Artificial intelligence cloud platform improves arrhythmia detection from insertable cardiac monitors to 25 cardiac rhythm patterns through multi-label classification.

BACKGROUND: Electrocardiogram (ECG) is the gold standard for the diagnosis of cardiac arrhythmias and other heart diseases. Insertable cardiac monitors (ICMs) have been developed to continuously monitor cardiac activity over long periods of time and to detect 4 cardiac patterns (atrial tachyarrhythmias, ventricular tachycardia, bradycardia, and pause). However, interpretation of ECG or ICM subcutaneous ECG (sECG) is time-consuming for clinicians. Artificial intelligence (AI) classifies ECG and sECG with high accuracy in short times. OBJECTIVE: To demonstrate whether an AI algorithm can expand ICM arrhythmia recognition from 4 to many cardiac patterns. METHODS: We performed an exploratory retrospective study with sECG raw data coming from 20 patients wearing a Confirm Rx™ (Abbott, Sylmar, USA) ICM. The sECG data were recorded in standard conditions and then analyzed by AI (Willem™, IDOVEN, Madrid, Spain) and cardiologists, in parallel. RESULTS: In nineteen patients, ICMs recorded 2261 sECGs in an average follow-up of 23 months. Within these 2261 sECG episodes, AI identified 7882 events and classified them according to 25 different cardiac rhythm patterns with a pondered global accuracy of 88%. Global positive predictive value, sensitivity, and F1-score were 86.77%, 83.89%, and 85.52% respectively. AI was especially sensitive for bradycardias, pauses, rS complexes, premature atrial contractions, and inverted T waves, reducing the median time spent to classify each sECG compared to cardiologists. CONCLUSION: AI can process sECG raw data coming from ICMs without previous training, extending the performance of these devices and saving cardiologists' time in reviewing cardiac rhythm patterns detection.

Current and Future Use of Artificial Intelligence in Electrocardiography.

Artificial intelligence (AI) is increasingly used in electrocardiography (ECG) to assist in diagnosis, stratification, and management. AI algorithms can help clinicians in the following areas: (1) interpretation and detection of arrhythmias, ST-segment changes, QT prolongation, and other ECG abnormalities; (2) risk prediction integrated with or without clinical variables (to predict arrhythmias, sudden cardiac death, stroke, and other cardiovascular events); (3) monitoring ECG signals from cardiac implantable electronic devices and wearable devices in real time and alerting clinicians or patients when significant changes occur according to timing, duration, and situation; (4) signal processing, improving ECG quality and accuracy by removing noise/artifacts/interference, and extracting features not visible to the human eye (heart rate variability, beat-to-beat intervals, wavelet transforms, sample-level resolution, etc.); (5) therapy guidance, assisting in patient selection, optimizing treatments, improving symptom-to-treatment times, and cost effectiveness (earlier activation of code infarction in patients with ST-segment elevation, predicting the response to antiarrhythmic drugs or cardiac implantable devices therapies, reducing the risk of cardiac toxicity, etc.); (6) facilitating the integration of ECG data with other modalities (imaging, genomics, proteomics, biomarkers, etc.). In the future, AI is expected to play an increasingly important role in ECG diagnosis and management, as more data become available and more sophisticated algorithms are developed.

Allometric scaling for normalizing maximal oxygen uptake in elite rugby union players / Normalización del consumo de oxígeno máximo por escala alométrica en jugadores de rugby unión de élite

Introduction: The relation of a biological variable to body mass is typically characterized by an allometric scaling law. Thepurpose of this study was to evaluate the relationship between oxygen consumption (VO2max), as a parameter of aerobicexercise performance, and body composition in rugby players. Material and method: The sample included one hundred and seven males of the Spanish rugby team. Age: 25.1 ± 3.4 years;body mass (BM): 89.8 ± 11.7 kg, height: 182.4 ± 6.5 cm; 52 backs (BR) and 55 forwards (FR). Maximum oxygen consumption(VO2max, l.min-1) was measured during treadmill exercise test with progressive workload. Anthropometrical measurementswere performed to estimate the fat-free mass (FFM) and muscle mass (MM). The allometric exponent “b” was determined fromequation y = a * xb; where “y” is VO2max and, “x” is the corresponding mass (BM, FFM or MM) and “a” is one constant. Results: The VO2max was 4.87 ± 0.56 l.min-1, BR vs FR, 4.67 ± 0.48 l.min-1 vs 5.06 ± 0.06 l.min-1; FFM: 77.5±7.7 kg, 73.5±7 kg vs81.3±6.3 kg; and MM: 52.9±6.5 kg, 49.6±5.6 kg vs 56.1±5.8 kg. The allometric exponents (p <0.0001; R2 = 0.4) were: 0.58 for BM(95% CI: 0.45 - 0.72); 0.71 for FFM (95% CI: 0.53 - 0.90); and 0.58 for MM (95% CI: 0.43 - 0.73). Significant differences (p <0.0001)were found BR vs FR according to their anthropometric characteristics and VO2max with respect to BM and MM without allo-metric scaling. While the VO2max indexed by means of allometric scaling was similar between BR and FR. Conclusions: In comparative studies, the VO2max should be expressed proportional to the 0.58 power of body mass or relatedto FFM in order to take into account the variability in of body composition in rugby players.(AU)

Introducción: La relación de una variable biológica con la masa corporal se caracteriza típicamente por una ley de escalaalométrica. El propósito del estudio fue evaluar la relación entre el consumo máximo de oxígeno (VO2max), como parámetrode rendimiento aeróbico, y la composición corporal en jugadores de rugby. Material y método: La muestra incluyó a 107 varones de la selección española de rugby. Edad: 25,1 ± 3,4 años; masa cor-poral (MC): 89,8 ± 11,7 kg, talla: 182,4 ± 6,5 cm; 52 defensas (DF) y 55 delanteros (DL). El VO2max (l.min-1) se determinó en tapizcon carga progresiva hasta el máximo esfuerzo. Mediante técnica antropométrica se estimó la masa libre de grasa (MLG) y lamasa muscular (MM). El exponente alométrico “b” se determinó por la ecuación y = a * xb; donde “y” es VO2max, “x” es la masacorrespondiente (MC, MLG o MM) y “a” es una constante. Resultados: El VO2max fue 4,87 ± 0,56 l.min-1, DF vs DL, 4,67 ± 0,48 l.min-1 vs 5,06 ± 0,06 l.min-1; MLG: 77,5 ± 7,7 kg, 73,5 ± 7 kg vs81,3 ± 6,3 kg; y MM: 52,9 ± 6,5 kg, 49,6 ± 5,6 kg vs 56,1 ± 5,8 kg. Los exponentes alométricos (p <0,0001; R2 = 0,4) fueron: 0,58para MC (IC 95%: 0,45 - 0,72); 0,71 para MLG (IC del 95%: 0,53 - 0,90); y 0,58 para MM (IC del 95%: 0,43 - 0,73). Se encontrarondiferencias significativas (p <0,0001) DF vs DL según sus características antropométricas y VO2max con respecto a BM y MM sinescalado alométrico. Mientras que el VO2max indexado mediante escalado alométrico fue similar entre DF y DL. Conclusiones: En estudios comparativos el VO2max debería expresarse a la potencia de 0.58 de MC o con MLG debido a lavariabilidad de la composición corporal en jugadores de rugby.(AU)

Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study.

Background: Insertable cardiac monitors (ICMs) are indicated for long-term monitoring of patients with unexplained syncope or who are at risk for cardiac arrhythmias. The volume of ICM-transmitted information may result in long data review times to identify true and clinically relevant arrhythmias. Objective: The purpose of this study was to evaluate whether artificial intelligence (AI) may improve ICM detection accuracy. Methods: We performed a retrospective analysis of consecutive patients implanted with the Confirm RxTM ICM (Abbott) and followed in a prospective observational study. This device continuously monitors subcutaneous electrocardiograms (SECGs) and transmits to clinicians information about detected arrhythmias and patient-activated symptomatic episodes. All SECGs were classified by expert electrophysiologists and by the WillemTM AI algorithm (IDOVEN). Results: During mean follow-up of 23 months, of 20 ICM patients (mean age 68 ± 12 years; 50% women), 19 had 2261 SECGs recordings associated with cardiac arrhythmia detections or patient symptoms. True arrhythmias occurred in 11 patients: asystoles in 2, bradycardias in 3, ventricular tachycardias in 4, and atrial tachyarrhythmias (atrial tachycardia/atrial fibrillation [AT/AF]) in 10; with 6 patients having >1 arrhythmia type. AI algorithm overall accuracy for arrhythmia classification was 95.4%, with 97.19% sensitivity, 94.52% specificity, 89.74% positive predictive value, and 98.55% negative predictive value. Application of AI would have reduced the number of false-positive results by 98.0% overall: 94.0% for AT/AF, 87.5% for ventricular tachycardia, 99.5% for bradycardia, and 98.8% for asystole. Conclusion: Application of AI to ICM-detected episodes is associated with high classification accuracy and may significantly reduce health care staff workload by triaging ICM data.

Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.

BACKGROUND: Patients with chest pain and persistent ST segment elevation (STE) may not have acute coronary occlusions or serum troponin curves suggestive of acute necrosis. Our objective is the validation and cost-effectiveness analysis of a diagnostic model assisted by artificial intelligence (AI). METHODS: Prospective multicenter registry in two groups of patients with STE: I) coronary arteries without significant lesions and without serum troponin curve suggestive of acute necrosis, II) myocardial infarction with acute coronary occlusion. The inclusion criteria are the following: 1) age ≥ 18 years, 2) chest pain or symptoms suggestive of myocardial ischemia, 3) STE at point J in two contiguous leads ≥0.1 mV, in V2 and V3 ≥ 0,2 mV and 4) signature of informed consent. The exclusion criteria are the following: 1) left bundle branch block, 2) acute cardiac necrosis in the absence of significant epicardial coronary artery stenosis, 3) STE ≤ 0.1 mV with pathologic Q wave, 4) severe anemia (hemoglobin <8.0 g/dl). For each patient without acute cardiac necrosis, the next patient from that center of the same sex and similar age (± 5 years) with myocardial infarction and acute coronary occlusion will be included. A manual centralized electrocardiographic analysis and another by deep learning AI will be performed. CONCLUSIONS: The results of the study will provide new information for the stratification of patients with STE. Our hypothesis is that an AI analysis of the surface electrocardiogram allows a better distinction of patients with STE due to acute myocardial ischemia, from those with another etiology.

A Complete and Low-Cost Cardiac Optical Mapping System in Translational Animal Models.

Clinicians, biologists, physicists, engineers, and computer scientists are coming together to better understand heart disease, which is currently the leading cause of death globally. Optical mapping, a high-speed fluorescence imaging technique that visualizes and measures key cardiac parameters such as action potentials, cytosolic calcium transients, and fibrillation dynamics, is a core research tool that has arisen from such interdisciplinary collaborations. In an effort to broaden its use, especially among clinical scientists and students, we developed a complete and low-cost optical mapping system, including a constant-flow Langendorff perfusion system, which minimizes the economic threshold to widespread use of this powerful tool in cardiac electrophysiology research. The system described here provides high spatiotemporal resolution data about action potentials, intracellular calcium transients and fibrillation wave dynamics in isolated Langendorff-perfused hearts (pigs and rabbits), relevant for translational research. All system components and software elements are fully disclosed with the aim of increasing the use of this affordable and highly versatile tool among clinicians, basic scientists and students wishing to tackle their own research questions with their own customizable systems.

Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy.

Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.

Personalized monitoring of electrical remodelling during atrial fibrillation progression via remote transmissions from implantable devices.

AIMS: Atrial electrical remodelling (AER) is a transitional period associated with the progression and long-term maintenance of atrial fibrillation (AF). We aimed to study the progression of AER in individual patients with implantable devices and AF episodes. METHODS AND RESULTS: Observational multicentre study (51 centres) including 4618 patients with implantable cardioverter-defibrillator +/-resynchronization therapy (ICD/CRT-D) and 352 patients (2 centres) with pacemakers (median follow-up: 3.4 years). Atrial activation rate (AAR) was quantified as the frequency of the dominant peak in the signal spectrum of AF episodes with atrial bipolar electrograms. Patients with complete progression of AER, from paroxysmal AF episodes to electrically remodelled persistent AF, were used to depict patient-specific AER slopes. A total of 34 712 AF tracings from 830 patients (87 with pacemakers) were suitable for the study. Complete progression of AER was documented in 216 patients (16 with pacemakers). Patients with persistent AF after completion of AER showed ∼30% faster AAR than patients with paroxysmal AF. The slope of AAR changes during AF progression revealed patient-specific patterns that correlated with the time-to-completion of AER (R2 = 0.85). Pacemaker patients were older than patients with ICD/CRT-Ds (78.3 vs. 67.2 year olds, respectively, P < 0.001) and had a shorter median time-to-completion of AER (24.9 vs. 93.5 days, respectively, P = 0.016). Remote transmissions in patients with ICD/CRT-D devices enabled the estimation of the time-to-completion of AER using the predicted slope of AAR changes from initiation to completion of electrical remodelling (R2 = 0.45). CONCLUSION: The AF progression shows patient-specific patterns of AER, which can be estimated using available remote-monitoring technology.

Bicuspid aortic valve behaviour in elite athletes.

AIMS: To determine the prevalence and characteristics of bicuspid aortic valve (BAV) among elite athletes and to analyse the effect of long-term exercise training on their aortas. METHODS AND RESULTS: Consecutive BAV and tricuspid aortic valve (TAV) elite athletes from a population of 5136 athletes evaluated at the Sports Medicine Center of the Spanish National Sports Council were identified using echocardiography. A total of 41 BAV elite athletes were matched with 41 TAV elite athletes, and 41 BAV non-athletic patients from three Spanish tertiary hospitals. Sixteen BAV elite athletes who had undergone at least two cardiac evaluations separated by more than 3 years were selected to assess their clinical course. The prevalence of BAV in elite athletes was 0.8%. The proximal ascending aorta was larger for both BAV groups in comparison to TAV athletes (P = 0.001). No differences in aortic diameters were found between BAV athletes and BAV non-athletes. In BAV elite athletes, the annual growth rates for aortic annulus, sinuses of Valsalva, sinotubular junction, and proximal ascending aorta were 0.04 ± 0.24, 0.11 ± 0.59, 0.14 ± 0.38, and 0.21 ± 0.44 mm/year, respectively. Aortic regurgitation was the only functional abnormality, but no significant progression was found. CONCLUSION: High-intensity training and sports competition may not aggravate BAV condition during elite athletes' careers. BAV elite athletes with mild-to-moderately dilated aortas may engage in high dynamic cardiovascular exercise without adverse consequences, although an echocardiographic follow-up is recommended.

Three-dimensional cardiac fibre disorganization as a novel parameter for ventricular arrhythmia stratification after myocardial infarction.

AIMS: Myocardial infarction (MI) alters cardiac fibre organization with unknown consequences on ventricular arrhythmia. We used diffusion tensor imaging (DTI) of three-dimensional (3D) cardiac fibres and scar reconstructions to identify the main parameters associated with ventricular arrhythmia inducibility and ventricular tachycardia (VT) features after MI. METHODS AND RESULTS: Twelve pigs with established MI and three controls underwent invasive electrophysiological characterization of ventricular arrhythmia inducibility and VT features. Animal-specific 3D scar and myocardial fibre distribution were obtained from ex vivo high-resolution contrast-enhanced T1 mapping and DTI sequences. Diffusion tensor imaging-derived parameters significantly different between healthy and scarring myocardium, scar volumes, and left ventricular ejection fraction (LVEF) were included for arrhythmia risk stratification and correlation analyses with VT features. Ventricular fibrillation (VF) was the only inducible arrhythmia in 4 out of 12 infarcted pigs and all controls. Ventricular tachycardia was also inducible in the remaining eight pigs during programmed ventricular stimulation. A DTI-based 3D fibre disorganization index (FDI) showed higher disorganization within dense scar regions of VF-only inducible pigs compared with VT inducible animals (FDI: 0.36; 0.36-0.37 vs. 0.32; 0.26-0.33, respectively, P = 0.0485). Ventricular fibrillation induction required lower programmed stimulation aggressiveness in VF-only inducible pigs than VT inducible and control animals. Neither LVEF nor scar volumes differentiated between VF and VT inducible animals. Re-entrant VT circuits were localized within areas of highly disorganized fibres. Moreover, the FDI within heterogeneous scar regions was associated with the median VT cycle length per animal (R2 = 0.5320). CONCLUSION: The amount of scar-related cardiac fibre disorganization in DTI sequences is a promising approach for ventricular arrhythmia stratification after MI.

Implications of bipolar voltage mapping and magnetic resonance imaging resolution in biventricular scar characterization after myocardial infarction.

AIMS: We aimed to study the differences in biventricular scar characterization using bipolar voltage mapping compared with state-of-the-art in vivo delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging and ex vivo T1 mapping. METHODS AND RESULTS: Ten pigs with established myocardial infarction (MI) underwent in vivo scar characterization using LGE-CMR imaging and high-density voltage mapping of both ventricles using a 3.5-mm tip catheter. Ex vivo post-contrast T1 mapping provided a high-resolution reference. Voltage maps were registered onto the left and right ventricular (LV and RV) endocardium, and epicardium of CMR-based geometries to compare voltage-derived scars with surface-projected 3D scars. Voltage-derived scar tissue of the LV endocardium and the epicardium resembled surface projections of 3D in vivo and ex vivo CMR-derived scars using 1-mm of surface projection distance. The thinner wall of the RV was especially sensitive to lower resolution in vivo LGE-CMR images, in which differences between normalized low bipolar voltage areas and CMR-derived scar areas did not decrease below a median of 8.84% [interquartile range (IQR) (3.58, 12.70%)]. Overall, voltage-derived scars and surface scar projections from in vivo LGE-CMR sequences showed larger normalized scar areas than high-resolution ex vivo images [12.87% (4.59, 27.15%), 18.51% (11.25, 24.61%), and 9.30% (3.84, 19.59%), respectively], despite having used optimized surface projection distances. Importantly, 43.02% (36.54, 48.72%) of voltage-derived scar areas from the LV endocardium were classified as non-enhanced healthy myocardium using ex vivo CMR imaging. CONCLUSION: In vivo LGE-CMR sequences and high-density voltage mapping using a conventional linear catheter fail to provide accurate characterization of post-MI scar, limiting the specificity of voltage-based strategies and imaging-guided procedures.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE).

OBJECTIVE: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. METHODS: Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale - GCS - ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS=15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. RESULTS: The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. CONCLUSIONS: A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE) / Valor pronóstico precoz de un algoritmo basado en variables espectrales de la fibrilación ventricular del ECG de pacientes con muerte súbita cardiaca: estudio observacional multicéntrico (AWAKE)

Abstract Objective: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. Methods: Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale GCS --- ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS = 15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. Results: The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. Conclusions: A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.

Resumen Objetivo: La muerte súbita (MS) por fibrilación ventricular (FV) es una importante causa de morbilidad y mortalidad. Los métodos biológicos y de imagen actuales muestran limitaciones para predecir el pronóstico cerebral al ingreso hospitalario. AWAKE es un estudio observacional, multicéntrico, con el objetivo de validar un modelo basado en el análisis espectral del elec- trocardiograma (ECG), que predice precozmente el pronóstico cerebral y la supervivencia en pacientes resucitados y en estado de coma. Métodos: Se recogerán datos de los ECG con FV de pacientes reanimados de MS. Los pacientes pueden ser tanto supervivientes en estado de coma (Glasgow Coma Scale GCS ≤ 8) sometidos a control de temperatura tras la recuperación de circulación espontánea (RCE), como aquellos que recuperan la consciencia (GCS = 15) tras RCE; todos ellos ingresados en unidades de terapia intensiva cardiológica de 4 hospitales de referencia. Los registros de FV previos al primer choque se digitalizarán y analizarán para obtener datos espectrales que se incluirán en un modelo predictivo que estime el pronóstico neurológico favorable (PNF). El resultado del modelo se comparará con el pronóstico real. Resultados: El objetivo principal es el PNF durante la hospitalización. Los pacientes se categorizarán en 4 subgrupos de pronóstico neurológico según la estimación de riesgo obtenida en el modelo predictivo. Los objetivos secundarios son supervivencia al alta hospitalaria, y PNF y supervivencia a los 6 meses. El resultado de este modelo también se comparará con el pronóstico según variables clínicas. Conclusiones: Un modelo basado en el análisis espectral de registros de FV es una herramienta prometedora para obtener datos pronósticos precoces tras MS por FV.

Single coronary artery presenting as acute myocardial infarction.

A single coronary artery is one of the most rarely seen coronary artery anomalies. In addition, the specific subtype (Lipton RII-A) that our patient presented is one of the least common, and its clinical presentation as myocardial infarction and cardiac arrest has not been described in the literature. The case shows that although it is essential to exclude a malignant interarterial course of the vessel, cardiac arrest is a possible clinical presentation produced by myocardial ischemia in the context of acute myocardial infarction and should be managed according to clinical practice guidelines.

Reference Values of Aortic Root in Male and Female White Elite Athletes According to Sport.

BACKGROUND: There is limited information regarding the aortic root upper physiological limits in all planes in elite athletes according to static and dynamic cardiovascular demands and sex. METHODS AND RESULTS: A cross-sectional study was performed in 3281 healthy elite athletes (2039 men and 1242 women) aged 23.1±5.7 years, with body surface area of 1.9±0.2 m2 and 8.9±4.9 years and 19.2±9.6 hours/week of training. Maximum end-diastolic aortic root diameters were measured in the parasternal long axis by 2-dimensional echocardiography. Age, left ventricular mass, and body surface area were the main predictors of aortic dimensions. Raw values were greater in males than in females (P<0.0001) at all aortic root levels. Dimensions corrected by body surface area were higher in men than in women at the aortic annulus (13.1±1.7 versus 12.9±1.7 mm/m2; P=0.007), without significant differences at the sinus of Valsalva (16.3±1.9 versus 16.3±1.9 mm/m2; P=0.797), and were smaller in men at the sinotubular junction (13.6±1.8 versus 13.8±1.8 mm/m2; P=0.008) and the proximal ascending aorta (13.8±1.9 versus 14.1±1.9 mm/m2; P=0.001). Only 1.8% of men and 1.5% of women had values >40 mm and 34 mm, respectively. Raw and corrected aortic measures at all levels were significantly greater in sports, with a high dynamic component in both sexes, except for corrected values of the sinotubular junction in women. CONCLUSIONS: Aortic root dimensions in healthy elite athletes are within the established limits for the general population. This study describes the normal dimensions for healthy elite athletes classified according to sex and dynamic and static components of their sports.

Endoscopic Ultrasound for the Detection of Left Atrial Appendage Thrombus: A Useful Technique in Patients with Transesophageal Echocardiography Contraindication.

Endoscopic ultrasound is a diagnostic and therapeutic technique used in specialized centers for patients that have undergone digestive procedures. This technique enables highly precise real-time imaging of the digestive tract wall and surrounding organs. Endoscopic ultrasound is also useful in patients with cardiovascular diseases such as atrial fibrillation. In patients with contraindication for transesophageal echocardiography due to high risk of esophageal bleeding or complications that may require immediate intervention, endoscopic ultrasound may be a safer option for visualizing atrial chambers to rule out the presence of left atrial appendage thrombi before cardioversion.

Safety threshold of R-wave amplitudes in patients with implantable cardioverter defibrillator.

OBJECTIVE: A safety threshold for baseline rhythm R-wave amplitudes during follow-up of implantable cardioverter defibrillators (ICD) has not been established. We aimed to analyse the amplitude distribution and undersensing rate during spontaneous episodes of ventricular fibrillation (VF), and define a safety amplitude threshold for baseline R-waves. METHODS: Data were obtained from an observational multicentre registry conducted at 48 centres in Spain. Baseline R-wave amplitudes and VF events were prospectively registered by remote monitoring. Signal processing algorithms were used to compare amplitudes of baseline R-waves with VF R-waves. All undersensed R-waves after the blanking period (120 ms) were manually marked. RESULTS: We studied 2507 patients from August 2011 to September 2014, which yielded 229 VF episodes (cycle length 189.6±29.1 ms) from 83 patients that were suitable for R-wave comparisons (follow-up 2.7±2.6 years). The majority (77.6%) of VF R-waves (n=13953) showed lower amplitudes than the reference baseline R-wave. The decrease in VF amplitude was progressively attenuated among subgroups of baseline R-wave amplitude (≥17; ≥12 to <17; ≥7 to <12; ≥2.2 to <7 mV) from the highest to the lowest: median deviations -51.2% to +22.4%, respectively (p=0.027). There were no significant differences in undersensing rates of VF R-waves among subgroups. Both the normalised histogram distribution and the undersensing risk function obtained from the ≥2.2 to <7 mV subgroup enabled the prediction that baseline R-wave amplitudes ≤2.5 mV (interquartile range: 2.3-2.8 mV) may lead to ≥25% of undersensed VF R-waves. CONCLUSIONS: Baseline R-wave amplitudes ≤2.5 mV during follow-up of patients with ICDs may lead to high risk of delayed detection of VF. TRIAL REGISTRATION NUMBER: NCT01561144; results.

La ecografía endoscópica, una alternativa a la ecografía transesofágica para pacientes con varices esofágicas durante el intervencionismo estructural / Endoscopic ultrasound: an alternative to transesophageal echocardiography for patients with esophageal varices during a structural interventional procedure

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