Metabolic disorders, including obesity, type 2 diabetes, metabolic dysfunction-associated fatty liver disease (MAFLD), anemia, and insulin resistance, are increasingly prevalent and represent a major contributor to cardiovascular morbidity and mortality. Emerging evidence indicates that these conditions are associated with prolongation of the corrected QT (QTc) interval, a well-established marker of ventricular arrhythmias and sudden cardiac death. Individuals with metabolic disorders have a significantly higher risk of life-threatening arrhythmias, even in the absence of known cardiovascular disease. Insulin resistance, a central component of cardiometabolic dysfunction, has also been linked to QT interval prolongation. Despite this growing body of evidence, QTc monitoring is not currently included in routine clinical guidelines for the management of metabolic disorders. Electrocardiography (ECG) is a low-cost and widely accessible diagnostic tool that enables early identification of high-risk individuals and supports timely preventive interventions. Routine implementation of baseline and annual ECG-based QTc monitoring has the potential to reduce sudden cardiac death, improve cardiovascular risk stratification, and decrease healthcare costs associated with acute cardiac events. This policy brief advocates for the adoption of a national QTc monitoring strategy as a scalable and cost-effective approach to improving cardiovascular outcomes in patients with metabolic disorders.

Short QT Syndrome type 3 (SQTS3) is an inherited disorder marked by an abnormally short QT interval on ECG and a high risk of life-threatening arrhythmias, for which effective targeted therapies are lacking. SQTS3 is caused by Kir2.1 mutations that enhance the outward component of the strong inward rectifier potassium current (IK1), disrupting its normal voltage-dependent regulation and severely abbreviating the cardiac action potential. Using a mouse model of SQTS3 carrying the Kir2.1M301K mutation, we examine whether administration of polyamines, the fundamental blockers of Kir2.1 channels, could restore the normal QT interval and prevent arrhythmia. Male mutant mice display reduced IK1 rectification, reduced sodium channel function, QT interval shortening, and a high susceptibility to induced ventricular tachycardia. Here, we show that systemic polyamine administration restores strong IK1 rectification, rescues sodium current density, prolongs action potential duration and QT interval, and significantly reduces arrhythmia inducibility, identifying a potential therapeutic approach for SQTS, a life-threatening disease.

Vitamin A is an essential micronutrient involved in growth, immune regulation, and central nervous system function; however, excessive intake may disrupt systemic homeostasis. This study investigated the electrophysiological effects of experimental hypervitaminosis A on hippocampal activity and cardiac function in male Wistar rats. Animals received a supraphysiological dose of vitamin A (50,000 IU/kg, intraperitoneally) once daily for 3, 7, or 14 days. Serum calcium levels were quantified, and electrophysiological recordings were obtained from the CA1 hippocampal region (EEG) and through electrocardiography (ECG). Vitamin A administration produced a time-dependent increase in total hippocampal spectral power. Power elevations were observed across multiple frequency bands, particularly theta (4-8 Hz), α (8-12 Hz), β (12-28 Hz), and γ (28-40 Hz) oscillations after 7 and 14 days of exposure. Serum calcium levels showed modest increases but remained within physiological reference ranges. Cardiac assessment revealed increased heart rate accompanied by reductions in R-R and QT intervals while maintaining sinus rhythm and preserved ECG morphology. These findings demonstrate that short-term exposure to supraphysiological vitamin A levels alters hippocampal oscillatory dynamics and modulates cardiac electrophysiological parameters in rats. Although the functional and mechanistic implications require further investigation, the results indicate that excessive vitamin A intake can influence neurocardiac electrophysiological homeostasis even in the absence of overt hypercalcemia.

Calcium plays a fundamental role in cardiac electrophysiology and myocardial, contraction, and disturbances in calcium homeostasis may lead to significant electrical, and mechanical cardiac dysfunction. We report two clinically opposite but pathophysiologically related cases of calcium imbalance. The first case describes severe hypocalcemia presenting with long QT interval and acute heart failure due to hypocalcemic cardiomyopathy, with complete recovery of ventricular function after calcium correction. The second case describes a young patient with severe hypercalcemia due to primary hyperparathyroidism who presented with syncope, a type 1 Brugada electrocardiographic pattern, and short QT interval. After normalization of calcium levels, the electrocardiographic abnormalities initially resolved; however, recurrent syncope and a type 2 Brugada pattern were later observed under normocalcemia. Pharmacological provocation with ajmaline unmasked a type 1 Brugada pattern, confirming Brugada syndrome. These cases illustrate that calcium disorders may cause significant electrocardiographic changes, reversible myocardial dysfunction, and may unmask latent channelopathies. Recognition of electrolyte abnormalities is essential, as these conditions may be reversible but potentially lifethreatening.

Although structural heart abnormalities are not typically associated with short QT syndrome (SQTS)-related sudden unexpected death, few autopsy studies have examined the underlying pathology and genetic factors of SQTS. Therefore, comprehensive pathologic examinations and whole-exome sequencing were conducted in four men (aged 24, 28, 31, and 45 years) with sudden unexpected death and a short QT interval (sQT). No variants were identified in genes currently known to be associated with SQTS. An enrichment analysis was performed to identify potential genetic causes and mechanisms. None of the men had a history of cardiovascular disease, familial sudden death, or arrhythmia. Rare variants in SCN10A, ANK2, KCNQ2, and CACNA1H were detected, potentially associated with cardiac electrophysiology. One case exhibited apical hypertrophic cardiomyopathy with a rare PLEC variant. The other three displayed left ventricular hypertrabeculation with poor compaction, deep recess formation, myocardial fibrosis, micronecrosis, and minimal inflammatory cell infiltration. The enrichment analysis indicated that these variants were associated with cardiac electrophysiology and morphogenesis. These results showed that individuals with sQT may be at risk of sudden death even without a clinical or family history. This risk may be increased by cardiomyopathy-related gene variants in preclinical or early disease stages. Electrocardiographic evaluation to identify sQT cases followed by morphologic and genetic evaluations improves the assessment of a sudden death risk in individuals with sQT.

Background and Objectives: The interaction between the brain and heart has become more interesting in the last 20 years. The most common cardiac complications after stroke are myocardial infarction, heart failure, arrhythmias, electrocardiographic disturbances, repolarization disorders, and sudden cardiac death. The prolonged Tpeak-Tend interval is an indicator of the electrical heterogeneity of the myocardium (abnormal repolarization) that causes malignant arrhythmias. We aimed to investigate whether the Tpeak-Tend interval, which reflects the heterogeneity of repolarization, is prolonged in stroke and its relationship with short-term mortality. Materials and Methods: Individuals over the age of 18 who presented with hemorrhagic or ischemic stroke were included in the study. Demographic characteristics, laboratory and imaging findings of the patients were recorded. ECGs were obtained at the time of admission to the hospital and 24 h later. Patients were followed for in-hospital mortality. Results: 89 (82.4%) of the patients had ischemic stroke, 19 (17.6%) had hemorrhagic stroke. It was determined that Tp-eV2 and Tp-eV5 at hospital admission were significantly longer than the 24th hour values. A total of 92.01 (16.3) ms at Tp-eV2 admission, 84.1 (16.3) ms after 24 h (p = 0.003), 91.9 (7.3) msTp-eV5 at admission, and 81.6 (17.8) ms (p = 0.000) after 24 h. In multivariate logistic regression analysis of in-hospital mortality, Tp-eV2 (HR: 0.96 (95% CI 0.93-0.99) p = 0.008) was determined as an independent predictor among cardiovascular parameters. Conclusions: Tp-e intervals were prolonged in both leads V2 and V5 in patients with stroke. Prolongation of lead V2 in the Tp-e interval is an independent indicator of short-term mortality among cardiovascular parameters.

Electrocardiography (ECG) plays a vital role in the diagnosis of cardiovascular diseases by analyzing the electrical activity of the heart. ECG semantic segmentation is a subfield focused on sample-wise delineation of ECG waveforms by assigning a physiological label to each time sample, enabling explicit estimation of clinically meaningful onset and offset boundaries. Recent advancements in deep learning have significantly improved ECG classification accuracy; however, the same has not yet been observed in automatic ECG segmentation. Existing models often lack explainability and adaptability to patient-specific variations, thereby reducing their generalizability. This study proposes a personalized deep neural network approach for enhanced ECG processing. This method incorporates convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks, incorporating an attention mechanism to refine segmentation accuracy. A novel loss function is introduced to ensure smoother temporal transitions and better classification accuracy. The model was evaluated using the QT Database, demonstrating substantial improvements in P-wave and QRS delineation and in T-wave offset localization segmentation when fine-tuned for individual patients when fine-tuned and evaluated on held-out data from the same patient, demonstrating the benefit of intra-patient adaptation. Our results indicate that personalization improves delineation accuracy for challenging waveforms (notably P and T waves), supporting the potential of deep learning to better capture patient-specific morphology and providing a stronger basis for waveform-level, clinically interpretable ECG analysis.

Long QT Syndrome (LQTS) is an inherited cardiac disorder characterized by dysfunctional cardiac ion channels, which result in prolonged QT intervals on electrocardiograms (ECGs). LQTS can lead to severe clinical manifestations, including syncope, ventricular arrhythmias, and sudden cardiac death. Effective genotype-specific management strategies are essential to mitigate the risk of life-threatening arrhythmias. This study aims to achieve automatic discrimination among the LQT1, LQT2, and LQT3 genotypes to enable targeted treatment and prevention strategies. Utilizing ECG data from the Telemetric and Holter ECG Warehouse's LQTS database, our methodology involves an automated extraction process of short ECG signals, geometric parameterization techniques, and classification using a two-stage cascade of binary support vector machine classifiers. The input features for the classifiers are derived from Lead I ECG signals sampled at 200 Hz, highlighting the potential application in developing single-lead ECG monitoring devices and applications, such as widely used smartwatches, for which short recording duration, low sampling frequency, and arm-to-arm lead measurements are fundamental prerequisites for practical use. The proposed classifier achieved 71% weighted accuracy on out-of-sample data (LQT1: 65% recall, 58% precision; LQT2: 79% recall, 82% precision; and LQT3: 71% recall, 77% precision). Our findings demonstrate the feasibility of noninvasive genotype differentiation for LQTS based on the morphological analysis of ECG signals, providing an advancement in the field of personalized cardiology and the development of portable diagnostic tools.

Background and Objectives: This study aimed to evaluate the pre- and post-treatment changes in ICEB and ICEBc score markers of cardiac electrical balance in patients presenting to the emergency department with hypertensive urgency and to investigate their relationship with short-term clinical outcomes. Materials and Methods: In this retrospective study, 50 patients who presented to a tertiary university hospital emergency department between 1 January 2021 and 31 December 2024 with a diagnosis of hypertensive urgency and had pre- and post-treatment 12-lead ECGs were analysed. ICEB (QT/QRS) and ICEBc (QTc/QRS) scores were calculated manually. Patients were categorized as discharged or hospitalized. Within-group and between-group comparisons of the scores were performed. Results: Of the patients, 66% were female, and the mean age was 60.4 ± 14.5 years. A statistically significant increase in ICEB scores was observed after treatment in discharged patients (p = 0.006), whereas ICEBc scores showed no significant change. In the hospitalized group, no significant difference was found in either ICEB or ICEBc scores. Additionally, between-group comparisons revealed no significant differences in ICEBc values. Conclusions: The ICEB score may serve as a dynamic marker reflecting the electrophysiological response to antihypertensive treatment. The observed increase in ICEB after treatment may indicate the restoration of electrical stability. In contrast, ICEBc appeared to have limited predictive value in this clinical context. Further prospective studies with larger populations are needed to determine the clinical utility of ICEB in the management of hypertensive crises.