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A Wearable ECG Sensor for Intelligent Cardiovascular Health Informatics
Published in Teena Bagga, Kamal Upreti, Nishant Kumar, Amirul Hasan Ansari, Danish Nadeem, Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics, 2023
Dhanashri H. Gawali, Vijay M. Wadhai, Minakshee Patil, Akshita S. Chanchlani
As per the World Health Organization (WHO) estimate, 31% of deaths occurring worldwide are due to cardiovascular diseases (CVDs), out of which more than 75% of CVD deaths occur in low- and middle-income countries. Almost 80% of CVD deaths occur due to heart attack and stroke. CVDs remained the leading cause of death worldwide owing to various risk factors. Also, there is a potential threat of long-term impact on the cardiovascular system due to the recently emerged COVID-19 disease. Cardiovascular health informatics refers to the processing, storage, transmission, acquisition and retrieval of cardiac information for the early detection, early prediction, early prevention, early diagnosis and early treatment of CVDs [1]. The major goal is to detect symptoms or risk factors at an early stage using wearable sensors with higher sensitivity. The electrocardiogram (ECG) plays a vital role in the diagnosis and management of CVDs. ECG data enable the diagnosis of many cardiovascular abnormalities, including numerous arrhythmias, atrial fibrillation (AF), premature contractions of the atria (PAC) or ventricles (PVC), myocardial infarction (MI) and congestive heart failure (CHF) [2]. A few arrhythmias such as MI are life-threatening, while rare and serious arrhythmias such as Brugada syndrome, arrhythmogenic right ventricular cardiomyopathy, long QT syndrome, hypertrophic cardiomyopathy, etc., are infrequent and only get detected on prolonged monitoring. This requires innovative solutions to monitor ECG signal over longer durations of time. Artificial intelligence (AI) techniques such as machine learning, deep learning and cognitive computing have the potential for rapid and accurate interpretation of large digital ECG data for early detection and diagnosis of CVDs [3].
Imaging of Beta-Receptors in the Heart
Published in Robert J. Gropler, David K. Glover, Albert J. Sinusas, Heinrich Taegtmeyer, Cardiovascular Molecular Imaging, 2007
Jeanne M. Link, John R. Stratton, Wayne C. Levy, Jeanne Poole, James H. Caldwell
Despite more than 15 years of a quantitative PET methodology for measuring β-AR, there are few reports of imaging human β-AR density in disease. Merlet et al. found that B′max in the left ventricle was decreased in patients with idiopathic cardiomyopathy; 3.12 ± 0.51 pmol/mL in patients vs 6.60 ± 1.18 pmol/mL in normals (23). Schafers et al. found that in patients with hypertrophic cardiomyopathy B′max was decreased from 10.2 ± 2.9 (n = 19) pmol/g in normals to 7.3 ± 2.6 (n = 13) pmol/g in patients (32). The same group observed down regulation of B′max to 5.9 ± 1.3 pmol/g of tissue in patients with arrhythmogenic right ventricular cardiomyopathy (33). In ischemic patients with CHF we have found 9.8 ± 7.3 pmol/g for LV B′max of patients versus 12.8 ± 3.9 pmol/g for LV B′max in normals. Qing et al. found that for untreated asthma patients B′max was not significantly different, 9.1 ± 3.3 pmol/g versus 8.8 ± 2.3 pmol/g for normals, but the measured B′max decreased 19% from 8.4 ± 2.03 pmol/g in asthmatics treated with Albuterol (31). The only report using [11C]-CGP12388 for imaging human cardiac disease reported a 36% decrease in B′max in idiopathic cardiomyopathy, but no experimental details were provided by the authors (31). These imaging results are consistent with each other, and are also consistent with the decrease of 25% in β-AR density measured in vitro for cardiac tissue biopsies from heart failure patients (35). In these patients, the regional distribution of β-AR can be quite heterogeneous. The downregulation of β-AR in cardiomyopathies measured in vivo by imaging has provided interesting physiological confirmation of animal studies and human biopsy measures. The system is so tightly regulated that a 20% density difference is often all that is seen in many cardiac diseases from in vitro binding assays of tissue samples. Despite the small change, some clinical utility may come from imaging β-AR. For example, B′ max is reported to predict left ventricular volume six months postacute myocardial infarction (36). It may be that this difference is even greater in other diseases, for example, in diabetes (37).
Usefulness of insertable cardiac monitors for risk stratification: current indications and clinical evidence
Published in Expert Review of Medical Devices, 2023
Amira Assaf, Dominic AMJ Theuns, Michelle Michels, Jolien Roos-Hesselink, Tamas Szili-Torok, Sing-Chien Yap
Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by fibro fatty replacement of cardiac tissue, mainly localized to the right ventricle (RV), but LV involvement occurs in up to 50% of patients [80]. Mutations in genes encoding desmosomal proteins are the most common genetic cause. Patients with ARVC are at increased risk of VT (usually monomorphic) and SCD, usually between the second and fourth decade of life. Disease progression may result in chronic heart failure. The 2017 AHA/ACC/HRS VA/SCD guidelines recommend (Class I) a primary prevention ICD with a left ventricular ejection fraction (LVEF) or right ventricular ejection fraction (RVEF) ≤35% [17]. Furthermore, a primary prevention ICD should be considered (class IIa) in patients with arrhythmogenic syncope. In the 2022 ESC VA/SCD guidelines a primary prevention ICD should be considered (class IIa) in patients with arrhythmic syncope; patients with severe RV or LV dysfunction (≤35%); or symptomatic patients (presyncope or palpitations) with moderate RV or LV dysfunction and either NSVT or inducible sustained monomorphic VT [18]. It is important to recognize that survival benefit of an ICD is less clear in patients with hemodynamically tolerated VT. Using large international registry data, risk calculators have been developed to estimate the risk of future sustained VA/SCD to guide the decision to implant a prophylactic ICD (https://arvcrisk.com) [3,4,81]. Identified predictors of sustained VA/SCD were age, sex, cardiac syncope, frequent NSVT, premature ventricular complexes (PVC) burden, number of leads with T-wave inversion and RVEF.
Right ventricular function in elite male athletes meeting the structural echocardiographic task force criteria for arrhythmogenic right ventricular cardiomyopathy
Published in Journal of Sports Sciences, 2019
Mohammad Qasem, Keith George, John Somauroo, Lynsey Forsythe, Benjamin Brown, David Oxborough
ARVC is an inherited genetic disease that is characterized by a fibrofatty replacement of the RV myocardium (Marcus et al., 2010). Due to the variable phenotypical expression and clinical manifestation of the disease, its diagnosis remains challenging, particularly, in its early stages. The structural changes in ARVC may be absent or subtle and limited to a localized region of the RV called the “triangle of dysplasia” (Marcus et al., 2010; Rojas & Calkins, 2015), RV inflow tract (sinus), the RV apex, RV outflow tract (Aneq, 2011; Te Riele et al., 2013) or infundibulum (RVOT2) (Basso et al., 1996). Many studies have demonstrated that chronic exercise training leads to RV dilation and acute exercise causes disproportionate wall stress (Douglas & O’Toole, 1990; Heidbuchel, Prior, & La Gerche, 2012; Rojas & Calkins, 2015). Thus, previous athlete heart studies have demonstrated RV enlargement that exceeds the normal cut-off values and fulfill ARVC structural TFC (D’Ascenzi, Pelliccia, et al., 2017; D’Ascenzi, Pisicchio, et al., 2017; Oxborough et al., 2012; Zaidi et al., 2013). The current study reports a significant enlargement in absolute and scaled RVOT in both long and short axis views, fulfilling major TFC but in addition these athletes have a significant higher absolute and scaled RVOT2 value suggesting a proportional dilatation of the outflow tract. It is apparent that although the RVOT may be enlarged in these athletes there is a lack of proportional enlargement of the inflow and RVDA with an increased RVOT/RVD1 ratio. This finding is disparate from previous studies in endurance athletes (Oxborough et al., 2012). It is difficult to provide a clear explanation for this, but it must be acknowledged that a disproportionate remodeling occurs as physiological adaptation in some athletes irrespective of training stimulus. We can speculate that this may be driven by individual heterogeneity/genetics, but it is important to note that an increased RVOT/RVD1 ratio (approaching 1) does not indicate pathology.