A 76-year-old outpatient with light-chain monoclonal gammopathy of undetermined significance presented for evaluation of new-onset, nonspecific symptoms. Paraproteinemia remained stable for over 25 years without prior signs of organ manifestation. Physical examination was unremarkable. To complete routine diagnostics, a 12-lead electrocardiogram was performed, demonstrating features suggestive of amyloidosis, including low QRS voltages and an unexplained anterior pseudoinfarction pattern. It contributed to initiating further evaluation, leading to the diagnosis of light-chain cardiac amyloidosis. TAKE-HOME MESSAGE: This case highlights the potential of electrocardiography as an easily accessible tool for increasing suspicion of cardiac complications in long-standing monoclonal gammopathy of undetermined significance, even in clinically inconclusive cases.

Cardiac toxicity from QT-prolonging drugs can precipitate malignant ventricular arrhythmias in susceptible individuals, and family screening may clarify inherited risk. We report a 33-year-old woman with a history of postpartum cardiac arrest treated with a secondary-prevention implantable cardioverter-defibrillator (ICD) who developed an electrical storm after self-administration of a single low dose of amitriptyline (12.5 mg). ICD interrogation documented 176 episodes of ventricular fibrillation requiring repeated shocks, followed by complete battery depletion, hemodynamic collapse, and the need for venoarterial extracorporeal membrane oxygenation and continuous renal replacement therapy. The admission electrocardiogram showed marked QT prolongation (QTc 651 ms), with previously documented prolonged baseline QTc values. Targeted next-generation sequencing identified a novel SCN5A missense variant (NM_000335.5:c.5738G > A) and a rare pathogenic KCNQ1 splice variant (NM_000218.3:c.1032G > C), cascade testing across the family demonstrated variable expressivity among carriers. Given a suspected contribution of late sodium current, a mechanism-based strategy was implemented with mexiletine added to propranolol and overdrive pacing (90 bpm). This case underscores the risk of malignant ventricular arrhythmias after exposure to QT-prolonging agents even at low doses, and supports genotype-informed, mechanism-based therapy to mitigate arrhythmic risk in patients with marked QT prolongation.

Brugada syndrome (BrS) is a rare but potentially life-threatening condition that may lead to sudden cardiac death. Among the causes, dysfunctions of ion channels involved in the cardiac action potential (specifically in SCN5A and SCN10A genes) are particularly significant. Among diagnosed Brugada patients, fever-induced episodes occur in 20-30% of cases. Fever worsens sodium channel dysfunction, as elevated temperature further reduces their conductance. First clinical manifestation of BrS occurs usually during a febrile episode, especially in young people. We performed a multiparametric examination in addition to genetic analysis. We treated a 19-year-old man presenting with subfebrility. During the patient's subfebrile episodes, 12-lead ECG recordings revealed ST-segment elevations in leads V1-V3. Notably, the patient remained asymptomatic. Targeted genetic testing of SCN5A did not reveal any disease-causing variants as an underlying cause of the syndrome, but the temperature-inducing effect was demonstrated. The occurrence of the Brugada type 1 pattern has also been observed at subfebrile episodes, although significantly rarely. This case demonstrates that in susceptible patients, even a relatively mild elevation in body temperature can trigger ion channel dysfunctions. Timely diagnosis and follow-up are important in preserving quality of life and preventing fatal outcomes.

BackgroundThe characterization of atrial repolarization (Ta wave) remains largely elusive due to its inherently low amplitude and concealment beneath the dominant QRS complex.ObjectiveThis study aims to witness Ta wave within QRS complex using spline interpolation framework.Methodology10-s ECGs of 50 Sinus Tachycardia (SiT) and 20 Atrial Tachycardia (AT) were recorded using standard 12-lead. Lead-II signals were pre-processed for noise removal and fiducial points detection. Later, three spline models were used to synthesize hidden Ta wave using the datapoints from PR and ST segment. Further, validation analysis was performed to select the optimal spline model with the Ta wave of Atrio-Ventricular Block (AVB) ECG.ResultsIt was noted that the clamped cubic & B-spline interpolation model gave the best SSIM score of 0.7 and lowest power spectrum % difference of 1.33 of interpolated Ta wave within QRS complex. Further, Ta wave voltage and temporal features including Ta dispersion, area, peak location, Ta area/duration, duration/amplitude, and Ta2/Ta1 were crafted. Statistically significant P, Ta & P-Ta features were fed to seven Machine Learning (ML) models. The best ML models, were used to design a stacked ensemble architecture with combined P-Ta features to enhance the classification accuracy 99% and F1 score 0.99.ConclusionThe proposed method demonstrated that along with the existing P wave features, Ta wave features have potential in better classification of atrial arrhythmia, while interpolation model offers ease of implementation and adaptability to diverse clinical applications.

Background: Cardiac amyloidosis (CA) is frequently diagnosed in clinically stable patients, yet the risk of subsequent heart failure (HF) hospitalization remains difficult to predict using readily available tools. Early identification of high-risk outpatients is crucial to optimize follow-up and therapeutic strategies. Purpose: To develop a simple, non-invasive risk score to predict HF hospitalization in stable patients with cardiac amyloidosis using standard electrocardiographic and echocardiographic parameters. Methods: We prospectively enrolled 100 consecutive patients with confirmed cardiac amyloidosis from three tertiary centers. Baseline evaluation included clinical assessment, electrocardiography, and transthoracic echocardiography. The primary endpoint was HF hospitalization during follow-up; secondary endpoints were HF-related and all-cause mortality. Cox regression analysis was used to identify independent predictors of HF hospitalization and to derive a point-based risk (CAMY-HF) score. Results: During a median follow-up of 36 months, 55% of patients required HF hospitalization and 47% died. Low QRS voltage, interventricular septal thickness ≥14 mm, and left ventricular ejection fraction ≤40% independently predicted HF hospitalization and were incorporated into the CAMY-HF score (range, 0-4). HF hospitalization occurred in 0% of low-risk, 47.9% of intermediate-risk, and 80.6% of high-risk patients at 3 years. Higher CAMY-HF scores were also associated with increased HF-related and all-cause mortality. Conclusions: The CAMY-HF score is a simple, widely applicable tool for early risk stratification in clinically stable patients with cardiac amyloidosis. By relying on routine ECG and echocardiographic parameters, it may help identify outpatients at high risk of HF hospitalization and guide follow-up intensity and management strategies.