Automated differentiation of wide QRS complex tachycardia using QRS complex polarity.

Background: Wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) remains challenging despite numerous 12-lead electrocardiogram (ECG) criteria and algorithms. Automated solutions leveraging computerized ECG interpretation (CEI) measurements and engineered features offer practical ways to improve diagnostic accuracy. We propose automated algorithms based on (i) WCT QRS polarity direction (WCT Polarity Code [WCT-PC]) and (ii) QRS polarity shifts between WCT and baseline ECGs (QRS Polarity Shift [QRS-PS]).

Bridging ECG learning with emerging technologies: Advancing clinical excellence.

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.

Direct Comparison of Methods to Differentiate Wide Complex Tachycardias: Novel Automated Algorithms Versus Manual ECG Interpretation Approaches.

Background: Differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide tachycardia via 12-lead ECG interpretation is a crucial but difficult task. Automated algorithms show promise as alternatives to manual ECG interpretation, but direct comparison of their diagnostic performance has not been undertaken.

Methods: Two electrophysiologists applied 3 manual WCT differentiation approaches (ie, Brugada, Vereckei aVR, and VT score).

A large-scale CRISPR screen reveals context-specific genetic regulation of retinal ganglion cell regeneration.

Many genes are known to regulate retinal regeneration after widespread tissue damage. Conversely, genes controlling regeneration after limited cell loss, as per degenerative diseases, are undefined. As stem/progenitor cell responses scale to injury levels, understanding how the extent and specificity of cell loss impact regenerative processes is important.

A novel way to prospectively evaluate of AI-enhanced ECG algorithms.

Significant strides will be made in the field of computerized electrocardiology through the development of artificial intelligence (AI)-enhanced ECG (AI-ECG) algorithms. Yet, the scientific discourse has primarily relied upon on retrospective analyses for deriving and externally validating AI-ECG classification algorithms, an approach that fails to fully judge their real-world effectiveness or reveal potential unintended consequences. Prospective trials and analyses of AI-ECG algorithms will be crucial for assessing real-world diagnostic scenarios and understanding their practical utility and degree influence they confer onto clinicians.

Molecular regulation of retinal regeneration is context specific.

Unlabelled: Many genes are known to regulate retinal regeneration following widespread tissue damage. Conversely, genes controlling regeneration following limited retinal cell loss, akin to disease conditions, are undefined. Combining a novel retinal ganglion cell (RGC) ablation-based glaucoma model, single cell omics, and rapid CRISPR/Cas9-based knockout methods to screen 100 genes, we identified 18 effectors of RGC regeneration kinetics.

Mayo Clinic VT calculator: A practical tool for accurate wide complex tachycardia differentiation.

The discrimination of ventricular tachycardia (VT) versus supraventricular wide complex tachycardia (SWCT) via 12-lead electrocardiogram (ECG) is crucial for achieving appropriate, high-quality, and cost-effective care in patients presenting with wide QRS complex tachycardia (WCT). Decades of rigorous research have brought forth an expanding arsenal of applicable manual algorithm methods for differentiating WCTs. However, these algorithms are limited by their heavy reliance on the ECG interpreter for their proper execution.

Predictors of ECG Interpretation Proficiency in Healthcare Professionals.

Accurate ECG interpretation is vital, but variations in skills exist among healthcare professionals. This study aims to identify factors contributing to ECG interpretation proficiency. Survey data and ECG interpretation test scores from participants in the EDUCATE Trial were analyzed to identify predictors of performance for 30 sequential 12-lead ECGs.

The emergence and destiny of automated methods to differentiate wide QRS complex tachycardias.

Accurate differentiation of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular wide complex tachycardia (SWCT) using non-invasive methods such as 12‑lead electrocardiogram (ECG) interpretation is crucial in clinical practice. Recent studies have demonstrated the potential for automated approaches utilizing computerized ECG interpretation software to achieve accurate WCT differentiation. In this review, we provide a comprehensive analysis of contemporary automated methods for VT and SWCT differentiation.

Impact of Computer-Interpreted ECGs on the Accuracy of Healthcare Professionals.

The interpretation of electrocardiograms (ECGs) involves a dynamic interplay between computerized ECG interpretation (CEI) software and human overread. However, the impact of computer ECG interpretation on the performance of healthcare professionals remains largely unexplored. The aim of this study was to evaluate the interpretation proficiency of various medical professional groups, with and without access to the CEI report.

Education curriculum assessment for teaching electrocardiography: Rationale and design for the prospective, international, randomized controlled EDUCATE trial.

Background: Electrocardiogram (ECG) interpretation training is a fundamental component of medical education across disciplines. However, the skill of interpreting ECGs is not universal among medical graduates, and numerous barriers and challenges exist in medical training and clinical practice. An evidence-based and widely accessible learning solution is needed.

ECG Interpretation Proficiency of Healthcare Professionals.

ECG interpretation is essential in modern medicine, yet achieving and maintaining competency can be challenging for healthcare professionals. Quantifying proficiency gaps can inform educational interventions for addressing these challenges. Medical professionals from diverse disciplines and training levels interpreted 30 12-lead ECGs with common urgent and nonurgent findings.

Variation in the Use of Targeted Temperature Management for Cardiac Arrest.

Targeted temperature management (TTM) is recommended for patients who do not respond after return of spontaneous circulation after cardiac arrest. However, the degree to which patients with cardiac arrest have access to this therapy on a national level is not known. Understanding hospital- and patient-level factors associated with receipt of TTM could inform interventions to improve access to this treatment among appropriate patients.

Exploring Factors Influencing ECG Interpretation Proficiency of Medical Professionals.

The electrocardiogram (ECG) is a crucial diagnostic tool in medicine with concerns about its interpretation proficiency across various medical disciplines. Our study aimed to explore potential causes of these issues and identify areas requiring improvement. A survey was conducted among medical professionals to understand their experiences with ECG interpretation and education.

Multidisciplinary Critical Care Management of Electrical Storm: JACC State-of-the-Art Review.

Electrical storm (ES) reflects life-threatening cardiac electrical instability with 3 or more ventricular arrhythmia episodes within 24 hours. Identification of underlying arrhythmogenic cardiac substrate and reversible triggers is essential, as is interrogation and programming of an implantable cardioverter-defibrillator, if present. Medical management includes antiarrhythmic drugs, beta-adrenergic blockade, sedation, and hemodynamic support.

Comparison of two artificial intelligence-augmented ECG approaches: Machine learning and deep learning.

Background: Artificial intelligence-augmented ECG (AI-ECG) refers to the application of novel AI solutions for complex ECG interpretation tasks. A broad variety of AI-ECG approaches exist, each having differing advantages and limitations relating to their creation and application.

Purpose: To provide illustrative comparison of two general AI-ECG modeling approaches: machine learning (ML) and deep learning (DL).

Computerized electrocardiogram data transformation enables effective algorithmic differentiation of wide QRS complex tachycardias.

Background: Accurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs.

Objective: Develop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG.

Methods: We developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data.

Wide complex tachycardia discrimination tool improves physicians' diagnostic accuracy.

Background: Timely and accurate discrimination of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular WCT (SWCT) is critically important. Previously we developed and validated an automated VT Prediction Model that provides a VT probability estimate using the paired WCT and baseline 12-lead ECGs. Whether this model improves physicians' diagnostic accuracy has not been evaluated.

Key Concepts Surrounding Cardiogenic Shock.

Cardiogenic shock (CS) is the final common pathway of impaired cardiovascular performance that results in ineffective forward cardiac output producing clinical and biochemical signs of organ hypoperfusion. CS represents the most common cause of shock in the cardiac intensive care unit (CICU) and accounts for a substantial proportion of CICU patient deaths. Despite significant advances in revascularization techniques, pharmacologic therapeutics and mechanical support devices, CS remains associated with a high mortality rate.

Automatic wide complex tachycardia differentiation using mathematically synthesized vectorcardiogram signals.

Background: Automated wide complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) may be accomplished using novel calculations that quantify the extent of mean electrical vector changes between the WCT and baseline electrocardiogram (ECG). At present, it is unknown whether quantifying mean electrical vector changes within three orthogonal vectorcardiogram (VCG) leads (X, Y, and Z leads) can improve automated VT and SWCT classification.

Methods: A derivation cohort of paired WCT and baseline ECGs was used to derive five logistic regression models: (i) one novel WCT differentiation model (i.

Gluteal Muscle Activation During Common Yoga Poses.

Background: Approximately 24% of physical therapists report regularly using yoga to strengthen major muscle groups. Although clinicians and athletes often use yoga as a form of strength training, little is known about the activation of specific muscle groups during yoga poses, including the gluteus maximus and medius.

Hypothesis/purpose: The purpose of this study was to measure gluteus maximimus and gluteus medius activation via electromyography (EMG) during five common yoga poses.