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Objective: To develop machine learning tools for automated hypertrophic cardiomyopathy (HCM) case recognition from echocardiographic metrics, aiming to identify HCM from standard echocardiographic data with high performance. Patients and Methods: Four different random forest machine learning models were developed using a case-control cohort composed of 5548 patients with HCM and 16,973 controls without HCM, from January 1, 2004, to March 15, 2019. Each patient with HCM was matched to 3 controls by sex, age, and year of echocardiography. Ten-fold crossvalidation was used to train the models to identify HCM. Variables included in the models were demographic characteristics (age, sex, and body surface area) and 16 standard echocardiographic metrics. Results: The models were differentiated by global, average, individual, or no strain measurements. Area under the receiver operating characteristic curves (area under the curve) ranged from 0.92 to 0.98 for the 4 separate models. Area under the curves of model 2 (using left ventricular global longitudinal strain; 0.97; 95% CI, 0.95-0.98), 3 (using averaged strain; 0.96; 95% CI, 0.94-0.97), and 4 (using 17 individual strains per patient; 0.98; 95% CI, 0.97-0.99) had comparable performance. By comparison, model 1 (no strain data; 0.92; 95% CI, 0.90-0.94) had an inferior area under the curve. Conclusion: Machine learning tools that analyze echocardiographic metrics identified HCM cases with high performance. Detection of HCM cases improved when strain data was combined with standard echocardiographic metrics.

Abstract Hypertrophic cardiomyopathy (HCM) is a genetically heterogenous condition with about half of cases remaining genetically elusive or non-genetic in origin. HCM patients with a positive genetic test (HCMSarc) present earlier and with more severe disease than those with a negative genetic test (HCMNeg). We hypothesized these differences may be due to and/or reflect proteomic and phosphoproteomic differences between the two groups. TMT-labeled mass spectrometry was performed on 15 HCMSarc, 8 HCMNeg, and 7 control samples. There were 243 proteins differentially expressed and 257 proteins differentially phosphorylated between HCMSarc and HCMNeg. About 90% of pathways altered between genotypes were in disease-related pathways and HCMSarc showed enhanced proteomic and phosphoproteomic alterations in these pathways. Thus, we show HCMSarc has enhanced proteomic and phosphoproteomic dysregulation observed which may contribute to the more severe disease phenotype.

Abstract Aims Data on the clinical course of hypertrophic cardiomyopathy (HCM) are mainly derived from tertiary HCM centre studies, and knowledge of clinical outcomes of patients leaving specialty care and returning to local physicians is limited due to gaps between clinical encounters or complete loss of follow‐up. This survey aims to describe the clinical course of HCM in patients following their evaluation at a tertiary referral centre. Methods and results A comprehensive outcomes survey was developed and sent to 4495 eligible patients with HCM previously evaluated at Mayo Clinic. Questions assessed general well‐being, New York Heart Association class, procedures performed, and probable HCM‐triggered ventricular arrhythmic events (VAEs) since last visit. In total, 2058 patients (mean age 63 ± 15 years; 42% female) responded to the survey covering a total of 10 510 patient‐years with an average of 5.4 ± 6.4 years of follow‐up since their last on‐campus/virtual visit to Mayo Clinic. During their time away from specialty care, 20% of patients reported having cardiac‐related hospitalizations and 25% reported having cardiac‐related procedures. Similar to high‐risk referral cohorts, 5% of patients reported VAEs with an event rate of 0.98 events/100 patient‐years. The prevalence of atrial fibrillation, syncope, pre‐syncope, cardiac‐related hospitalizations, and VAEs during time away from specialty care increased significantly with increasing New York Heart Association class (P

Background Sex‐specific risk management may improve outcomes in congenital long QT syndrome (LQTS). We recently developed a prediction score for cardiac events (CEs) and life‐threatening events (LTEs) in postadolescent women with LQTS. In the present study, we aimed to develop personalized risk estimates for the burden of CEs and LTEs in male adolescents with potassium channel‐mediated LQTS. Methods and Results The prognostic model was derived from the LQTS Registry headquartered in Rochester, NY, comprising 611 LQT1 or LQT2 male adolescents from age 10 through 20 years, using the following variables: genotype/mutation location, QTc‐specific thresholds, history of syncope, and β‐blocker therapy. Anderson‐Gill modeling was performed for the end point of CE burden (total number of syncope, aborted cardiac arrest, and appropriate defibrillator shocks). The applicability of the CE prediction model was tested for the end point of the first LTE (excluding syncope and adding sudden cardiac death) using Cox modeling. A total of 270 CEs occurred during follow‐up. The genotype–phenotype risk prediction model identified low‐, intermediate‐, and high‐risk groups, comprising 74%, 14%, and 12% of the study population, respectively. Compared with the low‐risk group, high‐risk male subjects experienced a pronounced 5.2‐fold increased risk of recurrent CEs (P

Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM). However, its application in routine clinical practice may be challenging owing to the low disease prevalence and potentially high false-positive rates. Objective: Identify clinical characteristics associated with true- and false-positive HCM AI-ECG results to improve its clinical application. Methods: We reviewed the records of the 200 patients with highest HCM AI-ECG scores in January 2021 at our institution. Logistic regression was used to create a clinical variable–based “Candidacy for HCM Detection (HCM-DETECT)” score, differentiating true-positive from false-positive AI-ECG results. We validated the HCM-DETECT score in an independent cohort of 200 patients with the highest AI-ECG scores from January 2022. Results: In the 2021 cohort (median age 71 [interquartile range 58–80] years, 48% female), the rates of true-positive, false-positive, and indeterminate AI-ECG results for HCM detection were 36%, 48%, and 16%, respectively. In the 2022 cohort, the rates were 26%, 47%, and 27%, respectively. The HCM-DETECT score included age, coronary artery disease, prior pacemaker, and prior cardiac valve surgery, and had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.73–0.87) for differentiating true- vs false-positive AI results. When the 2022 cohort was limited to HCM detection candidates identified with the HCM-DETECT score, the false-positive AI-ECG rate was reduced from 47% to 13.5%. Conclusion: Application of a clinical score (HCM-DETECT) in tandem with an AI-ECG model improved HCM detection yield, reducing the false-positive rate of AI-ECG more than 3-fold.

Abstract Background Cardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM) patients. However, collection of information from large numbers of CMR reports by manual review is time-consuming, error-prone and costly. Natural language processing (NLP) is an artificial intelligence method for automated extraction of information from narrative text including text in CMR reports in electronic health records (EHR). Our objective was to assess whether NLP can accurately extract diagnosis of HCM from CMR reports. Methods An NLP system with two tiers was developed for information extraction from narrative text in CMR reports; the first tier extracted information regarding HCM diagnosis while the second extracted categorical and numeric concepts for HCM classification. We randomly allocated 200 HCM patients with CMR reports from 2004 to 2018 into training (100 patients with 185 CMR reports) and testing sets (100 patients with 206 reports). Results NLP algorithms demonstrated very high performance compared to manual annotation. The algorithm to extract HCM diagnosis had accuracy of 0.99. The accuracy for categorical concepts included HCM morphologic subtype 0.99, systolic anterior motion of the mitral valve 0.96, mitral regurgitation 0.93, left ventricular (LV) obstruction 0.94, location of obstruction 0.92, apical pouch 0.98, LV delayed enhancement 0.93, left atrial enlargement 0.99 and right atrial enlargement 0.98. Accuracy for numeric concepts included maximal LV wall thickness 0.96, LV mass 0.99, LV mass index 0.98, LV ejection fraction 0.98 and right ventricular ejection fraction 0.99. Conclusions NLP identified and classified HCM from CMR narrative text reports with very high performance.

Background Clinical practice recommendations for participation in sports and exercise among young competitive athletes with cardiovascular conditions at risk for sudden death are based largely on expert consensus with a paucity of prospective outcomes data. Recent guidelines have taken a more permissive approach, using a shared decision‐making model. However, the impact and outcomes of this strategy remain unknown. Methods The ORCCA (Outcomes Registry for Cardiac Conditions in Athletes) study is a prospective, multicenter, longitudinal, observational cohort study designed to monitor clinical outcomes in athletes with potentially life‐threatening cardiovascular conditions. The study will assess sports eligibility decision‐making, exercise habits, psychosocial well‐being, and long‐term cardiovascular outcomes among young competitive athletes with cardiovascular conditions. Competitive athletes aged 18 to

A 17-year-old male elite athlete presented for evaluation after an abnormal pre-competitive college screening electrocardiogram. Subsequent evaluation revealed the presence of hypertrophic cardiomyopathy. He remained asymptomatic throughout four years of follow-up. Through shared decision making, he continued to play competitively and is now a professional athlete. (Level of Difficulty: Advanced.)

Mayfield et al. describe the implementation and feasibility of an exclusively remote randomized clinical trial of hydroxychloroquine and azithromycin for the treatment of COVID-19. The trial included monitoring of cardiovascular safety which was successfully done using digital technologies.

Background: The follow-up of implantable cardioverter-defibrillators (ICDs) generates large amounts of valuable structured and unstructured data embedded in device interrogation reports. Objective: We aimed to build a natural language processing (NLP) model for automated capture of ICD-recorded events from device interrogation reports using a single-center cohort of patients with hypertrophic cardiomyopathy (HCM). Methods: A total of 687 ICD interrogation reports from 247 HCM patients were included. Using a derivation set of 480 reports, we developed a rule-based NLP algorithm based on unstructured (free-text) data from the interpretation field of the ICD reports to identify sustained atrial and ventricular arrhythmias, and ICD therapies. A separate model based on structured numerical tabulated data was also developed. Both models were tested in a separate set of the 207 remaining ICD reports. Diagnostic performance was determined in reference to arrhythmia and ICD therapy annotations generated by expert manual review of the same reports. Results: The NLP system achieved sensitivity 0.98 and 0.99, and F1-scores 0.98 and 0.92 for arrhythmia and ICD therapy events, respectively. In contrast, the performance of the structured data model was significantly lower with sensitivity 0.33 and 0.76, and F1-scores 0.45 and 0.78, for arrhythmia and ICD therapy events, respectively. Conclusion: An automated NLP system can capture arrhythmia events and ICD therapies from unstructured device interrogation reports with high accuracy in HCM. These findings demonstrate the feasibility of an NLP paradigm for the extraction of data for clinical care and research from ICD reports embedded in the electronic health record.

Abstract This international multidisciplinary document intends to provide clinicians with evidence‐based practical patient‐centered recommendations for evaluating patients and decedents with (aborted) sudden cardiac arrest and their families. The document includes a framework for the investigation of the family allowing steps to be taken, should an inherited condition be found, to minimize further events in affected relatives. Integral to the process is counseling of the patients and families, not only because of the emotionally charged subject, but because finding (or not finding) the cause of the arrest may influence management of family members. The formation of multidisciplinary teams is essential to provide a complete service to the patients and their families, and the varied expertise of the writing committee was formulated to reflect this need. The document sections were divided up and drafted by the writing committee members according to their expertise. The recommendations represent the consensus opinion of the entire writing committee, graded by Class of Recommendation and Level of Evidence. The recommendations were opened for public comment and reviewed by the relevant scientific and clinical document committees of the Asia Pacific Heart Rhythm Society (APHRS) and the Heart Rhythm Society (HRS); the document underwent external review and endorsement by the partner and collaborating societies. While the recommendations are for optimal care, it is recognized that not all resources will be available to all clinicians. Nevertheless, this document articulates the evaluation that the clinician should aspire to provide for patients with sudden cardiac arrest, decedents with sudden unexplained death, and their families.

Objective: To systematically review the literature and to estimate the risk of chloroquine (CQ) and hydroxychloroquine (HCQ) cardiac toxicity in patients with coronavirus disease 2019 (COVID-19). Methods: We searched multiple data sources including PubMed/MEDLINE, Ovid Embase, Ovid EBM Reviews, Scopus, and Web of Science and medrxiv.org from November 2019 through May 27, 2020. We included studies that enrolled patients with COVID-19 treated with CQ or HCQ, with or without azithromycin, and reported on cardiac toxic effects. We performed a meta-analysis using the arcsine transformation of the different incidences. Results: A total of 19 studies with a total of 5652 patients were included. The pooled incidence of torsades de pointes arrhythmia, ventricular tachycardia, or cardiac arrest was 3 per 1000 (95% CI, 0-21; I2=96%) in 18 studies with 3725 patients. Among 13 studies of 4334 patients, the pooled incidence of discontinuation of CQ or HCQ due to prolonged QTc or arrhythmias was 5% (95% CI, 1-11; I2=98%). The pooled incidence of change in QTc from baseline of 60 milliseconds or more or QTc of 500 milliseconds or more was 9% (95% CI, 3-17; I2=97%). Mean or median age, coronary artery disease, hypertension, diabetes, concomitant QT-prolonging medications, intensive care unit admission, and severity of illness in the study populations explained between-studies heterogeneity. Conclusion: Treatment of patients with COVID-19 with CQ or HCQ is associated with an important risk of drug-induced QT prolongation and relatively higher incidence of torsades de pointes, ventricular tachycardia, or cardiac arrest. Therefore, these agents should not be used routinely in the management of COVID-19 disease. Patients with COVID-19 who are treated with antimalarials for other indications should be adequately monitored.

Background Sudden cardiac arrest is the leading mode of death in the United States. Epilepsy affects 1% of Americans; yet epidemiological data show a prevalence of 4% in cases of sudden cardiac arrest. Sudden unexpected death in epilepsy (SUDEP) may share features with sudden cardiac arrest. The objective of this study was to report autopsy and genomic findings in a large cohort of SUDEP cases. Methods and Results Mayo Clinic Sudden Death Registry containing cases (ages 0–90 years) of sudden unexpected and unexplained deaths 1960 to present was queried. Exome sequencing performed on decedent cases. From 13 687 cases of sudden death, 656 (4.8%) had a history of seizures, including 368 confirmed by electroencephalography, 96 classified as SUDEP, 58 as non‐SUDEP, and 214 as unknown (insufficient records). Mean age of death in SUDEP was 37 (±19.7) years; 56 (58.3%) were male; 65% of deaths occurred at night; 54% were found in bed; and 80.6% were prone. Autopsies were obtained in 83 cases; bystander coronary artery disease was frequently reported as cause of death; nonspecific fibrosis was seen in 32.6% of cases, in structurally normal hearts. There were 4 cases of Dravet syndrome with pathogenic variants in SCN1A gene. Using whole exome sequencing in 11 cases, 18 ultrarare nonsynonymous variants were identified in 6 cases including CACNB2, RYR2, CLNB, CACNA1H, and CLCN2. Conclusions This study examined one of the largest single‐center US series of SUDEP cases. Several cases were reclassified as SUDEP, 15% had an ECG when alive, and 11 (11.4%) had blood for whole exome sequencing analysis. The most frequent antemortem genetic finding was pathogenic variants in SCN1A; postmortem whole exome sequencing identified 18 ultrarare variants.

Abstract Background Interval duration measurements (IDMs) were compared between standard 12‐lead electrocardiograms (ECGs) and 6‐lead ECGs recorded with AliveCor's KardiaMobile 6L, a hand‐held mobile device designed for use by patients at home. Methods Electrocardiograms were recorded within, on average, 15 min from 705 patients in Mayo Clinic's Windland Smith Rice Genetic Heart Rhythm Clinic. Interpretable 12‐lead and 6‐lead recordings were available for 685 out of 705 (97%) eligible patients. The most common diagnosis was congenital long QT syndrome (LQTS, 343/685 [50%]), followed by unaffected relatives and patients (146/685 [21%]), and patients with other genetic heart diseases, including hypertrophic cardiomyopathy (36 [5.2%]), arrhythmogenic cardiomyopathy (23 [3.4%]), and idiopathic ventricular fibrillation (14 [2.0%]). IDMs were performed by a central ECG laboratory using lead II with a semi‐automated technique. Results Despite differences in patient position (supine for 12‐lead ECGs and sitting for 6‐lead ECGs), mean IDMs were comparable, with mean values for the 12‐lead and 6‐lead ECGs for QTcF, heart rate, PR, and QRS differing by 2.6 ms, −5.5 beats per minute, 1.0 and 1.2 ms, respectively. Despite a modest difference in heart rate, intervals were close enough to allow a detection of clinically meaningful abnormalities. Conclusions The 6‐lead hand‐held device is potentially useful for a clinical follow‐up of remote patients, and for a safety follow‐up of patients participating in clinical trials who cannot visit the investigational site. This technology may extend the use of 12‐lead ECG recordings during the current COVID‐19 pandemic as remote patient monitoring becomes more common in virtual or hybrid‐design clinical studies.

Abstract Human fibrin hydrogels are a popular choice for use as a biomaterial within tissue engineered constructs because they are biocompatible, nonxenogenic, autologous use compatible, and biodegradable. We have recently demonstrated the ability to culture induced pluripotent stem cell (iPSC)‐derived retinal pigment epithelium on fibrin hydrogels. However, iPSCs themselves have relatively few substrate options (e.g., laminin) for expansion in adherent cell culture for use in cell therapy. To address this, we investigated the potential of culturing iPSCs on fibrin hydrogels for three‐dimensional applications and further examined the use of fibrinogen, the soluble precursor protein, as a coating substrate for traditional adherent cell culture. iPSCs successfully adhered to and proliferated on fibrin hydrogels. The two‐dimensional culture with fibrinogen allows for immediate adaption of culture models to a nonxenogeneic model. Similarly, multiple commercially available iPSC lines adhered to and proliferated on fibrinogen coated surfaces. iPSCs cultured on fibrinogen expressed similar levels of the pluripotent stem cell markers SSea4 (98.7% ± 1.8%), Oct3/4 (97.3% ± 3.8%), TRA1‐60 (92.2% ± 5.3%), and NANOG (96.0% ± 3.9%) compared with iPSCs on Geltrex. Using a trilineage differentiation assay, we found no difference in the ability of iPSCs grown on fibrinogen or Geltrex to differentiate to endoderm, mesoderm, or ectoderm. Finally, we demonstrated the ability to differentiate iPSCs to endothelial cells using only fibrinogen coated plates. On the basis of these data, we conclude that human fibrinogen provides a readily available and inexpensive alternative to laminin‐based products for the growth, expansion, and differentiation of iPSCs for use in research and clinical cell therapy applications. Stem Cells Translational Medicine 2019;8:512–521

Background: Treatment options for outpatients with COVID-19 could reduce morbidity and prevent SARS-CoV-2 transmission. Methods: In this randomized, double-blind, three-arm (1:1:1) placebo-equivalent controlled trial conducted remotely throughout the United States, adult outpatients with laboratory-confirmed SARS-CoV-2 infection were recruited. Participants were randomly assigned to receive hydroxychloroquine (HCQ) (400 mg BID x1day, followed by 200 mg BID x9days) with or without azithromycin (AZ) (500 mg, then 250 mg daily x4days) or placebo-equivalent (ascorbic acid (HCQ) and folic acid (AZ)), stratified by risk for progression to severe COVID-19 (high-risk vs. low-risk). Self-collected nasal swabs for SARS-CoV-2 PCR, FLUPro symptom surveys, EKGs and vital signs were collected daily. Primary endpoints were: (a) 14-day progression to lower respiratory tract infection (LRTI), 28-day COVID-19 related hospitalization, or death; (b) 14-day time to viral clearance; secondary endpoints included time to symptom resolution (ClinicalTrials.gov: NCT04354428). Due to the low rate of clinical outcomes, the study was terminated for operational futility. Findings: Between 15th April and 27th July 2020, 231 participants were enrolled and 219 initiated medication a median of 5.9 days after symptom onset. Among 129 high-risk participants, incident LRTI occurred in six (4.7%) participants (two control, four HCQ/AZ) and COVID-19 related hospitalization in seven (5.4%) (four control, one HCQ, two HCQ/AZ); no LRTI and two (2%) hospitalizations occurred in the 102 low-risk participants (one HCQ, one HCQ/AZ). There were no deaths. Among 152 participants with viral shedding at enrollment, median time to clearance was 5 days (95% CI=4–6) in HCQ, 6 days (95% CI=4–8) in HCQ/AZ, and 8 days (95% CI=6–10) in control. Viral clearance was faster in HCQ (HR=1.62, 95% CI=1.01–2.60, p = 0.047) but not HCQ/AZ (HR=1.25, p = 0.39) compared to control. Among 197 participants who met the COVID-19 definition at enrollment, time to symptom resolution did not differ by group (HCQ: HR=1.02, 95% CI-0.63–1.64, p = 0.95, HCQ/AZ: HR=0.91, 95% CI=0.57–1.45, p = 0.70). Interpretation: Neither HCQ nor HCQ/AZ shortened the clinical course of outpatients with COVID-19, and HCQ, but not HCQ/AZ, had only a modest effect on SARS-CoV-2 viral shedding. HCQ and HCQ/AZ are not effective therapies for outpatient treatment of SARV-CoV-2 infection. Funding: The COVID-19 Early Treatment Study was funded by the Bill & Melinda Gates Foundation (INV-017062) through the COVID-19 Therapeutics Accelerator. University of Washington Institute of Translational Health Science (ITHS) grant support (UL1 TR002319), KL2 TR002317, and TL1 TR002318 from NCATS/NIH funded REDCap. The content is solely the responsibility of the authors and does not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated. PAN and MJA were supported by the Mayo Clinic Windland Smith Rice Comprehensive Sudden Cardiac Death Program.Trial registration ClinicalTrials.gov number NCT04354428

The analysis and interpretation of cardiac magnetic resonance (CMR) images are often time-consuming. The automated segmentation of cardiac structures can reduce the time required for image analysis. Spatial similarities between different CMR image types were leveraged to jointly segment multiple sequences using a segmentation model termed a multi-image type UNet (MI-UNet). This model was developed from 72 exams (46% female, mean age 63 ± 11 years) performed on patients with hypertrophic cardiomyopathy. The MI-UNet for steady-state free precession (SSFP) images achieved a superior Dice similarity coefficient (DSC) of 0.92 ± 0.06 compared to 0.87 ± 0.08 for a single-image type UNet (p < 0.001). The MI-UNet for late gadolinium enhancement (LGE) images also had a superior DSC of 0.86 ± 0.11 compared to 0.78 ± 0.11 for a single-image type UNet (p = 0.001). The difference across image types was most evident for the left ventricular myocardium in SSFP images and for both the left ventricular cavity and the left ventricular myocardium in LGE images. For the right ventricle, there were no differences in DCS when comparing the MI-UNet with single-image type UNets. The joint segmentation of multiple image types increases segmentation accuracy for CMR images of the left ventricle compared to single-image models. In clinical practice, the MI-UNet model may expedite the analysis and interpretation of CMR images of multiple types.

Background Sorbs2b (sorbin and SH3 domain‐containing 2b) was recently identified as a cardiomyopathy gene from a zebrafish mutagenesis screen. However, cardiac functions of its mammalian ortholog remain elusive. Methods and Results We conducted a detailed expression and subcellular localization analysis of Sorbs2 ortholog in mice and a phenotypic characterization in Sorbs2 knockout mice. Sorbs2 is highly expressed in the mouse heart and encodes an adhesion junction/desmosome protein that is mainly localized to the intercalated disc. A mutation with near complete depletion of the Sorbs2 protein in mice results in phenotypes characteristic of human arrhythmogenic cardiomyopathy (ACM), including right ventricular dilation, right ventricular dysfunction, spontaneous ventricular tachycardia, and premature death. Sorbs2 is required to maintain the structural integrity of intercalated disc. Its absence resulted in profound cardiac electrical remodeling with impaired impulse conduction and action potential derangements. Targeted sequencing of human patients with ACM identified 2 rare splicing variants classified as likely pathogenic were in 2 unrelated individuals with ACM from a cohort of 59 patients with ACM. Conclusions The Sorbs2 knockout mouse manifests several key features reminiscent of human ACM. Although the candidacy of SORBS2 as a new ACM‐susceptibility gene is supported by preliminary human genetics study, future validation in larger cohorts with ACM is needed.

Background Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy‐related death. SUDEP shares many features with sudden cardiac death and sudden unexplained death in the young and may have a similar genetic contribution. We aim to systematically review the literature on the genetics of SUDEP. Methods and Results PubMed, MEDLINE Epub Ahead of Print, Ovid Medline In‐Process & Other Non‐Indexed Citations, MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and Scopus were searched through April 4, 2017. English language human studies analyzing SUDEP for known sudden death, ion channel and arrhythmia‐related pathogenic variants, novel variant discovery, and copy number variant analyses were included. Aggregate descriptive statistics were generated; data were insufficient for meta‐analysis. A total of 8 studies with 161 unique individuals were included; mean was age 29.0 (±SD 14.2) years; 61% males; ECG data were reported in 7.5% of cases; 50.7% were found prone and 58% of deaths were nocturnal. Cause included all types of epilepsy. Antemortem diagnosis of Dravet syndrome and autism (with duplication of chromosome 15) was associated with 11% and 9% of cases. The most frequently detected known pathogenic variants at postmortem were in Na+ and K+ ion channel subunits, as were novel potentially pathogenic variants (11%). Overall, the majority of variants were of unknown significance. Analysis of copy number variant was insignificant. Conclusions SUDEP case adjudication and evaluation remains limited largely because of crucial missing data such as ECGs. The most frequent pathogenic/likely pathogenic variants identified by molecular autopsy are in ion channel or arrhythmia‐related genes, with an ≈11% discovery rate. Comprehensive postmortem examination should include examination of the heart and brain by specialized pathologists and blood storage.

It is believed that mutations in desmosomal adhesion complex protein plakophilin 2 (PKP2) cause arrhythmia due to loss of cell-cell communication. Here the authors show that PKP2 controls the expression of proteins involved in calcium cycling in adult mouse hearts, and that lack of PKP2 can cause arrhythmia in a structurally normal heart.

Summary: Junctophilin-2 (JPH2) is a structural calcium (Ca2+) handling protein, which approximates the cardiomyocyte transverse tubules (TTs) to the sarcoplasmic reticulum. This facilitates communication of the voltage-gated Ca2+ channel and the ryanodine receptor RyR2. A human patient with hypertrophic cardiomyopathy was positive for a JPH2 mutation substituting alanine-405âlocated within the alpha helix domainâwith a serine (A405S). Using a novel mouse echocardiography plane, we found that mice bearing this JPH2 mutation developed increased subvalvular septal thickness. Cardiomyocytes from the septa of these mice displayed irregular TTs and abnormal Ca2+ handling including increased SERCA activity. Key Words: calcium, hypertrophic cardiomyopathy, junctophilin-2, magnetic resonance imaging

Background: Bileaflet mitral valve prolapse (biMVP) is associated with frequent ventricular ectopy (VE) and malignant ventricular arrhythmia. We examined the effect of mitral valve (MV) surgery on VE burden in biMVP patients. Methods: We included 32 consecutive patients undergoing MV surgery for mitral regurgitation secondary to biMVP between 1993 and 2012 at Mayo Clinic who had available pre- and post-operative Holter monitoring data. Characteristics of patients with a significant reduction in postoperative VE (group A, defined as >10% reduction in VE burden compared to baseline) were compared with the rest of study patients (group B). Results: In the overall cohort, VE burden was unchanged after the surgery (41 interquartile range [16, 196] pre-surgery vs. 40 interquartile range [5186] beats/hour [bph] post-surgery; P = 0.34). However, in 17 patients (53.1%), VE burden decreased by at least 10% after the surgery. These patients (group A) were younger than the group B (59 ± 15 vs. 68 ± 7 years; P = 0.04). Other characteristics including pre- and postoperative left ventricular function and size were similar in both groups. Age

A 16-year-old female with ventricular dysfunction and frequent ventricular arrhythmia presented with a cardioembolic stroke. Prior electrophysiology study and ablation was performed for ventricular tachycardia (VT). For remaining ventricular ectopy, the patient was maintained on carvedilol and mexiletine. After one year on this regimen, she presented with an acute stroke. Transesophageal echocardiography revealed no evidence of an intracardiac or ventricular thrombus but demonstrated markedly decreased left atrial appendage (LAA) flow velocity worsened during frequent premature ventricular contractions (PVC). In the absence of atrial fibrillation (AF), the LAA dysfunction was considered secondary to the frequent PVCs and was thought to be the underlying cause for the stroke. We present this case to highlight a potential under recognized association between LAA dysfunction and ventricular arrhythmia, similar to that observed with atrioventricular dyssynchronous pacing.

BackgroundHyper‐ and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood‐free method for tracking potassium would be an important clinical advance. Methods and ResultsTwo groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high‐resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single‐channel ECG. In addition, by analyzing the entire development group's first‐visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). ConclusionsThe signal‐processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost‐effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

The SNTA1-encoded α1-syntrophin (SNTA1) missense mutation, p.A257G, causes long QT syndrome (LQTS) by pathogenic accentuation of Nav1.5’s sodium current (INa). Subsequently, we found p.A257G in combination with the SNTA1 polymorphism, p.P74L in 4 victims of sudden infant death syndrome (SIDS) as well as in 3 adult controls. We hypothesized that p.P74L-SNTA1 could functionally modify the pathogenic phenotype of p.A257G-SNTA1, thus explaining its occurrence in non-LQTS populations. The SNTA1 variants p.P74L, p.A257G, and the combination variant p.P74L/p.A257G were engineered using PCR-based overlapextension and were co-expressed heterologously with SCN5A in HEK293 cells. INa was recorded using the whole-cell method. Compared to wild-type (WT), the significant increase in peak INa and window current found with p.A257G was reversed by the intragenic variant p.P74L (p.P74L/p.A257G). These results report for the first time the intragenic rescue of an LQT-associated SNTA1 mutation when found in combination with the SNTA1 polymorphism p.P74L, suggesting an ever-increasing picture of complexity in terms of genetic risk stratification for arrhythmia.