Atrial fibrillation signatures on intracardiac electrograms identified by deep learning

Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events'. This may delay or misdirect therapy. Objective: We hypothesized that deep learning (DL) can accurately classify AF from AT by revealing electrogram (EGM) signatures. Methods: We studied 86 patients in whom the diagnosis of AF or AT was established at electrophysiological study (25 female, 65 ± 11 years). Custom DL architectures were trained to identify AF using N = 29,340 unipolar and N = 23,760 bipolar EGM segments. We compared DL to traditional classifiers based on rate or regularity. We explained DL using computer models to assess the impact of controlled variations in shape, rate and timing on AF/AT classification in 246,067 EGMs reconstructed from clinical data. Results: DL identified AF with AUC of 0.97 ± 0.04 (unipolar) and 0.92 ± 0.09 (bipolar). Rule-based classifiers misclassified ∼10-12% of cases. DL classification was explained by regularity in EGM shape (13%) or timing (26%), and rate (60%; p 15% timing variation, <0.48 correlation in beat-to-beat EGM shapes and CL < 190 ms (p < 0.001). Conclusions: Deep learning of intracardiac EGMs can identify AF or AT via signatures of rate, regularity in timing or shape, and specific EGM shapes. Future work should examine if these signatures differ between different clinical subpopulations with AF

In-Hospital Outcome In Patients With Acyanotic Congenital Heart Disease Undergoing Transcatheter Aortic Valve Replacement.

The purpose of the study was to determine the in-hospital outcome and resource utilization in patients with acyanotic congenital heart disease (ACHD) undergoing transcatheter aortic valve replacement (TAVR). Current guidelines from professional societies do not support TAVR in patients with ACHD, likely from a lack of supportive evidence. Temporal trends in patients with ACHD undergoing TAVR were determined using the 2016-2018 National Inpatient Sample database appropriate ICS-10-PCS code. Stata 16.0 was used for statistical analysis. 0.87% of patients undergoing TAVR had concomitant ACHD, with ASD being the most common (78%). After matching, there was no increased risk of mortality in ACHD patients undergoing TAVR compared to patients without ACHD (OR 1.43, P = 0.59). Additionally, no difference was found in the incidence of overall cardiac complications between patients with ACHD and patients without ACHD, except STEMI (OR 4.16, 95% CI, 1.08-16.00, P = 0.038), which is likely due to more comorbidity burden in the later cohort. Complications such as acute kidney injury, ischemic stroke, and bleeding were similar. Hospital resource utilization was higher in the ACHD group in the form of increased length of stay and higher mean total cost. The comparable in-hospital all-cause mortality and complication rate in ACHD patients undergoing TAVR compared to patients without ACHD is encouraging and will be helpful to design future randomized controlled trials

Healthcare Access Among Individuals of Asian Descent in the U.S.

Introduction. Some groups of Asian Americans, especially Asian Indians, experience higher rates of atherosclerotic cardiovascular disease (ASCVD) compared with other groups in the U.S. Barriers in accessing medical care partly may explain this higher risk as a result of delayed screening for cardiovascular risk factors and timely initiation of preventive treatment. Methods. Cross-sectional data were utilized from the 2006 to 2015 National Health Interview Survey (NHIS). Barriers to accessing medical care included no place to seek medical care when needed, no healthcare coverage, no care due to cost, delayed care due to cost, inability to afford medication, or not seeing a doctor in the past 12 months. Results. The study sample consisted of 18,150 Asian individuals, of whom 20.5% were Asian Indian, 20.5% were Chinese, 23.4% were Filipino, and 35.6% were classified as “Other Asians”. The mean (standard error) age was 43.8 (0.21) years and 53% were women. Among participants with history of hypertension, diabetes mellitus, or ASCVD (prevalence = 25%), Asian Indians were more likely to report delayed care due to cost (2.58 (1.14,5.85)), while Other Asians were more likely to report no care due to cost (2.43 (1.09,5.44)) or delayed care due to cost (2.35 (1.14,4.86)), compared with Chinese. Results among Filipinos were not statistically significant. Conclusions. Among Asians living in the U.S. with cardiovascular risk factors or ASCVD, Asian Indians and Other Asians are more likely to report delayed care or no care due to cost compared with Chinese

Artificial intelligence in gastroenterology: a state-of-the-art review

The development of artificial intelligence (AI) has increased dramatically in the last 20 years, with clinical applications progressively being explored for most of the medical specialties. The field of gastroenterology and hepatology, substantially reliant on vast amounts of imaging studies, is not an exception. The clinical applications of AI systems in this field include the identification of premalignant or malignant lesions (e.g., identification of dysplasia or esophageal adenocarcinoma in Barrett's esophagus, pancreatic malignancies), detection of lesions (e.g., polyp identification and classification, small-bowel bleeding lesion on capsule endoscopy, pancreatic cystic lesions), development of objective scoring systems for risk stratification, predicting disease prognosis or treatment response [e.g., determining survival in patients post-resection of hepatocellular carcinoma), determining which patients with inflammatory bowel disease (IBD) will benefit from biologic therapy], or evaluation of metrics such as bowel preparation score or quality of endoscopic examination. The objective of this comprehensive review is to analyze the available AI-related studies pertaining to the entirety of the gastrointestinal tract, including the upper, middle and lower tracts; IBD; the hepatobiliary system; and the pancreas, discussing the findings and clinical applications, as well as outlining the current limitations and future directions in this field.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Dual Antiplatelet Therapy: A Concise Review for Clinicians

Dual antiplatelet therapy (DAPT) combines two antiplatelet agents to decrease the risk of thrombotic complications associated with atherosclerotic cardiovascular diseases. Emerging data about the duration of DAPT is being published continuously. New approaches are trying to balance the time, benefits, and risks for patients taking DAPT for established cardiovascular diseases. Short-term dual DAPT of 3–6 months, or even 1 month in high-bleeding risk patients, is equivalent in terms of efficacy and effectiveness compared to long-term DAPT for patients who experienced percutaneous coronary intervention in an acute coronary syndrome setting. Prolonged DAPT beyond 12 months reduces stent thrombosis, major adverse cardiovascular events, and myocardial infarction rates but increases bleeding risk. Extended DAPT does not significantly benefit stable coronary artery disease patients in reducing stroke, myocardial infarction, or cardiovascular death. Ticagrelor and aspirin reduce cardiovascular events in stable coronary artery disease with diabetes but carry a higher bleeding risk. Antiplatelet therapy duration in atrial fibrillation patients after percutaneous coronary intervention depends on individual characteristics and bleeding risk. Antiplatelet therapy is crucial for post-coronary artery bypass graft and transcatheter aortic valve implantation; Aspirin (ASA) monotherapy is preferred. Antiplatelet therapy duration in peripheral artery disease depends on the scenario. Adding vorapaxar and cilostazol may benefit secondary prevention and claudication, respectively. Carotid artery disease patients with transient ischemic attack or stroke benefit from antiplatelet therapy and combining ASA and clopidogrel is more effective than ASA alone. The optimal duration of DAPT after carotid artery stenting is uncertain. Resistance to ASA and clopidogrel poses an incremental risk of deleterious cardiovascular events and stroke. The selection and duration of antiplatelet therapy in patients with cardiovascular disease requires careful consideration of both efficacy and safety outcomes. The use of combination therapies may provide added benefits but should be weighed against the risk of bleeding. Further research and clinical trials are needed to optimize antiplatelet treatment in different patient populations and clinical scenarios

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.</jats:p

Sleep, obesity and cardiometabolic disease in children and adolescents

© 2019 Elsevier Inc. All rights reserved. Obesity and type 2 diabetes mellitus was previously limited to adults, but in recent decades, there has been an increased prevalence among children and adolescents. Given the cost burden and a plethora of adverse consequences with which these diseases are associated, obesity and cardiometabolic diseases now pose a major public health challenge. Obesity and type 2 diabetes mellitus are chronic conditions that commonly track into adulthood and also increase the likelihood of cardiovascular consequences. While these diseases can be caused by genetics, they are largely driven by lifestyle behaviors. Attempts at addressing the global epidemic have targeted behavior modification such as increasing physical activity levels and controlling dietary intake in the hope of restoring energy balance. Sleep impinges on both side of the energy balance equation and there is now an abundance of evidence to suggest that multiple features of sleep may be contributing to the onset and progression of these chronic conditions, which are discussed in this chapter. In particular, we discuss the literature pertaining to the relationship between sleep and obesity as well as type 2 diabetes mellitus in children and adolescents, while also drawing upon crucial information from adult studies. We also highlight potential mechanisms and make recommendations for future approaches which may enhance the effectiveness of interventions targeting the global epidemic of childhood obesity, which is the main driver of metabolic and cardiovascular diseases

Nivel de conocimientos de estudiantes de medicina sobre diagnóstico y manejo del infarto agudo del miocardio

Introduction: acute myocardial infarction is a disease with high morbidity and mortality.Objective: to determine the knowledge level of medical students about the diagnosis and management of acute myocardial infarction.Method: an observational, descriptive and cross-sectional study was carried out between January and February 2022 in medical students from the University of Medical Sciences of Pinar del Río who participated in the provincial update workshop on acute myocardial infarction. Through intentional sampling, a sample of 92 students was selected. To collect the information, a survey was used using Google Forms.Results: the female sex (65,21%), the age group from 21 to 22 years (65,21%) and the fourth-year students (50%) prevailed. Hypertension was the most identified risk factor (97,98%). 97,82% of the students identified precordial pain as the main clinical manifestation. 100% identified the presentation with complications, where sudden death was the most identified (81,52%). 100% point to the electrocardiogram as the main complementary, where ST alterations were the most identified (84,78%). 95,65% of the students indicated constant monitoring of vital parameters and cardiovascular function as the management measure.Conclusions: Medicine students belonging to the clinical area at the University of Medical Sciences of Pinar del Río have an adequate level of knowledge about the diagnosis and management of acute myocardial infarction.Introducción: el infarto agudo del miocardio constituye una enfermedad con elevada morbilidad y mortalidad.Objetivo: determinar el nivel de conocimientos de estudiantes de medicina sobre el diagnóstico y manejo del infarto agudo del miocardioMétodo: se realizó un estudio observacional, descriptivo y transversal entre enero y febrero de 2022 en estudiantes de Medicina de la Universidad de Ciencias Médicas de Pinar del Río del ciclo clínico que participaron en el Taller provincial de actualización sobre infarto agudo de miocardio. Mediante un muestreo intencional se seleccionó una muestra de 92 estudiantes. Para la recolección de la información se empleó una encuesta mediante Google Forms.Resultados: predominó el sexo femenino (65,21 %), el grupo etario de 21 a 22 años (65,21 %) y los estudiantes de cuarto año (50 %). La hipertensión fue el factor de riesgo más identificado (97,98 %). El 97,82 % de los estudiantes identificó el dolor precordial como principal manifestación clínica. El 100 % identificó la presentación con complicaciones, donde la muerte súbita fue la más identificada (81,52 %). El 100 % señala al electrocardiograma como principal complementario, donde las alteraciones del ST fueron las más identificada (84,78 %). El 95,65 % de los estudiantes indicaron la monitorización constante de los parámetros vitales y función cardiovascular como la medida de manejo.Conclusiones: los estudiantes de Medicina pertenecientes al área clínica en la Universidad de Ciencias Médicas de Pinar del Río poseen un adecuado nivel de conocimientos sobre el diagnóstico y manejo del infarto agudo del miocardio.  

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics