Abstract:The progression from cardiac injury to symptomatic heart failure has been intensely studied over the last decade, and is largely attributable to a loss of functional cardiac myocytes through necrosis, intrinsic and extrinsic apoptosis pathways and autophagy. Therefore, the molecular regulation of these cellular programs has been rigorously investigated in the hopes of identifying a potential cell target that could promote cell survival and/or inhibit cell death to avert, or at least prolong, the degeneration toward symptomatic heart failure. The nuclear factor (NF)-B super family of transcription factors has been implicated in the regulation of immune cell maturation, cell survival, and inflammation in many cell types, including cardiac myocytes. Recent studies have shown that NF-B is cardioprotective during acute hypoxia and reperfusion injury. However, prolonged activation of NF-B appears to be detrimental and promotes heart failure by eliciting signals that trigger chronic inflammation through enhanced elaboration of cytokines including tumor necrosis factor ␣, interleukin-1, and interleukin-6, leading to endoplasmic reticulum stress responses and cell death. The underlying mechanisms that account for the multifaceted and differential outcomes of NF-B on cardiac cell fate are presently unknown. Herein, we posit a novel paradigm in which the timing, duration of activation, and cellular context may explain mechanistically the differential outcomes of NF-B signaling in the heart that may be essential for future development of novel therapeutic interventions designed to target NF-B responses and heart failure following myocardial injury. (Circ Res. 2011;108:1122-1132.)

Despite the acknowledged importance of uremic pruritus to patients, with the exception of gabapentin, the current evidence for treatments is weak. Large, simple, rigorous, multiarm RCTs of promising therapies are urgently needed.

BackgroundAs the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A1c (HbA1c) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear.ObjectiveThe primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA1c levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA1c levels compared with controls.MethodsThe study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA1c levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app.ResultsThe results of an analysis of covariance controlling for baseline HbA1c levels did not show evidence of intervention impact on HbA1c levels at 3 months (mean difference [ITG−WLC] −0.42, 95% CI −1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA1c levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants’ 3-month HbA1c levels (95% CI −0.03 to −0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51).ConclusionsThe results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA1c levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed.Trial RegistrationClinicaltrials.gov NCT02813343; https://clinicaltr...

Background Applications of artificial intelligence (AI) in health care have garnered much attention in recent years, but the implementation issues posed by AI have not been substantially addressed. Objective In this paper, we have focused on machine learning (ML) as a form of AI and have provided a framework for thinking about use cases of ML in health care. We have structured our discussion of challenges in the implementation of ML in comparison with other technologies using the framework of Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies (NASSS). Methods After providing an overview of AI technology, we describe use cases of ML as falling into the categories of decision support and automation. We suggest these use cases apply to clinical, operational, and epidemiological tasks and that the primary function of ML in health care in the near term will be decision support. We then outline unique implementation issues posed by ML initiatives in the categories addressed by the NASSS framework, specifically including meaningful decision support, explainability, privacy, consent, algorithmic bias, security, scalability, the role of corporations, and the changing nature of health care work. Results Ultimately, we suggest that the future of ML in health care remains positive but uncertain, as support from patients, the public, and a wide range of health care stakeholders is necessary to enable its meaningful implementation. Conclusions If the implementation science community is to facilitate the adoption of ML in ways that stand to generate widespread benefits, the issues raised in this paper will require substantial attention in the coming years.

Background The development of new virtual care technologies (including telehealth and telemedicine) is growing rapidly, leading to a number of challenges related to health policy and planning for health systems around the world. Methods We brought together a diverse group of health system stakeholders, including patient representatives, to engage in policy dialogue to set health system priorities for the application of virtual care in the primary care sector in the Province of Ontario, Canada. We applied a nominal group technique (NGT) process to determine key priorities, and synthesized these priorities with group discussion to develop recommendations for virtual care policy. Methods included a structured priority ranking process, open-ended note-taking, and thematic analysis to identify priorities. Results Recommendations were summarized under the following themes: (a) identify clear health system leadership to embed virtual care strategies into all aspects of primary and community care; (b) make patients the focal point of health system decision-making; (c) leverage incentives to achieve meaningful health system improvements; and (d) building virtual care into streamlined workflows. Two key implications of our policy dialogue are especially relevant for an international audience. First, shifting the dialogue away from technology toward more meaningful patient engagement will enable policy planning for applications of technology that better meet patients' needs. Second, a strong conceptual framework on guiding the meaningful use of technology in health care settings is essential for intelligent planning of virtual care policy. Conclusions Policy planning for virtual care needs to shift toward a stronger focus on patient engagement to understand patients' needs.

Background: There is uncertainty regarding which pharmacological agents most effectively prevent venous thromboembolism in hospitalized medical patients. We therefore performed a meta-analysis to determine this.

Background The COVID-19 health crisis has disproportionately impacted populations who have been historically marginalized in health care and public health, including low-income and racial and ethnic minority groups. Members of marginalized communities experience undue barriers to accessing health care through virtual care technologies, which have become the primary mode of ambulatory health care delivery during the COVID-19 pandemic. Insights generated during the COVID-19 pandemic can inform strategies to promote health equity in virtual care now and in the future. Objective The aim of this study is to generate insights arising from literature that was published in direct response to the widespread use of virtual care during the COVID-19 pandemic, and had a primary focus on providing recommendations for promoting health equity in the delivery of virtual care. Methods We conducted a narrative review of literature on health equity and virtual care during the COVID-19 pandemic published in 2020, describing strategies that have been proposed in the literature at three levels: (1) policy and government, (2) organizations and health systems, and (3) communities and patients. Results We highlight three strategies for promoting health equity through virtual care that have been underaddressed in this literature: (1) simplifying complex interfaces and workflows, (2) using supportive intermediaries, and (3) creating mechanisms through which marginalized community members can provide immediate input into the planning and delivery of virtual care. Conclusions We conclude by outlining three areas of work that are required to ensure that virtual care is employed in ways that are equity enhancing in a post–COVID-19 reality.

Background-A survival role for the transcription factor nuclear factor-B (NF-B) in ventricular myocytes has been reported; however, the underlying mechanism is undefined. In this report we provide new mechanistic evidence that survival signals conferred by NF-B impinge on the hypoxia-inducible death factor BNIP3.