseline to month 6 after U300 initiation. Other endpoints included number of documented hypoglycaemic and diabetic ketoacidosis episodes, and change in daily basal insulin dose., Results: A total of 298 people with Type 1 diabetes were included [mean age 42.1 years, mean HbA 1c 79 mmol/mol (9.4%)]. After U300 initiation, the mean reduction in HbA 1c from baseline to month 6 was -4 mmol/mol (-0.4%; P<0.001; n=188). The total daily basal insulin dose at 6 months was 1.3 units higher than at the time of U300 initiation (P<0.001; n=275) but was not significantly different from the prior basal insulin dose. There was no clinically significant difference in weight between baseline and month 6 [mean difference +0.7 kg, 95% CI -0.1, 1.5; P=0.084; n=115). During the 6 months before and after U300 initiation, severe hypoglycaemic episodes were documented for 6/298 and 4/298 participants. Diabetic ketoacidosis episodes requiring Accident and Emergency department visits or hospitalization were documented for 4/298 and 6/298 participants, before and after U300 initiation, respectively., Conclusions: In people with Type 1 diabetes, a change in basal insulin to U300 was associated with clinically and statistically significant HbA 1c improvements, without significant changes in basal insulin dose and weight. Documented severe hypoglycaemia episodes and diabetic ketoacidosis requiring Accident and Emergency department visits or hospitalization were low and similar before and after U300 initiation., (© 2018 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)