The association of atrial fibrillation (AF) with ischemic stroke has long been recognized; yet, the pathogenic mechanisms underlying this relationship are incompletely understood. Clinical schemas, ...such as the CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes mellitus, stroke/transient ischemic attack, vascular disease, age 65 to 74 years, sex category) score, incompletely account for thromboembolic risk, and emerging evidence suggests that stroke can occur in patients with AF even after sinus rhythm is restored. Atrial fibrosis correlates with both the persistence and burden of AF, and gadolinium-enhanced magnetic resonance imaging is gaining utility for detection and quantification of the fibrotic substrate, but methodological challenges limit its use. Factors related to evolution of the thrombogenic fibrotic atrial cardiomyopathy support the view that AF is a marker of stroke risk regardless of whether or not the arrhythmia is sustained. Antithrombotic therapy should be guided by a comprehensive assessment of intrinsic risk rather than the presence or absence of AF at a given time.
Diabetes mellitus is one of the most common chronic medical conditions, and is a risk factor for the development of atrial fibrillation (AF). The presence of diabetes in patients with AF is ...associated with increased symptom burden and increased cardiovascular and cerebrovascular mortality. The pathophysiology of diabetes-related AF is not fully understood, but is related to structural, electrical, electromechanical, and autonomic remodeling. This paper reviews the complex interaction between diabetes and AF, and explores its effect on the prevention and treatment of AF.
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning ...is a form of ML typically implemented via multi-layered neural networks. Deep learning has accelerated by recent advances in computer hardware and algorithms and is increasingly applied in e-commerce, finance, and voice and image recognition to learn and classify complex datasets. The current medical literature shows both strengths and limitations of DL. Strengths of DL include its ability to automate medical image interpretation, enhance clinical decision-making, identify novel phenotypes, and select better treatment pathways in complex diseases. Deep learning may be well-suited to cardiovascular medicine in which haemodynamic and electrophysiological indices are increasingly captured on a continuous basis by wearable devices as well as image segmentation in cardiac imaging. However, DL also has significant weaknesses including difficulties in interpreting its models (the 'black-box' criticism), its need for extensive adjudicated ('labelled') data in training, lack of standardization in design, lack of data-efficiency in training, limited applicability to clinical trials, and other factors. Thus, the optimal clinical application of DL requires careful formulation of solvable problems, selection of most appropriate DL algorithms and data, and balanced interpretation of results. This review synthesizes the current state of DL for cardiovascular clinicians and investigators, and provides technical context to appreciate the promise, pitfalls, near-term challenges, and opportunities for this exciting new area.
Thoracic Aortic Aneurysm and Dissection Goldfinger, Judith Z., MD; Halperin, Jonathan L., MD; Marin, Michael L., MD ...
Journal of the American College of Cardiology,
10/2014, Letnik:
64, Številka:
16
Journal Article
Recenzirano
Odprti dostop
Abstract Aortic dissection is the most devastating complication of thoracic aortic disease. In the more than 250 years since thoracic aortic dissection was first described, much has been learned ...about diseases of the thoracic aorta. In this review, we describe normal thoracic aortic size; risk factors for dissection, including genetic and inflammatory conditions; the underpinnings of genetic diseases associated with aneurysm and dissection, including Marfan syndrome and the role of transforming growth factor beta signaling; data on the role for medical therapies in aneurysmal disease, including beta-blockers, angiotensin receptor blockers, and angiotensin-converting enzyme inhibitors; prophylactic surgery for aneurysm; surgical techniques for the aortic root; and surgical and endovascular management of aneurysm and dissection for different aortic segments.
Purpose To examine the time burden of managing neovascular age-related macular degeneration (AMD) imposed on physicians, staff, patients, and caregivers. Design Mixed-methods, prospective, ...observational time-and-motion study. Methods The multicenter study was conducted from March 2011 through August 2012. Retina specialists administering ≥50 vascular endothelial growth factor (VEGF)–inhibitor injections monthly were surveyed and completed records for ≥5 patients scheduled for office visits within 3 weeks for anti-VEGF injection or monitoring. A survey was administered to 75 neovascular AMD patients aged ≥50 years who received ≥1 anti-VEGF injection in the past 6 months. Telephone interviews were conducted with 13 neovascular AMD patient caregivers. Results Fifty-six physicians provided data for 221 patients with neovascular AMD. Patients accounted for 20% of the health care staff's time per week, with an average of 23 staff members. An average patient visit for neovascular AMD was 90 minutes (range: 13 minutes to >4 hours). Patients reported an average time per visit of almost 12 hours, including preappointment preparation (16 minutes), travel (66 minutes), waiting time (37 minutes), treatment time (43 minutes), and postappointment recovery (9 hours). Patients stated that caregivers took time away from work (22%) and personal activities (28%) to provide transportation to appointments. Conclusions Neovascular AMD management imposes a substantial time burden on physicians, staff, patients, and caregivers. There may be a need for additional support and/or reimbursement for services required by patients and caregivers and provided by physicians.
The cardiovascular system is affected broadly by severe acute respiratory syndrome coronavirus 2 infection. Both direct viral infection and indirect injury resulting from inflammation, endothelial ...activation, and microvascular thrombosis occur in the context of coronavirus disease 2019. What determines the extent of cardiovascular injury is the amount of viral inoculum, the magnitude of the host immune response, and the presence of co-morbidities. Myocardial injury occurs in approximately one-quarter of hospitalized patients and is associated with a greater need for mechanical ventilator support and higher hospital mortality. The central pathophysiology underlying cardiovascular injury is the interplay between virus binding to the angiotensin-converting enzyme 2 receptor and the impact this action has on the renin-angiotensin system, the body's innate immune response, and the vascular response to cytokine production. The purpose of this review was to describe the mechanisms underlying cardiovascular injury, including that of thromboembolic disease and arrhythmia, and to discuss their clinical sequelae.
The multicenter PROTECT AF study (Watchman Left Atrial Appendage System for Embolic Protection in Patients With Atrial Fibrillation) was conducted to determine whether percutaneous left atrial ...appendage closure with a filter device (Watchman) was noninferior to warfarin for stroke prevention in atrial fibrillation.
Patients (n=707) with nonvalvular atrial fibrillation and at least 1 risk factor (age >75 years, hypertension, heart failure, diabetes, or prior stroke/transient ischemic attack) were randomized to either the Watchman device (n=463) or continued warfarin (n=244) in a 2:1 ratio. After device implantation, warfarin was continued for ≈45 days, followed by clopidogrel for 4.5 months and lifelong aspirin. Study discontinuation rates were 15.3% (71/463) and 22.5% (55/244) for the Watchman and warfarin groups, respectively. The time in therapeutic range for the warfarin group was 66%. The composite primary efficacy end point included stroke, systemic embolism, and cardiovascular death, and the primary analysis was by intention to treat. After 1588 patient-years of follow-up (mean 2.3±1.1 years), the primary efficacy event rates were 3.0% and 4.3% (percent per 100 patient-years) in the Watchman and warfarin groups, respectively (relative risk, 0.71; 95% confidence interval, 0.44%-1.30% per year), which met the criteria for noninferiority (probability of noninferiority >0.999). There were more primary safety events in the Watchman group (5.5% per year; 95% confidence interval, 4.2%-7.1% per year) than in the control group (3.6% per year; 95% confidence interval, 2.2%-5.3% per year; relative risk, 1.53; 95% confidence interval, 0.95-2.70).
The "local" strategy of left atrial appendage closure is noninferior to "systemic" anticoagulation with warfarin. PROTECT AF has, for the first time, implicated the left atrial appendage in the pathogenesis of stroke in atrial fibrillation.
: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00129545.
Atrial fibrillation (AF) is associated with thrombus formation in the left atrial appendage and systemic embolic events including ischemic stroke. Cardiogenic thromboembolism can also occur in the ...absence of clinical AF as a result of various pathological conditions affecting the endocardium. The inconsistent temporal relation between AF and ischemic events has stimulated exploration for factors other than clinical AF that contribute to thromboembolism. These include subclinical AF, a thrombogenic atrial cardiomyopathy, and left atrial appendage dysfunction and embolism from other sources. In conclusion, thromboembolism during normal sinus rhythm is likely multifactorial, involving intertwined pathologic processes. Patients at risk, if accurately identified, could theoretically benefit from anticoagulation.
No conflict of interest in data monitoring Halperin, Jonathan L
Science (American Association for the Advancement of Science),
12/2018, Letnik:
362, Številka:
6419
Journal Article
Ambulatory monitoring is increasingly important for cardiovascular care but is often limited by the unpredictability of cardiovascular events, the intermittent nature of ambulatory monitors and the ...variable clinical significance of recorded data in patients. Technological advances in computing have led to the introduction of novel physiological biosignals that can increase the frequency at which abnormalities in cardiovascular parameters can be detected, making expert-level, automated diagnosis a reality. However, use of these biosignals for diagnosis also raises numerous concerns related to accuracy and actionability within clinical guidelines, in addition to medico-legal and ethical issues. Analytical methods such as machine learning can potentially increase the accuracy and improve the actionability of device-based diagnoses. Coupled with interoperability of data to widen access to all stakeholders, seamless connectivity (an internet of things) and maintenance of anonymity, this approach could ultimately facilitate near-real-time diagnosis and therapy. These tools are increasingly recognized by regulatory agencies and professional medical societies, but several technical and ethical issues remain. In this Review, we describe the current state of cardiovascular monitoring along the continuum from biosignal acquisition to the identification of novel biosensors and the development of analytical techniques and ultimately to regulatory and ethical issues. Furthermore, we outline new paradigms for cardiovascular monitoring.
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