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As an integral aspect of health care, digital technology has enabled modelling of complex relationships to detect, screen, diagnose, and predict patient outcomes. With massive data sets, artificial intelligence (AI) can have marked effects on 3 levels: for patients, clinicians, and health systems. In this review, we discuss contemporary AI-enabled wearable devices undergoing research in the field of cardiovascular medicine. These include devices such as smart watches, electrocardiogram patches, and smart textiles such as smart socks and chest sensors for diagnosis, management, and prognostication of conditions such as atrial fibrillation, heart failure, and hypertension as well as monitoring for cardiac rehabilitation. We review the evolution of machine learning algorithms used in wearable devices from random forest models to the use of convolutional neural networks and transformers. We further discuss frameworks for wearable technologies such as the V3-stage process of verification, analytical validation, and clinical validation as well as challenges of AI integration in medicine such as data veracity, validity, and security and provide a reference framework to maintain fairness and equity. Last, clinician and patient perspectives are discussed to highlight the importance of considering end-user feedback in development and regulatory processes.

A 26-year-old man experienced an unwitnessed syncopal event while brushing his teeth at night. He suffered trauma to his head and was found, unconscious on the floor, by his roommate. [...]

In a meta-analysis of 33 studies, cardiac MRI had higher sensitivity but similar specificity compared with fluorodeoxyglucose PET for diagnosis of cardiac sarcoidosis.

While COVID-19 is still ongoing and associated with more than 5 million deaths, the scope and speed of advances over the past year in terms of scientific discovery, data dissemination, and technology have been staggering. It is not a matter of “if” but “when” we will face the next pandemic, and how we leverage technology and data management effectively to create flexible ecosystems that facilitate collaboration, equitable care, and innovation will determine its severity and scale. The aim of this review is to address emerging challenges that came to light during the pandemic in health care and innovations that enabled us to adapt and continue to care for patients. The pandemic highlighted the need for seismic shifts in care paradigms and technology with considerations related to the digital divide and health literacy for digital health interventions to reach full potential and improve health outcomes. We discuss advances in telemedicine, remote patient monitoring, and emerging wearable technologies. Despite the promise of digital health, we emphasise the importance of addressing its limitations, including interpretation challenges, accuracy of findings, and artificial intelligence–driven algorithms. We summarise the most recent recommendation of the Virtual Care Task Force to scaling virtual medical services in Canada. Finally, we propose a model for optimal implementation of health digital innovations with 5 tenets including data management, data security, digital biomarkers, useful artificial intelligence, and clinical integration.

Supplemental Digital Content is available in the text.The left ventricular assist device (LVAD) is an established treatment for select patients with end-stage heart failure. Some patients recovered and are considered for explantation. Assessing recovery involves exercise testing and echo ramping on full and minimal LVAD support. Combined cardiopulmonary exercise testing with simultaneous echo ramping (CPET-R) has not been well studied. Patients were included if they had CPET within the previous 6 months, were clinically stable, and had an INR >2.0 on the day of examination. Patients had CPET-R on two occasions within 14 days: (a) with LVAD at therapeutic speed and (b) with LVAD at the lowest speed possible. Six patients were between 29 and 75 years (two female). One patient did not complete a turn-down test due to evidence of ischemia on initial CPET-R subsequently confirmed as a significant coronary artery stenosis on angiography. There were no significant differences in CPET or echo metrics between LVAD speeds. Two patients were explanted due to presumed LV recovery and remained event free for 30 and 47 months, respectively. Serial CPET-R seems safe and feasible for the evaluation of LV and global function and may result in improved clinical decision making for LVAD explantation.

A 66-year-old woman who recently completed Pleted a course of levofloxacin to treat community-acquired pneumonia presents sents to her family physician with a two-day history of watery diarrhea. Her stool [...]

Left ventricular assist devices (LVAD) can be implanted as either a bridge to transplantation (BTT) or destination therapy (DT). This definition is fluid, as some DT patients undergo transplantation. This study compared posttransplant outcomes between BTT and DT LVAD patients. We performed a retrospective analysis of LVAD patients who underwent cardiac transplantation from 2010 to 2016. Outcomes including mortality, rejection, infection, and overall readmission were assessed with univariable Cox analyses. This cohort included 92 LVAD patients underwent transplantation: 57 BTT, mean age 52 years, and 79% male. The DT group had a longer LVAD support time (median support 406 versus161 days, p< 0.001) with no significant difference in 1-year survival (BTT 86% and DT 92%, p= 0.52) or survival time (HR 0.89, 95% confidence interval [CI] 0.33–2.41, p= 0.82). Rates of nonfatal adverse events were also similar between BTT and DT patients. In our cohort, DT patients had similar long-term survival and rates of adverse events as compared with BTT, despite a longer time to transplant. This study suggests that transplant outcomes are acceptable for patients initially labeled DT and that a longer duration of LVAD support may not adversely affect posttransplant outcomes.

A previously well 67-year-old woman presents to her family physician with new-onset palpitations and fatigue over the last 6 weeks. These symptoms have adversely affected her quality of life, and [...]

A 60-year-old man with poorly controlled type 2 diabetes mellitus and associated neuropathy presents to his family doctor with a wound on the plantar aspect of his left foot. He [...]

Clinicians have strong opinions about whether they should be provided the clinical history before or after bedside testing. We hypothesized that diagnostic accuracy is improved when a concordant clinical history is provided before a diagnostic test. To investigate whether the timing (before or after) and the consistency (concordant vs discordant) of the clinical history in the setting of focused bedside echocardiography affects clinician diagnostic accuracy and management decisions. Thirty-two cardiology residents were asked to perform a bedside echocardiogram on a Vimedix 3D mannequin. Half of the histories were provided before echocardiography and half after echocardiography. Half were consistent with the echocardiographic diagnosis (concordant), and half were suggestive of a plausible alternative diagnosis (discordant). Participants were asked for a diagnosis and management plan. The primary outcome was the diagnostic accuracy of the echocardiographic images. The secondary outcome was the management plan. Overall diagnostic accuracy was 63%. If the clinical history was provided before the bedside testing, it significantly improved diagnostic accuracy if it was concordant and it diminished accuracy if it was discordant (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.16-0.80; P = 0.001). Clinical history, whether concordant or discordant, had no significant impact if provided after the images were obtained. Appropriate management was chosen 77% of the time and was chosen less often with discordant compared with concordant histories (OR, 0.25; 95% CI, 0.11-0.57; P = 0.001). Our study suggests a significant downside to clinical information received before echocardiography when the information is discordant, raising the possibility that receiving clinical information after echocardiography may be superior for diagnostic accuracy.

1 How is heart failure with reduced ejection fraction diagnosed? Heart failure with reduced ejection fraction is a clinical syndrome of dyspnea, exercise intolerance and/or edema resulting from an impairment [...]

Dyslipidemia is common in patients undergoing heart transplantation and is associated with the progression of cardiac allograft vasculopathy. Two monoclonal antibodies directed against PCSK9i—evolocumab and alirocumab—are currently available. However, their use, safety and efficacy in the post-transplant setting have not been studied. We present our experience with 6 heart transplant recipients treated with a PCSK9i. A > 70% reduction in LDL-cholesterol was observed after evolocumab therapy. PCSK9 inhibitors are a potentially lipid-lowering therapeutic option for heart transplant patients with suboptimal LDL despite maximal tolerated statin doses.

In a meta-analysis of 37 studies, late gadolinium enhancement at cardiac MRI and fluorodeoxyglucose uptake at PET were both predictive of major adverse events in cardiac sarcoidosis.

1 Bacterial meningitis is a medical emergency, and timely antibiotic therapy is critical A recent retrospective study including 125 adults with proven bacterial meningitis reported a 30% increase in unfavourable [...]

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

Quality improvement (QI) initiatives have become an integral part of patient-centered care. In this primer, we outline 6 steps for initiating, implementing, and monitoring improvement in heart failure care. These steps include acknowledging that improvement is needed and setting a culture for improvement; forming a QI team; understanding the local problem; generating improvement strategies that will fit with the local problem; monitoring; testing; and refining improvements, analysis of data, and interpretation of run charts. This primer provides tools and resources for clinicians who want to learn how to perform QI specifically in the field of heart failure. We will illustrate the application of these steps using a hypothetical example for a congestive heart failure postdischarge clinic.

Supplemental Digital Content is available in the text.