Ackerman, Michael J.

Abstract Aims ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy (ARVC) and we hypothesized that an artificial intelligence (AI)-enhanced ECG could help identify patients with ARVC and serve as a valuable disease-detection tool. Methods and results We created a convolutional neural network to detect ARVC using a 12-lead ECG. All patients with ARVC who met the 2010 task force criteria and had disease-causative genetic variants were included. All case ECGs were randomly assigned in an 8:1:1 ratio into training, validation, and testing groups. The case ECGs were age- and sex-matched with control ECGs at our institution in a 1:100 ratio. Seventy-seven patients (51% male; mean age 47.2 ± 19.9), including 56 patients with PKP2, 7 with DSG2, 6 with DSC2, 6 with DSP, and 2 with JUP were included. The model was trained using 61 case ECGs and 5009 control ECGs; validated with 7 case ECGs and 678 control ECGs and tested in 22 case ECGs and 1256 control ECGs. The sensitivity, specificity, positive and negative predictive values of the model were 77.3, 62.9, 3.32, and 99.4%, respectively. The area under the curve for rhythm ECG and median beat ECG was 0.75 and 0.76, respectively. Conclusion Our study found that the model performed well in excluding ARVC and supports the concept that the AI ECG can serve as a biomarker for ARVC if a larger cohort were available for network training. A multicentre study including patients with ARVC from other centres would be the next step in refining, testing, and validating this algorithm.

Background: The safety of triple antiemetic therapy consisting of ondansetron, haloperidol, and a steroid, to surgical patients is unknown. Objective: To determine the incidence of torsade de pointes (TdP) or death following perioperative administration of triple antiemetic therapy. Methods: A retrospective cohort study identified 19,874 patients who received 22,202 doses of triple antiemetics during the 2.5-year time frame from March 4, 2020 to September 7, 2022 for surgical nausea prophylaxis or treatment of nausea. These patients above were cross-matched with an electrocardiogram and adverse outcome database; this identified 226 patients with documentation of a QTc > 450 ms, all ventricular tachycardias including TdP within 48 hours of receiving triple antiemetic therapy, or death within 7 days of receiving ondansetron. Results: There were 3 patients who had documented VT (n = 3), but there were no documented incidents of TdP (n = 0). There were 9 codes called on patients within 48 hours of medication administration, and none of them were due to ventricular arrythmias (n = 0). A total of 11 patients died within 7 days of triple antiemetic therapy. Ten of the 11 deaths were determined to not be from the triple antiemetic. One patient died at home within 24 hours of the procedure of an unknown cause (n = 1). Conclusions and Relevance: No episodes of TdP were identified in patients receiving triple antiemetic therapy perioperatively, though the cause of death in 1 patient could not be determined. This suggest that low-dose triple antiemetic therapy is low risk for the development of TdP.

Abstract Aims In long QT syndrome (LQTS), primary prevention improves outcome; thus, early identification is key. The most common LQTS phenotype is a foetal heart rate (FHR) < 3rd percentile for gestational age (GA) but the effects of cohort, genotype, variant, and maternal β-blocker therapy on FHR are unknown. We assessed the influence of these factors on FHR in pregnancies with familial LQTS and developed a FHR/GA threshold for LQTS. Methods and results In an international cohort of pregnancies in which one parent had LQTS, LQTS genotype, familial variant, and maternal β-blocker effects on FHR were assessed. We developed a testing algorithm for LQTS using FHR and GA as continuous predictors. Data included 1966 FHRs at 7–42 weeks’ GA from 267 pregnancies/164 LQTS families [220 LQTS type 1 (LQT1), 35 LQTS type 2 (LQT2), and 12 LQTS type 3 (LQT3)]. The FHRs were significantly lower in LQT1 and LQT2 but not LQT3 or LQTS negative. The LQT1 variants with non-nonsense and severe function loss (current density or β-adrenergic response) had lower FHR. Maternal β-blockers potentiated bradycardia in LQT1 and LQT2 but did not affect FHR in LQTS negative. A FHR/GA threshold predicted LQT1 and LQT2 with 74.9% accuracy, 71% sensitivity, and 81% specificity. Conclusion Genotype, LQT1 variant, and maternal β-blocker therapy affect FHR. A predictive threshold of FHR/GA significantly improves the accuracy, sensitivity, and specificity for LQT1 and LQT2, above the infant’s a priori 50% probability. We speculate this model may be useful in screening for LQTS in perinatal subjects without a known LQTS family history.

BACKGROUND: Understanding the incidence, causes, and trends of sudden cardiac death (SCD) among young competitive athletes is critical to inform preventive policies. METHODS: This study included National Collegiate Athletic Association athlete deaths during a 20-year time frame (July 1, 2002, through June 30, 2022). Athlete deaths were identified through 4 separate independent databases and search strategies (National Collegiate Athletic Association resolutions list, Parent Heart Watch database and media reports, National Center for Catastrophic Sports Injury Research database, and insurance claims). Autopsy reports and medical history were reviewed by an expert panel to adjudicate causes of SCD. RESULTS: A total of 143 SCD cases in National Collegiate Athletic Association athletes were identified from 1102 total deaths. The National Collegiate Athletic Association resolutions list identified 117 of 143 (82%), the Parent Heart Watch database or media reports identified 89 of 143 (62%), the National Center for Catastrophic Sports Injury Research database identified 63 of 143 (44%), and insurance claims identified 27 of 143 (19%) SCD cases. The overall incidence of SCD was 1:63 682 athlete-years (95% CI, 1:54 065–1:75 010). Incidence was higher in male athletes than in female athletes (1:43 348 [95% CI, 1:36 228–1:51 867] versus 1:164 504 [95% CI, 1:110 552–1:244 787] athlete-years, respectively) and Black athletes compared with White athletes (1:26 704 [1:20 417–1:34 925] versus 1:74 581 [1:60 247–1:92 326] athlete-years, respectively). The highest incidence of SCD was among Division I male basketball players (1:8188 [White, 1:5848; Black, 1:7696 athlete-years]). The incidence rate for SCD decreased over the study period (5-year incidence rate ratio, 0.71 [95% CI, 0.61–0.82]), whereas the rate of noncardiovascular deaths remained stable (5-year incidence rate ratio, 0.98 [95% CI, 0.94–1.04]). Autopsy-negative sudden unexplained death (19.5%) was the most common postmortem examination finding, followed by idiopathic left ventricular hypertrophy or possible cardiomyopathy (16.9%) and hypertrophic cardiomyopathy (12.7%), in cases with enough information for adjudication (118 of 143). Eight cases of death were attributable to myocarditis over the study period (1 case from January 1, 2020, through June 30, 2022), with none attributed to COVID-19 infection. SCD events were exertional in 50% of cases. Exertional SCD was more common among those with coronary artery anomalies (100%) and arrhythmogenic cardiomyopathy (83%). CONCLUSIONS: The incidence of SCD in college athletes has decreased. Male sex, Black race, and basketball are associated with a higher incidence of SCD.

Abstract Background/Introduction Arrhythmogenic mitral valve prolapse syndrome (AMVPS) is a female-predominant sudden cardiac death (SCD)-predisposing disorder characterized clinically by myxomatous mitral valve prolapse (MVP), inferolateral T-wave inversions and complex ventricular ectopy. However, insights into the pathogenesis and potential genetic basis of AMVPS are currently lacking. Purpose Considering recent case reports that suggest a potential role for genetic cardiomyopathies in the pathogenesis of AMVPS, we sought to determine the yield of pathogenic/likely pathogenic (P/LP) genetic variants in strong evidence cardiomyopathy-susceptibility genes amongst AMVPS patients who underwent clinical genetic testing. Methods In this retrospective study, the medical records of 4,907 patients referred to our cardiovascular genetics clinic was used to identify those patients with a clinical phenotype consistent with AMVPS. After exclusion of individuals with severe mitral valve regurgitation, pertinent clinical, electrocardiographic, imaging and genetic testing data was extracted from the electronic record. For those AMVPS that underwent a form of genetic testing that encompassed 23 Clinical Genome Resource-defined strong/definitive evidence cardiomyopathy-susceptibility genes, ultra-rare (minor allele frequency ≤ 0.00005 in the Genome Aggregation Database [n=141,456 individuals]) non-synonymous variants identified within these genes were adjudicated independently as P, LP or variant of uncertain significance with the assistance of Varsome. The frequency of P/LP variants was then compared to a previously published cohort of 973 ostensibly healthy control exomes. Results Overall, 56 unrelated patients with suspected AMVPS were identified (82% female; average age at presentation of 31 ± 13 years; 32% with a family history of MVP and/or SCD). Of these, 24/56 (43%) underwent a form of clinical genetic testing that encompassed the pre-defined panel of cardiomyopathy-susceptibility genes. In comparison to control exomes (n=973), P/LP variants in strong/definitive evidence cardiomyopathy-susceptibility genes were over-represented in AMVPS patients [4/24 (16.7%) vs 20/973 (2.1%); p=0.002]. Interestingly, this enrichment was driven in large part by an excess number of A-band-localizing P/LP truncating variants in TTN-encoded titin in AMVPS cases [3/24 (12.5%) versus 4/973 (0.4%); p=0.0004]. Conclusion This study provides further evidence that a subset of AMVPS may arise secondary to a "two-hit" model whereby an underlying cardiomyopathic genetic substrate is exacerbated by the mechanical force generated by genetically unrelated myxomatous MVP resulting in maladaptive and ventricular arrhythmia-predisposing fibrosis within the inferobasal left ventricle and posteromedial papillary muscles. Larger studies are needed to better understand the potential role of genetic testing in the diagnosis, risk-stratification and management of patients with suspected AMVPS.

BACKGROUND: In severely affected patients with catecholaminergic polymorphic ventricular tachycardia, beta-blockers are often insufficiently protective. The purpose of this study was to evaluate whether flecainide is associated with a lower incidence of arrhythmic events (AEs) when added to beta-blockers in a large cohort of patients with catecholaminergic polymorphic ventricular tachycardia. METHODS: From 2 international registries, this multicenter case cross-over study included patients with a clinical or genetic diagnosis of catecholaminergic polymorphic ventricular tachycardia in whom flecainide was added to beta-blocker therapy. The study period was defined as the period in which background therapy (ie, beta-blocker type [beta1-selective or nonselective]), left cardiac sympathetic denervation, and implantable cardioverter defibrillator treatment status, remained unchanged within individual patients and was divided into pre-flecainide and on-flecainide periods. The primary end point was AEs, defined as sudden cardiac death, sudden cardiac arrest, appropriate implantable cardioverter defibrillator shock, and arrhythmic syncope. The association of flecainide with AE rates was assessed using a generalized linear mixed model assuming negative binomial distribution and random effects for patients. RESULTS: A total of 247 patients (123 [50%] females; median age at start of flecainide, 18 years [interquartile range, 14–29]; median flecainide dose, 2.2 mg/kg per day [interquartile range, 1.7–3.1]) were included. At baseline, all patients used a beta-blocker, 70 (28%) had an implantable cardioverter defibrillator, and 21 (9%) had a left cardiac sympathetic denervation. During a median pre-flecainide follow-up of 2.1 years (interquartile range, 0.4–7.2), 41 patients (17%) experienced 58 AEs (annual event rate, 5.6%). During a median on-flecainide follow-up of 2.9 years (interquartile range, 1.0–6.0), 23 patients (9%) experienced 38 AEs (annual event rate, 4.0%). There were significantly fewer AEs after initiation of flecainide (incidence rate ratio, 0.55 [95% CI, 0.38–0.83]; P =0.007). Among patients who were symptomatic before diagnosis or during the pre-flecainide period (n=167), flecainide was associated with significantly fewer AEs (incidence rate ratio, 0.49 [95% CI, 0.31–0.77]; P =0.002). Among patients with ≥1 AE on beta-blocker therapy (n=41), adding flecainide was also associated with significantly fewer AEs (incidence rate ratio, 0.25 [95% CI, 0.14–0.45]; P <0.001). CONCLUSIONS: For patients with catecholaminergic polymorphic ventricular tachycardia, adding flecainide to beta-blocker therapy was associated with a lower incidence of AEs in the overall cohort, in symptomatic patients, and particularly in patients with breakthrough AEs while on beta-blocker therapy.

ImportanceSyncope is the most powerful predictor for subsequent life-threatening events (LTEs) in patients with congenital long QT syndrome (LQTS). Whether distinct syncope triggers are associated with differential subsequent risk of LTEs is unknown.ObjectiveTo evaluate the association between adrenergic (AD)– and nonadrenergic (non–AD)-triggered syncopal events and the risk of subsequent LTEs in patients with LQT types 1 to 3 (LQT1-3).Design, Setting, and ParticipantsThis retrospective cohort study included data from 5 international LQTS registries (Rochester, New York; the Mayo Clinic, Rochester, Minnesota; Israel, the Netherlands, and Japan). The study population comprised 2938 patients with genetically confirmed LQT1, LQT2, or LQT3 stemming from a single LQTS-causative variant. Patients were enrolled from July 1979 to July 2021.ExposuresSyncope by AD and non-AD triggers.Main Outcomes and MeasuresThe primary end point was the first occurrence of an LTE. Multivariate Cox regression was used to determine the association of AD- or non–AD-triggered syncope on the risk of subsequent LTE by genotype. Separate analysis was performed in patients with β-blockers.ResultsA total of 2938 patients were included (mean [SD] age at enrollment, 29 [7] years; 1645 [56%] female). In 1331 patients with LQT1, a first syncope occurred in 365 (27%) and was induced mostly with AD triggers (243 [67%]). Syncope preceded 43 subsequent LTEs (68%). Syncopal episodes associated with AD triggers were associated with the highest risk of subsequent LTE (hazard ratio [HR], 7.61; 95% CI, 4.18-14.20; P &amp;lt; .001), whereas the risk associated with syncopal events due to non-AD triggers was statistically nonsignificant (HR, 1.50; 95% CI, 0.21-4.77; P = .97). In 1106 patients with LQT2, a first syncope occurred in 283 (26%) and was associated with AD and non-AD triggers in 106 (37%) and 177 (63%), respectively. Syncope preceded 55 LTEs (56%). Both AD- and non–AD-triggered syncope were associated with a greater than 3-fold increased risk of subsequent LTE (HR, 3.07; 95% CI, 1.66-5.67; P ≤ .001 and HR, 3.45, 95% CI, 1.96-6.06; P ≤ .001, respectively). In contrast, in 501 patients with LQT3, LTE was preceded by a syncopal episode in 7 (12%). In patients with LQT1 and LQT2, treatment with β-blockers following a syncopal event was associated with a significant reduction in the risk of subsequent LTEs. The rate of breakthrough events during treatment with β-blockers was significantly higher among those treated with selective agents vs nonselective agents.Conclusion and RelevanceIn this study, trigger-specific syncope in LQTS patients was associated with differential risk of subsequent LTE and response to β-blocker therapy.

Abstract Aims Calmodulinopathy due to mutations in any of the three CALM genes (CALM1–3) causes life-threatening arrhythmia syndromes, especially in young individuals. The International Calmodulinopathy Registry (ICalmR) aims to define and link the increasing complexity of the clinical presentation to the underlying molecular mechanisms. Methods and results The ICalmR is an international, collaborative, observational study, assembling and analysing clinical and genetic data on CALM-positive patients. The ICalmR has enrolled 140 subjects (median age 10.8 years [interquartile range 5–19]), 97 index cases and 43 family members. CALM-LQTS and CALM-CPVT are the prevalent phenotypes. Primary neurological manifestations, unrelated to post-anoxic sequelae, manifested in 20 patients. Calmodulinopathy remains associated with a high arrhythmic event rate (symptomatic patients, n = 103, 74%). However, compared with the original 2019 cohort, there was a reduced frequency and severity of all cardiac events (61% vs. 85%; P = .001) and sudden death (9% vs. 27%; P = .008). Data on therapy do not allow definitive recommendations. Cardiac structural abnormalities, either cardiomyopathy or congenital heart defects, are present in 30% of patients, mainly CALM-LQTS, and lethal cases of heart failure have occurred. The number of familial cases and of families with strikingly different phenotypes is increasing. Conclusion Calmodulinopathy has pleiotropic presentations, from channelopathy to syndromic forms. Clinical severity ranges from the early onset of life-threatening arrhythmias to the absence of symptoms, and the percentage of milder and familial forms is increasing. There are no hard data to guide therapy, and current management includes pharmacological and surgical antiadrenergic interventions with sodium channel blockers often accompanied by an implantable cardioverter–defibrillator.

Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM AI-score). However, its clinical application may be challenging due to the low disease prevalence and potentially high false-positive rate when screening unenriched cohorts. Aims: To identify clinical characteristics associated with false-positive HCM AI-score results to improve screening tool application. Methods: From a cohort of 20,677 patients with a digital 12-lead ECG in routine clinical practice in 2021, we performed a detailed chart review of the 200 patients with highest HCM AI-score to determine their HCM status and collect clinical data. Stepwise forward logistic regression was used to create a clinical variable-based “candidacy for HCM screening” score (CHS score), differentiating true- and likely true-positive from likely false-positive HCM AI-score results. We then validated the CHS score in 200 patients with the highest HCM AI-scores from an independent cohort of 15,147 patients with an ECG in 2022. Results: Among the 200 patients in 2021 (median age 71 years, 48% female), 96 (48%) were likely false-positive HCM AI-score results, 71 (36%) definite or likely true-positive results, and 33 (16%) indeterminate. The CHS score included a history of surgical septal myectomy, coronary artery bypass graft surgery, cardiac valve replacement, and pacemaker, and had an AUC of 0.88 (95% CI 0.83-0.92) for the differentiation of true- versus false-positive AI results. In the 2022 cohort, the CHS score had an AUC of 0.82 (95% CI 0.76 - 0.88). After limiting the cohort to HCM candidates identified by the CHS score, the false-positive results rate was reduced to 27/114 (24%). Conclusions: By applying the CHS score to patients with positive HCM AI-screening results, the false-positive rate decreased from 49% to 24%. Utilizing a clinical model used in tandem with an AI model improved diagnostic yield.

Introduction: Over 100 FDA-approved medications, electrolyte perturbations, and many disease states can prolong the QTc beyond its 99 th percentile value resulting in acquired QT prolongation. In contrast, approximately 1 in 2000 people have congenital long QT syndrome (LQTS) hallmarked by pathological QT prolongation secondary to genetic defects in the heart. Hypothesis: An artificial intelligence (AI) deep neural network (DNN) can distinguish patients with LQTS from those with acquired QT prolongation. Methods: The study cohort included all patients with LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic’s ECG data vault comprising over 2.5 million patients. For the AI-DNN model, every patient/control with ≥ 1 ECG above age- and sex- specific 99 th percentile values for QTc [> 460 ms for all patients (male/female) < 13 years of age, or > 470 ms for men and > 480 ms for women above this age] was included. An AI-DNN involving a multi-layer c onvolutional n eural n etwork (CNN) was developed to classify patients. LQTS patients were age- and sex- matched to controls at 1:5 ratio. Results: Among the 1,599 patients with genetically confirmed LQTS, 808 had ≥ 1 ECG with QTc above the threshold (2,987 ECGs) compared to 361,069/2.5M controls (14% of Mayo Clinic patients getting an ECG, ‘presumed negative’; 989,313 ECGs). Following age- and sex- matching and splitting, 3,309 (training), 411 (validation) and 887 (testing) control ECGs were used. This model distinguished LQTS from those with acquired QT prolongation with an AUC of 0.896 (accuracy 85%, sensitivity 77%, specificity 88%, PPV 0.58, NPV 0.94). After exclusion of patients with a wide QRS (>150 ms) or pacemaker, the model remained successful in distinguishing the two groups (AUC 0.85, accuracy 78%, sensitivity 78%, specificity 87%, PPV 59%, NPV 94%). Conclusions: For patients with a QTc exceeding its 99 th percentile values, this novel AI-DNN functions as a LQTS mutation detector being able to identify patients with abnormal QT prolongation secondary to a LQTS-causative mutation rather than acquired QT prolongation with a >50% positive predictive value. This algorithm may facilitate screening for this potentially lethal, yet highly treatable, genetic heart disease.