An electrocardiogram of an uncommon congenital heart disease is presented to highlight the unique findings in diagnosis with its clinical implications and predictive value.
An electrocardiogram of an uncommon congenital heart disease is presented to highlight the unique findings in diagnosis with its clinical implications and predictive value.
We present a case of advanced interatrial block induced by flecainide toxicity. We discuss the implications of this conduction abnormality.
The Dressler-de Winter sign is an electrocardiogram (ECG) pattern characterized by upsloping ST-segment depression in leads V1-V6 followed by tall, hyperacute T waves, typically indicating an occlusion of the left anterior descending artery (LAD). We present a case involving an inferoposterior ST-segment elevation myocardial infarction (STEMI) with a variant of the de Winter sign, a concept of ST-segment continuum in the precordial leads. Despite initial ECG findings suggesting right coronary artery (RCA) or left circumflex artery (LCX) involvement, coronary angiography confirmed occlusion of the wrap-around LAD distal to the first septal (S1) and diagonal branch (D1) and revealed a left dominant system accompanied by a small non-dominant RCA. This case highlights the diagnostic complexity in accurately localizing the culprit artery in STEMI cases exhibiting the de Winter sign. Understanding such ECG variants is crucial for analyzing the mechanisms of acute ischemia and ensuring accurate assessment of the culprit vessel for effective revascularization.
Acute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction is a major cause of morbidity and mortality throughout Europe. Diagnosis in the acute setting is mainly based on clinical symptoms and physician's interpretation of an electrocardiogram (ECG), which may be subject to errors. ST-segment elevation is the leading criteria to activate urgent reperfusion therapy, but a clear ST-elevation pattern might not be present in patients with coronary occlusion and ST-segment elevation might be seen in patients with normal coronary arteries.
The ASSIST project is a retrospective observational study aiming to improve the ECG-assisted assessment of ACS patients in the acute setting by incorporating an artificial intelligence platform, Willem™ to analyze 12‑lead ECGs. Our aim is to improve diagnostic accuracy and reduce treatment delays. ECG and clinical data collected during this study will enable the optimization and validation of Willem™. A retrospective multicenter study will collect ECG, clinical, and coronary angiography data from 10,309 patients. The primary outcome is the performance of this tool in the correct identification of acute myocardial infarction with coronary artery occlusion. Model performance will be evaluated internally with patients recruited in this retrospective study while external validation will be performed in a second stage.
ASSIST will provide key data to optimize Willem™ platform to detect myocardial infarction based on ECG-assessment alone. Our hypothesis is that such a diagnostic approach may reduce time delays, enhance diagnostic accuracy, and improve clinical outcomes.
Currently, the interrupted recording technique is commonly used to perform left bundle branch (LBB) pacing (LBBP). However, this method requires repeated testing to confirm that the LBB is captured and perforations are avoided. An automated solution may make this repetitive work easier.
LBBP was performed using an uninterrupted recording technique in an 86-year-old woman. Lead position and LBB capture was confirmed by the characteristics of the intrinsic filtered and unfiltered intracardiac electrograms.
Continuous mapping and recording technique may help achieve more accurate positioning of LBBP lead in the ventricular septum.
Atrial fibrosis has a significant impact on the success rate of catheter ablation (CA) treatment of atrial fibrillation (AF). The fibrotic tissues could be reflected by the amplitude of the fibrillatory wave (F-wave).
704 patients with persistent AF and at least 1-year follow-up after CA were included as the internal group. 101 patients from another hospital were used as the external validation cohort. A 12‑lead ECG was performed before CA and the maximum FWA in three ECG leads (aVL, aVF, V1) were measured. The FWA score (0 to 6 points according to the amplitude range of the three leads) of each patients was calculated. Five models including clinical features, FWA score, CHA2DS2-VASc score, APPLE score and the fusion of clinical features and FWA score were built. The FWA score was superior to the model constructed by clinical variables, CHA2DS2-VASc score and APPLE score. It not only had good predictive performance for AF recurrence, with an AUC value of 0.812 (95% CI 0.724–0.900), but also showed a significant predictive value for the recurrence rate according to F-wave amplitude. In the external validation cohort, the FWA score showed similar results (AUC 0.768, 95% CI 0.672–0.865).
The present study reveals the significant predictive value of the FWA score for persistent AF ablation recurrence.
As ECG technology rapidly evolves to improve patient care, accurate ECG interpretation will continue to be foundational for maintaining high clinical standards. Recent studies have exposed significant educational gaps, with many healthcare professionals lacking sufficient training and proficiency. Furthermore, integrating new software and hardware ECG technologies poses challenges about potential knowledge and skill erosion. This underscores the need for clinicians who are adept at integrating clinical expertise with technological proficiency. It also highlights the need for innovative solutions to enhance ECG interpretation among healthcare professionals in this rapidly evolving environment. This work explores the importance of aligning ECG education with technological advancements and proposes how this synergy could advance patient care in the future.
Brugada syndrome (BrS) is a rare autosomal dominant inherited channel disorder characterized by a specific electrocardiographic pattern of right precordial ST-segment elevation. Clinically, patients may experience polymorphic ventricular tachycardia and ventricular fibrillation, leading to recurrent syncope and sudden cardiac death (SCD) in the absence of structural cardiomyopathy. The A-kinase anchor protein 9 (AKAP9) gene, located on chromosome 7, encodes the AKAP9 protein, which plays a crucial role in regulating the phosphorylation of slowly activating delayed rectifier potassium channels (IKs). Here, we present a rare case of BrS associated with an insertion mutation in AKAP9, resulting in a frameshift mutation.
Heart disease and strokes are leading global killers. While atrial arrhythmias are not deadly by themselves, they can disrupt blood flow in the heart, causing blood clots. These clots can travel to the brain, causing strokes, or to the coronary arteries, causing heart attacks. Additionally, prolonged periods of elevated heart rates can lead to structural and functional changes in the heart, ultimately leading to heart failure if untreated. The left atrium, with its more complex topology, is the primary site for complex arrhythmias. Much remains unknown about the causes of these arrhythmias, and computer modeling is employed to study them.
We use N-body modeling techniques and parallel computing to build an interactive model of the left atrium. Through user input, individual muscle attributes can be adjusted, and ectopic events can be placed to induce arrhythmias in the model. Users can test ablation scenarios to determine the most effective way to eliminate these arrhythmias.
We set up muscle conditions that either spontaneously generate common arrhythmias or, with a properly timed and located ectopic event, induce an arrhythmia. These arrhythmias were successfully eliminated with simulated ablation.
We believe the model could be useful to doctors, researchers, and medical students studying left atrial arrhythmias.
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