Motor vehicle crash risk after cardioverter-defibrillator implantation: a population-based cohort study.

BACKGROUND: Limited empirical evidence informs driving restrictions after implantable cardioverter-defibrillator (ICD) implantation. We sought to evaluate real-world motor vehicle crash risks after ICD implantation. METHODS: We performed a retrospective cohort study using 22 years of population-based health and driving data from British Columbia, Canada (2019 population: 5 million). Individuals with a first ICD implantation between 1997 and 2019 were age and sex matched to three controls. The primary outcome was involvement as a driver in a crash that was attended by police or that resulted in an insurance claim. We used survival analysis to compare crash risk in the first 6 months after ICD implantation to crash risk during a corresponding 6-month interval among controls. RESULTS: A crash occurred prior to a censoring event for 296 of 9373 individuals with ICDs and for 1077 of 28 119 controls, suggesting ICD implantation was associated with a reduced risk of subsequent crash (crude incidence rate, 8.5 vs 10.5 crashes per 100 person-years; adjusted HR (aHR), 0.71; 95% CI 0.61 to 0.83; p<0.001). Results were similar after stratification by primary versus secondary prevention ICD. Relative to controls, ICD patients had more traffic contraventions in the 3 years prior to ICD implantation but fewer contraventions in the 6 months after implantation, suggesting individuals reduced their road exposure (hours or miles driven per week) or drove more conservatively after ICD implantation. CONCLUSIONS: Crash risk is lower in the 6 months after ICD implantation than among matched controls, likely because individuals reduced their road exposure in order to comply with contemporary postimplantation driving restrictions. Policymakers might consider liberalisation of postimplantation driving restrictions while monitoring crash rates.

The Diagnostic Utility of Holter Monitoring in Catecholaminergic Polymorphic Ventricular Tachycardia.

BACKGROUND: Holter monitoring may raise suspicion of an underlying catecholaminergic polymorphic ventricular tachycardia (CPVT) diagnosis. Although not a primary investigation for CPVT, Holter monitoring is ubiquitously used as a diagnostic tool in the heart rhythm clinic. OBJECTIVES: The objective of this study was to explore Holter monitoring in CPVT diagnosis. METHODS: This retrospective cohort study analyzed off-therapy Holter monitoring from 13 ryanodine receptor 2-positive CPVT and 34 healthy patients from the Canadian Hearts in Rhythm Organization national registry. Using the Edwards method, the ratio of ambient-maximum heart rate during Holter monitoring was correlated with exertion level to separate premature ventricular contractions (PVCs) during periods of adrenergic and nonadrenergic stress. A receiver operating characteristic curve analysis determined the optimal threshold for isolating CPVT-induced PVCs during adrenergic states. RESULTS: PVC burden differed between groups (P = 0.001) but was within population norm, suggesting ambient PVCs are uncommon in CPVT. CPVT patients had higher PVC counts than healthy controls (P = 0.002), with a different distribution based on adrenergic state. The optimal threshold for separating PVCs into periods of adrenergic and nonadrenergic stress in CPVT patients was 76% of the maximum heart rate during the monitoring period. Compared with healthy controls, CPVT patients had a higher PVC count, limited to periods of adrenergic stress, defined by >76% maximum heart rate threshold (P = 0.002; area under the receiver operating characteristic curve: 0.84). Below this threshold, there was no significant PVC difference (P = 0.604). CONCLUSIONS: Holter monitor PVC counts alone are inadequate for CPVT diagnosis, owing to the adrenergic nature of the disease. Quantifying PVC prevalence at a heart rate threshold >76% identified CPVT with moderate sensitivity (69%) and high specificity (94%).

Effects of Implantable Cardioverter-Defibrillator Leads on the Tricuspid Valve and Right Ventricle: A Randomized Trial.

BACKGROUND: There are no randomized data to inform the extent to which transvenous cardiac leads cause tricuspid regurgitation (TR). OBJECTIVES: This study sought to determine the effect of a transvenous implantable cardioverter-defibrillator (TV-ICD) on TR severity, and secondarily, on right ventricular (RV) size and function. METHODS: We evaluated TR severity before and 6 months after implantable cardioverter-defibrillator insertion in a post hoc analysis of adults randomized to receive a transvenous (n = 252) or subcutaneous implantable cardioverter-defibrillator (S-ICD) (n = 251) device. TR and RV size and systolic function were assessed by echocardiographic images analyzed in a core laboratory. RESULTS: At baseline, at least mild TR was present in 30% of individuals. At 6 months, the proportion of participants with any TR in the TV-ICD group was 42% vs 19% in the S-ICD group (P < 0.001). The proportion with moderate or severe TR was 7% in the TV-ICD group vs 2% in the S-ICD group (P = 0.021). At 6 months, the OR of at least 1 grade worsening of TR in the TV-ICD group as compared with the S-ICD group was 7.2 (95% CI: 3.3-15.8; P < 0.001). There were no differences between groups with respect to RV size or systolic function. CONCLUSIONS: Six months following TV-ICD insertion, there was a 7-fold increase in the risk of at least 1 grade worsening of TR, with 7% of individuals having TR that was moderate or severe. There was no detectable difference in RV size or function; however, longer follow-up is needed.

Distinguishing Primary Prevention From Secondary Prevention Implantable Cardioverter Defibrillators Using Administrative Health and Cardiac Device Registry Data.

Background: Administrative health data and cardiac device registries can be used to empirically evaluate outcomes and costs after implantable cardioverter defibrillator (ICD) implantation. These datasets often have incomplete information on the indication for implantation (primary vs secondary prevention of sudden cardiac death). Methods: We used 16 years of population-based cardiac device registry and administrative health data from British Columbia, Canada, to derive and internally validate statistical models that predict the likely indication for ICD implantation. We used chart review data as the reference standard for ICD indication in the Cardiac Device Registry database (CDR; 2004-2012 [Cardiac Services BC]) and nonmissing indication as the reference standard in the Heart Information System registry database (HEARTis; 2013-2019 [Cardiac Services BC]). We created 3 logistic regression prediction models in each database: one using only registry data, one using only administrative data, and one using both registry and administrative data. We assessed the predictive performance of each model using standard metrics after optimism correction with 200 bootstrap resamples. Results: Models that used registry data alone demonstrated excellent predictive performance (sensitivity ≥ 89%; specificity ≥ 87%). Models that used only administrative data performed well (sensitivity ≥ 84%; specificity ≥ 70%). Models that used both registry and administrative data showed modest gains over those that used registry data alone (sensitivity ≥ 90%; specificity ≥ 89%). Conclusions: Administrative health data and cardiac device registry data can distinguish secondary prevention ICDs from primary prevention ICDs with acceptable sensitivity and specificity. Imputation of missing ICD indication might make these data resources more useful for research and health system monitoring.

Contexte: Les données administratives de santé et les registres des dispositifs cardiaques peuvent être utilisés pour évaluer de manière empirique les résultats et les coûts associés aux défibrillateurs cardioverteurs implantables (DCI). Or, ces ensembles de données comportent souvent des informations incomplètes sur l'indication de l'implant (prévention primaire ou secondaire de la mort subite d'origine cardiaque). Méthodologie: Nous avons analysé 16 ans de données provenant du registre populationnel des dispositifs cardiaques et des données administratives de santé de la Colombie-Britannique, au Canada, pour alimenter des modèles statistiques prédisant l'indication probable de l'implant d'un DCI et pour effectuer une validation interne de ces modèles. Nous avons utilisé les données de la revue des dossiers médicaux comme norme de référence de l'indication des DCI dans le registre des dispositifs cardiaques (Cardiac Device Registry; 2004-2012 [Cardiac Services BC]) et les indications consignées comme norme de référence dans la banque de données Heart Information System (HEARTis; 2013-2019 [Cardiac Services BC]). Nous avons créé 3 modèles prédictifs par régression logistique dans chaque base de données : une utilisant seulement les données du registre, une utilisant seulement les données administratives et une utilisant les deux types de données. Nous avons évalué la performance de chaque modèle en matière de prédiction à l'aide de mesures normalisées, après correction pour l'optimisme de l'erreur à l'aide de 200 nouveaux échantillons obtenus par la méthode bootstrap. Résultats: Les modèles utilisant seulement les données du registre avaient une excellente performance prédictive (sensibilité ≥ 89 %; spécificité ≥ 87 %). Les modèles qui n'utilisaient que les données administratives donnaient quant à eux de bons résultats (sensibilité ≥ 84 %; spécificité ≥ 70 %). Enfin, les modèles qui utilisaient les données administratives et les données du registre ont donné des gains modestes par rapport aux modèles qui n'utilisaient que les données du registre (sensibilité ≥ 90 %; spécificité ≥ 89 %). Conclusions: Les données administratives de santé et les données des registres de dispositifs cardiaques permettent de distinguer les DCI implantés en prévention secondaire des DCI implantés en prévention primaire avec une sensibilité et une spécificité acceptables. Dans les cas où elle est absente, l'attribution d'une indication pour les DCI pourrait donc rendre ces ressources plus utiles pour la recherche et la surveillance du système de santé.

A Clinical Diagnostic Test for Calcium Release Deficiency Syndrome.

Importance: Sudden death and cardiac arrest frequently occur without explanation, even after a thorough clinical evaluation. Calcium release deficiency syndrome (CRDS), a life-threatening genetic arrhythmia syndrome, is undetectable with standard testing and leads to unexplained cardiac arrest. Objective: To explore the cardiac repolarization response on an electrocardiogram after brief tachycardia and a pause as a clinical diagnostic test for CRDS. Design, Setting, and Participants: An international, multicenter, case-control study including individual cases of CRDS, 3 patient control groups (individuals with suspected supraventricular tachycardia; survivors of unexplained cardiac arrest [UCA]; and individuals with genotype-positive catecholaminergic polymorphic ventricular tachycardia [CPVT]), and genetic mouse models (CRDS, wild type, and CPVT were used to define the cellular mechanism) conducted at 10 centers in 7 countries. Patient tracings were recorded between June 2005 and December 2023, and the analyses were performed from April 2023 to December 2023. Intervention: Brief tachycardia and a subsequent pause (either spontaneous or mediated through cardiac pacing). Main Outcomes and Measures: Change in QT interval and change in T-wave amplitude (defined as the difference between their absolute values on the postpause sinus beat and the last beat prior to tachycardia). Results: Among 10 case patients with CRDS, 45 control patients with suspected supraventricular tachycardia, 10 control patients who experienced UCA, and 3 control patients with genotype-positive CPVT, the median change in T-wave amplitude on the postpause sinus beat (after brief ventricular tachycardia at ≥150 beats/min) was higher in patients with CRDS (P < .001). The smallest change in T-wave amplitude was 0.250 mV for a CRDS case patient compared with the largest change in T-wave amplitude of 0.160 mV for a control patient, indicating 100% discrimination. Although the median change in QT interval was longer in CRDS cases (P = .002), an overlap between the cases and controls was present. The genetic mouse models recapitulated the findings observed in humans and suggested the repolarization response was secondary to a pathologically large systolic release of calcium from the sarcoplasmic reticulum. Conclusions and Relevance: There is a unique repolarization response on an electrocardiogram after provocation with brief tachycardia and a subsequent pause in CRDS cases and mouse models, which is absent from the controls. If these findings are confirmed in larger studies, this easy to perform maneuver may serve as an effective clinical diagnostic test for CRDS and become an important part of the evaluation of cardiac arrest.

Maximising Large Language Model Utility in Cardiovascular Care: A Practical Guide.

Large language models (LLMs) have emerged as powerful tools in artificial intelligence, demonstrating remarkable capabilities in natural language processing and generation. In this article, we explore the potential applications of LLMs in enhancing cardiovascular care and research. We discuss how LLMs can be used to simplify complex medical information, improve patient-physician communication, and automate tasks such as summarising medical articles and extracting key information. In addition, we highlight the role of LLMs in categorising and analysing unstructured data, such as medical notes and test results, which could revolutionise data handling and interpretation in cardiovascular research. However, we also emphasise the limitations and challenges associated with LLMs, including potential biases, reasoning opacity, and the need for rigourous validation in medical contexts. This review provides a practical guide for cardiovascular professionals to understand and harness the power of LLMs while navigating their limitations. We conclude by discussing the future directions and implications of LLMs in transforming cardiovascular care and research.

The potential of artificial intelligence to revolutionize health care delivery, research, and education in cardiac electrophysiology.

The field of electrophysiology (EP) has benefited from numerous seminal innovations and discoveries that have enabled clinicians to deliver therapies and interventions that save lives and promote quality of life. The rapid pace of innovation in EP may be hindered by several challenges including the aging population with increasing morbidity, the availability of multiple costly therapies that, in many instances, confer minor incremental benefit, the limitations of healthcare reimbursement, the lack of response to therapies by some patients, and the complications of the invasive procedures performed. To overcome these challenges and continue on a steadfast path of transformative innovation, the EP community must comprehensively explore how artificial intelligence (AI) can be applied to healthcare delivery, research, and education and consider all opportunities in which AI can catalyze innovation; create workflow, research, and education efficiencies; and improve patient outcomes at a lower cost. In this white paper, we define AI and discuss the potential of AI to revolutionize the EP field. We also address the requirements for implementing, maintaining, and enhancing quality when using AI and consider ethical, operational, and regulatory aspects of AI implementation. This manuscript will be followed by several perspective papers that will expand on some of these topics.

Autopsy of all young sudden death cases is important to increase survival in family members left behind.

Sudden cardiac death (SCD) is an important public health problem worldwide, accounting for an estimated 6-20% of total mortality. A significant proportion of SCD is caused by inherited heart disease, especially among the young. An autopsy is crucial to establish a diagnosis of inherited heart disease, allowing for subsequent identification of family members who require cardiac evaluation. Autopsy of cases of unexplained sudden death in the young is recommended by both the European Society of Cardiology and the American Heart Association. Overall autopsy rates, however, have been declining in many countries across the globe, and there is a lack of skilled trained pathologists able to carry out full autopsies. Recent studies show that not all cases of sudden death in the young are autopsied, likely due to financial, administrative, and organizational limitations as well as awareness among police, legal authorities, and physicians. Consequently, diagnoses of inherited heart disease are likely missed, along with the opportunity for treatment and prevention among surviving relatives. This article reviews the evidence for the role of autopsy in sudden death, how the cardiologist should interpret the autopsy-record, and how this can be integrated and implemented in clinical practice. Finally, we identify areas for future research along with potential for healthcare reform aimed at increasing autopsy awareness and ultimately reducing mortality from SCD.

2024 HRS expert consensus statement on arrhythmias in the athlete: Evaluation, treatment, and return to play.

Youth and adult participation in sports continues to increase, and athletes may be diagnosed with potentially arrhythmogenic cardiac conditions. This international multidisciplinary document is intended to guide electrophysiologists, sports cardiologists, and associated health care team members in the diagnosis, treatment, and management of arrhythmic conditions in the athlete with the goal of facilitating return to sport and avoiding the harm caused by restriction. Expert, disease-specific risk assessment in the context of athlete symptoms and diagnoses is emphasized throughout the document. After appropriate risk assessment, management of arrhythmias geared toward return to play when possible is addressed. Other topics include shared decision-making and emergency action planning. The goal of this document is to provide evidence-based recommendations impacting all areas in the care of athletes with arrhythmic conditions. Areas in need of further study are also discussed.

Device-specific quality of life: Results from the ATLAS trial-Avoid Transvenous Leads in Appropriate Subjects.

AIM: Patient reported outcomes (PROs) provide important insights into patients' acceptance of their medical devices. ATLAS, a randomized, multi-center, open-label clinical trial, recently reported fewer perioperative complications in S-ICD compared to TV-ICD patients. This study reports PROs, including device-specific and generic quality of life (QOL) from the ATLAS trial. METHODS AND RESULTS: Device-specific QOL was the primary PRO using the Florida Patient Acceptance Survey (FPAS) at 1-and 6-months post-implantation. Secondary outcomes included generic QOL using the Medical Outcomes Survey (SF-36) pre-implant and 6-months post-implantation. FPAS and SF-36 were analyzed using ANCOVA. Pain measured using a Numeric Rating Scale, at 1-and 6-months, anesthetic, BMI and within/between differences were analyzed using descriptive statistics and mixed-effects linear models (MLM). Of the 503 patients randomized in ATLAS, 404 had complete FPAS data to include in this analysis. Participant characteristics were balanced. There were no significant differences between S-ICD and TV-ICD for FPAS or SF-36, across timepoints. Mean total FPAS scores increased from 73.73 (16.09) to 77.05 (16.13) and 74.43 (15.35) to 78.25 (15.88) for S-ICD and TV-ICD, respectively, (p <0.001). PROs suggested that both devices were associated with good QOL. CONCLUSION: Device-specific and generic QOL were similar between S-ICD and TV-ICD groups up to 6-months post-implantation indicating that regardless of device type, both groups reported good device specific QOL in ATLAS patients. S-ICD patients reported higher pain scores at implant, but pain decreased by 6 months. The findings offer evidence that can be included during shared decision-making. The inclusion of patient partners in ATLAS provided opportunity to measure PROs that were deemed important to patients.

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical gaps remain, particularly within case ascertainment, access to genetic testing, and risk stratification. Artificial intelligence (AI), specifically machine learning and its subset deep learning, present promising solutions to these challenges. The capacity of AI to process vast amounts of patient data and identify disease patterns differentiates them from traditional methods, which are time- and resource-intensive. To date, AI models have shown immense potential in condition detection (including asymptomatic/concealed disease) and genotype and phenotype identification, exceeding expert cardiologists in these tasks. Additionally, they have exhibited applicability for general population screening, improving case ascertainment in a set of conditions that are often asymptomatic such as left ventricular dysfunction. Third, models have shown the ability to improve testing protocols; through model identification of disease and genotype, specific clinical testing (eg, drug challenges or further diagnostic imaging) can be avoided, reducing health care expenses, speeding diagnosis, and possibly allowing for more incremental or targeted genetic testing approaches. These significant benefits warrant continued investigation of AI, particularly regarding the development and implementation of clinically applicable screening tools. In this review we summarize key developments in AI, including studies in long QT syndrome, Brugada syndrome, hypertrophic cardiomyopathy, and arrhythmogenic cardiomyopathies, and provide direction for effective future AI implementation in clinical practice.

An international multicenter cohort study on implantable cardioverter-defibrillators for the treatment of symptomatic children with catecholaminergic polymorphic ventricular tachycardia.

BACKGROUND: Catecholaminergic polymorphic ventricular tachycardia (CPVT) may cause sudden cardiac death (SCD) despite medical therapy. Therefore, implantable cardioverter-defibrillators (ICDs) are commonly advised. However, there is limited data on the outcomes of ICD use in children. OBJECTIVE: The purpose of this study was to compare the risk of arrhythmic events in pediatric patients with CPVT with and without an ICD. METHODS: We compared the risk of SCD in patients with RYR2 (ryanodine receptor 2) variants and phenotype-positive symptomatic CPVT patients with and without an ICD who were younger than 19 years and had no history of sudden cardiac arrest at phenotype diagnosis. The primary outcome was SCD; secondary outcomes were composite end points of SCD, sudden cardiac arrest, or appropriate ICD shocks with or without arrhythmic syncope. RESULTS: The study included 235 patients, 73 with an ICD (31.1%) and 162 without an ICD (68.9%). Over a median follow-up of 8.0 years (interquartile range 4.3-13.4 years), SCD occurred in 7 patients (3.0%), of whom 4 (57.1%) were noncompliant with medications and none had an ICD. Patients with ICD had a higher risk of both secondary composite outcomes (without syncope: hazard ratio 5.85; 95% confidence interval 3.40-10.09; P < .0001; with syncope: hazard ratio 2.55; 95% confidence interval 1.50-4.34; P = .0005). Thirty-one patients with ICD (42.5%) experienced appropriate shocks, 18 (24.7%) inappropriate shocks, and 21 (28.8%) device-related complications. CONCLUSION: SCD events occurred only in patients without an ICD and mostly in those not on optimal medical therapy. Patients with an ICD had a high risk of appropriate and inappropriate shocks, which may be reduced with appropriate device programming. Severe ICD complications were common, and risks vs benefits of ICDs need to be considered.