This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrialfibrillation (AF) in patients with embolic stroke of undetermined source (ESUS).
Patients had routine 12-lead electrocardiograms (ECGs) regardless of presenting complaints. Data regarding AF screening in conflict countries emergency departments (ED) is lacking.MethodsWe included consecutive patients >40 years old who reported to the ED of a Syrian tertiary centre between July 2024 and September 2024.
Single-lead electrocardiograms (1L ECG) are increasingly used for atrialfibrillation (AF) detection. Automated 1L ECG interpretation may possess prognostic value for future AF among cases where screening does not result in a short-term AF diagnosis.
In a proof-of-concept demonstration, an atrialfibrillation diagnostic algorithm achieved 91.3% Results Waveforms from 40 516 scanned and 444 photographed ECGs were automatically extracted. 12 828 of 13 258 (96.8%) scanned and 5399 of 5743 (94.0%) photographed waveforms were correctly cropped and labelled. sensitivity, 94.2%
Introduction A high recurrence rate of atrialfibrillation was monitored after catheter ablation for persistent atrialfibrillation. The primary outcome will be sinus rhythm maintenance rate over 12 months, monitored by random electrocardiogram and 24-h Holter electrocardiogram.
Although smartphone-based devices have been developed to record 1-lead ECG, existing solutions for automatic atrialfibrillation (AF) detection often has poor positive predictive value.
The ability to record an electrocardiogram (ECG) with a smartwatch (readily available without medical prescription), is a small revolution for cardiology.1 The ability to record an electrocardiogram (ECG) with a smartwatch (readily available without medical prescription), is a small revolution for cardiology.1
The P-wave on surface electrocardiogram (ECG) undergoes characteristic changes prior to developing atrialfibrillation (AF). However, the relationship between P-wave parameters and lifetime risk of AF remains poorly characterized.
Convolutional neural networks (CNNs) have been used to build atrialfibrillation (AF) prediction models based on analysis of a sinus rhythm 12-lead electrocardiogram (ECG) using large datasets. Such datasets are not readily available for all clinical scenarios or diseases.
Recurrence after atrialfibrillation (AF) ablation is frequent. Monitoring with (long-term) electrocardiograms (ECG) is constrained by limited monitoring time, measurement dispersion, and cost.
Background The echocardiographic parameters total atrial conduction time (PA-TDI duration), left atrial (LA) volume index (LAVI), and LA strain reflect adverse atrial remodeling and predict atrialfibrillation (AF).
The Apple Watch can notify users of irregular heart rhythms and potential atrialfibrillation (AF). However, the time delay between the notification and electrocardiogram (ECG) recording may cause a failure in disease diagnosis.
left atrial low-voltage areas (LVA) can significantly increase the risk of atrialfibrillation (AF) recurrence after catheter ablation. Some studies demonstrated that LVA ablation plus pulmonary veins isolation significantly improved the success rate. However, identification of LVA before the procedure is difficult.
The autonomic nervous system (ANS) is critical to atrialfibrillation (AF) pathophysiology, but it is often difficult to differentiate vagal and adrenergic AF due to complex physiological interactions.1 2 We previously reported that ERPs were associated with increased susceptibility to AF.3
Photoplethysmography (PPG) based smartphone applications to detect atrialfibrillation (AF) have gained prominence. While the diagnosis of AF requires an electrocardiogram (ECG), PPG might be used to monitor AF episodes in patients with an established diagnosis of AF. However, studies in this setting are lacking.
Introduction: The application of artificial intelligence (AI) algorithms to 12-lead electrocardiogram (ECG) provides promising age prediction models. We explored whether the gap between the pre-procedural AI-ECG age and chronological age can predict atrialfibrillation (AF) recurrence after catheter ablation (CA).
Atrialfibrillation (AF) is frequently under-detected but linked to cardiovascular comorbidities, including stroke. Preexisting screening modalities are known to have low performance.
Symptom-driven electrocardiogram (ECG) recording plays a significant role in the detection of post-ablation atrialfibrillation recurrence (AFR). However, making timely medical contact whenever symptoms occur may not be practical.
A gradual increase in arrhythmia recurrences during 12 months after catheter ablation (CA) of atrialfibrillation (AF) is still reported.1 A gradual increase in arrhythmia recurrences during 12 months after catheter ablation (CA) of atrialfibrillation (AF) is still reported.1
Here is the computer interpretation: ATRIALFIBRILLATION WITH RAPID VENTRICULAR RESPONSE WITH ABERRANT CONDUCTION OR VENTRICULAR PREMATURE COMPLEXES LEFT AXIS DEVIATION [QRS AXIS beyone -30] NONSPECIFIC ST and T-WAVE ABNORMALITY The over-reading physician confirmed this diagnosis, which is incorrect. It is not atrialfibrillation.
Artificial intelligence (AI)-enabled electrocardiography (ECG) scores can predict atrialfibrillation (AF) and grade atrial cardiomyopathy. Advanced stages present with left atrial fibrosis that can be identified by low-voltage areas (LVAs).
BACKGROUND:It is difficult to identify patients with atrialfibrillation (AF) most likely to respond to ablation. Circulation: Arrhythmia and Electrophysiology, Ahead of Print.
Persistent cardiac arrhythmias are readily amenable to detection by performing a standard electrocardiogram (ECG), but detection of transient (paroxysmal) arrhythmias has long been a significant cause of frustration to both doctors and patients.
Abstract Introduction Despite advanced ablation strategies and major technological improvements, treatment of persistent atrialfibrillation (AF) remains challenging and the underlying pathophysiology is not fully understood. ms after) and AF termination to atrial tachycardia (AT) or sinus rhythm (SR) in 12 patients (24%).
Atrial High-Rate Events (AHREs) are common in patients with cardiac implantable electronic devices (CIED). They are classed as AtrialFibrillation (AF) when confirmed by electrocardiogram. Their associated temporal risk of heart failure (HF) hospitalisation has not been explored.
Introduction:Patients diagnosed with ischemic stroke routinely undergo prolonged cardiac telemetry (PCT) to evaluate for occult atrialfibrillation (AF), but this approach is limited by high cost and low yield. Stroke, Volume 55, Issue Suppl_1 , Page AWP287-AWP287, February 1, 2024.
An admission electrocardiogram (ECG) revealed atrialfibrillation with a wide QRS complex and noticeable splitting (Figure 1A, red arrows). A 56-year-old man with heart failure on oral treatment presented with breathlessness. Chronological ECG changes over the past 20 years are shown in Figure 1B.
In a case report published in 1984 in the New England Journal of Medicine, Figure 1 was an electrocardiogram that showed sinus bradycardia with a short PR interval and prominent delta waves, with a pattern of preexcitation typical of a posteroseptal accessory pathway (PSAP).1
This prognostic study investigates whether deep learning models applied to electrocardiograms (ECGs) of sinus rhythm in a population of US Veterans Affairs (VA) patients can predict the presence of concurrent atrialfibrillation (AF).
However, widely split P' waves in focal atrial tachycardia (AT) on a surface electrocardiogram (ECG) have rarely been reported. Case summary A 67-year-old patient, who had undergone two radiofrequency ablations for atrialfibrillation, presented with recurrent palpitation.
In a world where technology reigns supreme, one of the most profound tools in medicine remains the irreplaceable electrocardiogram (ECG). AFIB/AFL – atrialfibrillation or atrial flutter episodes. An abnormal electrocardiogram can mean many things.
Introduction:Personal electrocardiogram (ECG) devices have significant potential for monitoring abnormal heart rhythms outside clinical environments. Many consumer-grade devices, such as the Apple Watch ECG (AW-ECG), frequently classify atrial and ventricular ectopy as ‘inconclusive’.Hypothesis/Objective:To
This measurement has been correlated with those made at electrophysiology study and may predict the potential risk of rapid anterograde conduction if the person develops atrialfibrillation. QT prolongation and the occurrence of ventricular arrhythmias with exercise are another important aspect of exercise testing in children.
The rhythm is irregularly irregular, therefore it is atrialfibrillation 2. The complexes are wide (so one might think of atrialfibrillation with aberrancy, in which case you should see RBBB or LBBB pattern, which is not there) 3. Here is the initial ED ECG: What is the diagnosis (this is pathognomonic)?
Apple has made available in Australia its electrocardiogram app for Series 4, 5 and 6 of its Apple Watch. An irregular rhythm notification feature that checks atrialfibrillation was also included in the Apple Watch Series 3 and later versions.
The rhythm is nearly regular, but there are no P-waves (it is too regular to be atrialfibrillation). Updates on the Electrocardiogram in Acute Coronary Syndromes. Electrocardiogram patterns in acute left main coronary artery occlusion. at the time of the ECG. Mg was 1.6. However, the QRS is barely wide, if at all.
Case submitted and written by Mazen El-Baba MD, with edits from Jesse McLaren and edits/comments by Smith and Grauer A 90-year old with a past medical history of atrialfibrillation, type-2 diabetes, hypertension, dyslipidemia, presented with acute onset chest/epigastric pain, nausea, and vomiting. Harhash AA, Huang JJ, Reddy S, et al.
What is the atrial activity? Or is it atrialfibrillation with complete AV block and junctional escape? A 12-lead electrocardiogram, lead V4R , and leads V7-9 were recorded on admission. He appeared gray in color, with cool skin. Here is his ED ECG: There is bradycardia with a junctional escape.
An international consensus statement on how to treat atrialfibrillation with catheter or surgical ablation has been published in EP Europace, a journal of the European Society of Cardiology (ESC), and was recently presented at EHRA 2024, a scientific congress held April 7-9 in Berlin, Germany.
milla1cf Wed, 12/13/2023 - 10:24 December 13, 2023 — A new artificial intelligence (AI) model designed by Scripps Research scientists could help clinicians better screen patients for atrialfibrillation (or AFib)—an irregular, fast heartbeat that is associated with stroke and heart failure.
We organize all of the trending information in your field so you don't have to. Join thousands of users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content