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Background: Pacemaker-dependent patients with device infection require temporary pacing while the infection is treated. External transthoracic pacing is painful and variably effective, while temporary pacing leads are susceptible to superinfection.Objective: To create a biological pacemaker delivered via venous catheters in a porcine model of complete heart block, providing a temporary alternative/adjunct to external pacing devices without additional indwelling hardware.Methods: Complete atrioventricular (AV) nodal block was induced in pigs by radiofrequency ablation after the implantation of a single-chamber electronic pacemaker to maintain a ventricular backup rate of 50 beats/min. An adenoviral vector cocktail (K(AAA) + H2), expressing dominant-negative inward rectifier potassium channel (Kir2.1AAA) and hyperpolarization-activated cation channel (HCN2) genes, was injected into the AV junctional region via a NOGA Myostar catheter advanced through the femoral vein.Results: Animals injected with K(AAA) + H2 maintained a physiologically relevant ventricular rate of 93.5 ± 7 beats/min (n = 4) compared with control animals (average rate, 59.4 ± 4 beats/min; n = 6 at day 7 postinjection; P <.05). Backup electronic pacemaker utilization decreased by almost 4-fold in the K(AAA) + H2 group compared with the control (P <.05), an effect maintained for the entire 14-day window. In contrast to the efficacy of gene delivery into the AV junctional region, open-chest, direct injection of K(AAA) + H2 (or its individual vectors) into the ventricular myocardium failed to elicit significant pacemaker activity.Conclusions: The right-sided delivery of K(AAA) + H2 to the AV junctional region provided physiologically relevant biological pacing over a 14-day period. Our approach may provide temporary, bridge-to-device pacing for the effective clearance of infection prior to the reimplantation of a definitive electronic pacemaker. [ABSTRACT FROM AUTHOR]

Background: The availability of a non-invasive test to detect and quantify interstitial and replacement fibrosis would be a useful advance for evaluation of cardiac therapies that could prevent fibrosis progression. There is an established role for magnetic resonance imaging (MRI) in the assessment of replacement fibrosis (when fibrosis replaces myocytes), but the potential for assessment of interstitial fibrosis (when amount of fibrosis increases between myocytes) has not been evaluated.Methods: A novel in vitro MRI technique was developed for comparison of gadodiamide contrast distribution volume as a measure of both kinds of myocardial fibrosis, with histologically determined myocardial collagen volume fraction, the current gold standard for quantification of myocardial fibrosis. Eight samples of human myocardium were obtained postmortem and a fast spin-echo sequence (3 Tesla) with non-slice selective inversion pulse performed before and after immersion in a gadodiamide saline solution for determination of the gadodiamide partition coefficient. T1 values were calculated from the inversion recovery signal curves. The same samples were fixed in formalin, and collagen volume fraction was determined by the picrosirius red method using a semi-automated, polarized, digital microscopy system.Results: Both gadodiamide distribution volumes as well as CVF values were significantly different in normal myocardium versus interstitial fibrosis (P = 0.001), and normal versus replacement fibrosis (P = 0.015). Moreover, there was a significant positive correlation between the two methods, across all three histological categories of myocardial fibrosis (r = 0.73; P = 0.017).Conclusion: These findings indicate an expanded potential for gadodiamide enhanced MRI as a novel, non-invasive alternative to histological evaluation, for the quantification of both interstitial and replacement myocardial fibrosis. [ABSTRACT FROM AUTHOR]

Nonautomatic focal atrial tachycardia (NAFAT) is a rare and poorly understood arrhythmia either due to microreentry or triggered mechanism. NAFAT was defined as a focal atrial tachycardia which was inducible with pacing maneuvers in the electrophysiology lab. We reviewed the charts and EP study reports of all 38 patients with NAFAT, who underwent an EP study at our center between April 1994 and September 2000. Patients' were predominantly female (n = 31, 82%), aged 11-78 years (median 46). The mean age at presentation was 31 years (range 7-71 years). None of the patients had structural heart disease or had undergone prior heart surgery. Electroanatomic mapping (EAM) was performed in 22 patients and showed no scars in the atrium. A total of 45 foci were identified (range 1-3 foci/patient). Anatomically NAFAT foci were predominantly right atrial (n = 35) rather than left (n = 10). The NAFAT cycle length ranged from 270 to 490 (mean +/- SD; 380 +/- 69 ms) and was significantly lower in patients younger than 24 years of age. Ablation, attempted for 42 foci was successful in 33 (79%). The success rate in the EAM group was 20/25 foci (80%) compared to 13/18 (72%) in the non-EAM group. In conclusion, NAFAT is a rare arrhythmia which predominantly affects women with no other associated cardiac disease. It mainly occurs in the right atrium, affects all ages and is amenable to catheter ablation. [ABSTRACT FROM AUTHOR]

Introduction: We observed a change in the atrial activation sequence during radiofrequency (RF) energy application in patients undergoing left accessory pathway (AP) ablation. This occurred without damage to the AP and in the absence of a second AP or alternative arrhythmia mechanism. We hypothesized that block in a left atrial 'isthmus' of tissue between the mitral annulus and a left inferior pulmonary vein was responsible for these findings. Methods and Results: Electrophysiologic studies of 159 patients who underwent RF ablation of a left free-wall AP from 1995 to 1999 were reviewed. All studies with intra-atrial conduction block resulting from RF energy delivery were identified. Fluoroscopic catheter positions were reviewed. Intra-atrial conduction block was observed following RF delivery in 11 cases (6.9%). This was evidenced by a sudden change in retrograde left atrial activation sequence despite persistent and unaffected pathway conduction. In six patients, reversal of eccentric atrial excitation during orthodromic reciprocating tachycardia falsely suggested the presence of a second (septal) AP. A multipolar coronary sinus catheter in two patients directly demonstrated conduction block along the mitral annulus during tachycardia. Conclusion: An isthmus of conductive tissue is present in the low lateral left atrium of some individuals. Awareness of this structure may avoid misinterpretation of the electrogram during left AP ablation and may be useful in future therapies of atypical atrial flutter and fibrillation. [ABSTRACT FROM AUTHOR]

Aims: The concept of "atrial cardiomyopathy" (AtCM) had been percolating through the literature since its first mention in 1972. Since then, publications using the term were sporadic until the decision was made to convene an expert working group with representation from four multinational arrhythmia organizations to prepare a consensus document on atrial cardiomyopathy in 2016 (EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: definition, characterization, and clinical implication). Subsequently, publications on AtCM have increased progressively., Methods and Results: The present consensus document elaborates the 2016 AtCM document further to implement a simple AtCM staging system (AtCM stages 1-3) by integrating biomarkers, atrial geometry, and electrophysiological changes. However, the proposed AtCM staging needs clinical validation. Importantly, it is clearly stated that the presence of AtCM might serve as a substrate for the development of atrial fibrillation (AF) and AF may accelerates AtCM substantially, but AtCM per se needs to be viewed as a separate entity., Conclusion: Thus, the present document serves as a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS) to contribute to the evolution of the AtCM concept., Competing Interests: Conflict of interest: L.M.: (2022) Direct personal payment from healthcare industry: speaker fees, honoraria, consultancy, advisory board fees, investigator, committee member, etc. Biosense Webster: Atrial Fibrillation (AF); Boston Scientific, Medtronic, Abbott Medical: Atrial Fibrillation (AF), Device Therapy. Research funding from healthcare industry under your direct/personal responsibility (to department or institution). Johnson & Johnson: Research projects, PI; Boston Scientific, Medtronic, Biotronik, Abbott Medical: Research projects, PI., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Late potential (LP) elimination has been proposed as a surrogate endpoint for scar-related ventricular tachycardia (VT) ablation procedures. The characteristics, distribution, and predictors of persistent late potentials (pLPs) after ablation have not been studied., Objective: The purpose of this study was to characterize the spatial distribution and features of pLP after catheter ablation of VT substrate with high-resolution mapping., Methods: Cases of scar-related VT ablation with adequate pre- and postablation electroanatomic maps (EAMs) acquired exclusively using a high-density grid catheter were reviewed from 2021 to 2023., Results: A total of 62 EAMs (pre- and postablation) from 31 cases using a high-density grid catheter were reviewed. pLPs were observed in 19 cases (61%) after ablation. New LP, spatially distinct from preablation LP, at the periphery of the ablation area comprised the majority of pLPs (16/19 [84%]). Isolated pLPs were more prevalent than fractionated pLPs, with a median amplitude of 0.26 mV (0.09-0.59 mV). The presence of pLP was associated with a significantly lower left ventricular ejection fraction (LVEF) and septal ablation but not low voltage, LP, or ablation area compared to absence of pLP (22.8% ± 7.8% vs 31.5% ± 8.0%, P = .008 for LVEF; 83% vs 44%, P = .033 for septal ablation)., Conclusion: Formation of spatially distinct new LP after targeted VT ablation is common, especially in patients with lower LVEF and septal substrate independent of ablation burden. This finding highlights the limitations of complete LP elimination as an endpoint to VT ablation procedures., Competing Interests: Disclosures Shreel Joshi is an employee of Abbott Laboratories, manufacturer of the mapping system and catheters used in this study. All other authors have no conflicts to disclose., (Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Survival after out-of-hospital cardiac arrest (OHCA) remains low, although the number of survivors is increasing, and survivors are living longer. With increasing long-term survival, there is a need to understand health-related quality of life (HRQoL) measures. Although there are current recommendations for measuring HRQoL in OHCA survivors, there is significant heterogeneity in assessment timing and the measurement tools used to quantify HRQoL outcomes, making the interpretation and comparison of HRQoL difficult. Identifying groups of survivors of OHCA with poor HRQoL measures could be used for targeted intervention studies. Sex differences in OHCA resuscitation characteristics, post-cardiac arrest treatment, and short-term survival outcomes are well-documented, although variability in study methods and statistical adjustments appear to affect study results and conclusions. It is unclear whether sex differences exist in HRQoL among OHCA survivors and if study methods and statistical adjustment for patient characteristics or arrest circumstances impact the results. In this narrative review article, we provide an overview of the assessment of HRQoL and the main domains of HRQoL. We summarize the literature regarding sex differences in HRQoL in OHCA survivors. Few multivariable-adjusted studies reported HRQoL sex differences and there was significant heterogeneity in study size, timing of assessment, and domains measured and reported. What is reported suggests females have worse HRQoL than males, especially in the domains of physical function and mental health, but results should be interpreted with caution. Lastly, we discuss the challenges of a non-uniform approach to measurement and future directions for assessing and improving HRQoL in OHCA survivors., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Aims: Ablation of monomorphic ventricular tachycardia (MMVT) has been shown to reduce shock frequency and improve survival. We aimed to compare cause-specific risk factors for MMVT and polymorphic ventricular tachycardia (PVT)/ventricular fibrillation (VF) and to develop predictive models., Methods and Results: The multicentre retrospective cohort study included 2668 patients (age 63.1 ± 13.0 years; 23% female; 78% white; 43% non-ischaemic cardiomyopathy; left ventricular ejection fraction 28.2 ± 11.1%). Cox models were adjusted for demographic characteristics, heart failure severity and treatment, device programming, and electrocardiogram metrics. Global electrical heterogeneity was measured by spatial QRS-T angle (QRSTa), spatial ventricular gradient elevation (SVGel), azimuth, magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). We compared the out-of-sample performance of the lasso and elastic net for Cox proportional hazards and the Fine-Gray competing risk model. During a median follow-up of 4 years, 359 patients experienced their first sustained MMVT with appropriate implantable cardioverter-defibrillator (ICD) therapy, and 129 patients had their first PVT/VF with appropriate ICD shock. The risk of MMVT was associated with wider QRSTa [hazard ratio (HR) 1.16; 95% confidence interval (CI) 1.01-1.34], larger SVGel (HR 1.17; 95% CI 1.05-1.30), and smaller SVGmag (HR 0.74; 95% CI 0.63-0.86) and SAIQRST (HR 0.84; 95% CI 0.71-0.99). The best-performing 3-year competing risk Fine-Gray model for MMVT [time-dependent area under the receiver operating characteristic curve (ROC(t)AUC) 0.728; 95% CI 0.668-0.788] identified high-risk (> 50%) patients with 75% sensitivity and 65% specificity, and PVT/VF prediction model had ROC(t)AUC 0.915 (95% CI 0.868-0.962), both satisfactory calibration., Conclusion: We developed and validated models to predict the competing risks of MMVT or PVT/VF that could inform procedural planning and future randomized controlled trials of prophylactic ventricular tachycardia ablation., Clinical Trial Registration: URL:www.clinicaltrials.gov Unique identifier:NCT03210883., Competing Interests: Conflict of interest: J.W.W. was on the advisory board for Heartcor Solutions for work unrelated to this publication. S.M.N. reports grant support from the National Institutes of Health (R01 HL149134 and R01 HL83359), consulting from Abbott Inc., Life Signals Inc., Uptodate Inc., and TDK Inc., intellectual property owned by the University of California Regents and Stanford University. A.J.R. reports support from the NIH (K23 HL166977) and AHA (23CDA933663). All remaining authors have declared no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95-0.96), AUPRC 0.91 (0.90-0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71-0.77), AUPRC 0.19 (0.16-0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67-0.70), AUPRC 0.34 (0.31-0.36)). Performance held across patients who were women (AUC 0.76 (0.72-0.81)), older than 65 years (0.73 (0.69-0.76)), or had a CHA 2 DS 2 VASc ≥2 (0.73 (0.79-0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62-0.67)), TTE measurements (0.64 (0.62-0.67)), left atrial size (0.63 (0.62-0.64)), or CHA 2 DS 2 VASc (0.61 (0.60-0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Competing Interests: Disclosures None.

Background and Aims: Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD., Methods: The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score., Results: Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts., Conclusions: Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Conventional ECG-based algorithms could contribute to sudden cardiac death (SCD) risk stratification but demonstrate moderate predictive capabilities. Deep learning (DL) models use the entire digital signal and could potentially improve predictive power. We aimed to train and validate a 12 lead ECG-based DL algorithm for SCD risk assessment., Methods: Out-of-hospital SCD cases were prospectively ascertained in the Portland, Oregon, metro area. A total of 1,827 pre- cardiac arrest 12 lead ECGs from 1,796 SCD cases were retrospectively collected and analyzed to develop an ECG-based DL model. External validation was performed in 714 ECGs from 714 SCD cases from Ventura County, CA. Two separate control group samples were obtained from 1342 ECGs taken from 1325 individuals of which at least 50% had established coronary artery disease. The DL model was compared with a previously validated conventional 6 variable ECG risk model., Results: The DL model achieves an AUROC of 0.889 (95% CI 0.861-0.917) for the detection of SCD cases vs. controls in the internal held-out test dataset, and is successfully validated in external SCD cases with an AUROC of 0.820 (0.794-0.847). The DL model performs significantly better than the conventional ECG model that achieves an AUROC of 0.712 (0.668-0.756) in the internal and 0.743 (0.711-0.775) in the external cohort., Conclusions: An ECG-based DL model distinguishes SCD cases from controls with improved accuracy and performs better than a conventional ECG risk model. Further detailed investigation is warranted to evaluate how the DL model could contribute to improved SCD risk stratification., (© 2024. The Author(s).)

Background: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor., Methods: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is zero, the true SCA initial rhythm is recorded. The internal cohort consisted of 421 emergency medical services-witnessed out-of-hospital SCAs with PEA or VF as the initial rhythm in the Portland, Oregon metropolitan area. External validation was performed in 220 emergency medical services-witnessed SCAs from Ventura, CA., Results: In the internal cohort, the artificial intelligence model achieved an area under the receiver operating characteristic curve of 0.68 (95% CI, 0.61-0.76). Model performance was similar in the external cohort, achieving an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.59-0.84). Anemia, older age, increased weight, and dyspnea as a warning symptom were the most important features of PEA-SCA; younger age, chest pain as a warning symptom and established coronary artery disease were important features associated with VF., Conclusions: The artificial intelligence model identified novel features of PEA-SCA, differentiated from VF-SCA and was successfully replicated in an external cohort. These findings enhance the mechanistic understanding of PEA-SCA with potential implications for developing novel management strategies., Competing Interests: Disclosures None.

Background: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing., Methods: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems., Findings: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81])., Interpretation: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications., Funding: National Heart, Lung, and Blood Institute., Competing Interests: Declaration of interests DO reports support from the National Institute of Health (NIH; NHLBI R00HL157421) and Alexion, and consulting or honoraria for lectures from EchoIQ, Ultromics, Pfizer, InVision, the Korean Society of Echo, and the Japanese Society of Echo. JWH reports funding from the National Science Foundation (DGE-1656518). PE reports research support from the NIH (T32HL007854-21) and serves on the American College of Cardiology Innovation Council. BC reports consulting from Alnylam, Cardurion, Corvia, CVRX, Cytokinetics, Intellia, and Rocket. TP reports stock in Abbot and Baxter, and research support from the American Heart Association, Eido, Pfizer, Edwards, and the New York Academy of Medicine. JHC reports research funding from NIH/National Institute of Aging (AI17812101), NIH/National Institute on Drug Abuse (UG1DA015815-CTN-0136), AIMI-HAI Partnership, Doris Duke Charitable Foundation (20211260), Google (SPO136094), American Heart Association, and Clinical and Translational Sciences Awards Program by the National Center for Advancing Translational Sciences (R56LM013365); is a co-founder of Reaction Explorer; and receives consulting fees from Sutton Pierce and Younker Hyde MacFarlane. MP reports research support from the NIH (HL136390), patents for ECG-based cardiac arrhythmia detection (WO2014205310A3), and consulting fees from Apple, Biotronik, Boston Scientific, QALY, Johnson and Johnson, and Bristol Myers Squibb. CMA reports support from NIH (HL165840), consulting fees from Medtronic, Novartis, Illumina, and Medtronic, and participation in advisory boards for Boston Scientific, Medtronic, and Element Science; and is a trustee on the board for the Heart Rhythm Society. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND license. Published by Elsevier Ltd.. All rights reserved.)

The discovery of zinc fingers and homeoboxes (ZHX) transcriptional factors and the upregulation of hyposialylated angiopoietin-like 4 (ANGPTL4) in podocytes have been crucial in explaining the cardinal manifestations of human minimal change nephrotic syndrome (MCNS). Recently, uncovered genomic defects upstream of ZHX2 induce a ZHX2 hypomorph state that makes podocytes inherently susceptible to mild cytokine storms resulting from a common cold. In ZHX2 hypomorph podocytes, ZHX proteins are redistributed away from normal transmembrane partners like aminopeptidase A (APA) toward alternative binding partners like IL-4Rα. During disease relapse, high plasma soluble IL-4Rα (sIL-4Rα) associated with chronic atopy complements the cytokine milieu of a common cold to displace ZHX1 from podocyte transmembrane IL-4Rα toward the podocyte nucleus. Nuclear ZHX1 induces severe upregulation of ANGPTL4 , resulting in incomplete sialylation of part of the ANGPTL4 protein, secretion of hyposialylated ANGPTL4, and hyposialylation-related injury in the glomerulus. This pattern of injury induces many of the classic manifestations of human minimal change disease (MCD), including massive and selective proteinuria, podocyte foot process effacement, and loss of glomerular basement membrane charge. Administration of glucocorticoids reduces ANGPTL4 upregulation, which reduces hyposialylation injury to improve the clinical phenotype. Improving sialylation of podocyte-secreted ANGPTL4 also reduces proteinuria and improves experimental MCD. Neutralizing circulating TNF-α, IL-6, or sIL-4Rα after the induction of the cytokine storm in Zhx2 hypomorph mice reduces albuminuria, suggesting potential new therapeutic targets for clinical trials to prevent MCD relapse. These studies collectively lay to rest prior suggestions of a role of single cytokines or soluble proteins in triggering MCD relapse.

Background: Sudden cardiac arrest is a global public health problem with a mortality rate of more than 90%. Prearrest warning symptoms could be harnessed using digital technology to potentially improve survival outcomes. We aimed to estimate the strength of association between symptoms and imminent sudden cardiac arrest., Methods: We conducted a case-control study of individuals with sudden cardiac arrest and participants without sudden cardiac arrest who had similar symptoms identified from two US community-based studies of patients with sudden cardiac arrest in California state, USA (discovery population; the Ventura Prediction of Sudden Death in Multi-Ethnic Communities [PRESTO] study), and Oregon state, USA (replication population; the Oregon Sudden Unexpected Death Study [SUDS]). Participant data were obtained from emergency medical services reports for people aged 18-85 years with witnessed sudden cardiac arrest (between Feb 1, 2015, and Jan 31, 2021) and an inclusion symptom. Data were also obtained from corresponding control populations without sudden cardiac arrest who were attended by emergency medical services for similar symptoms (between Jan 1 and Dec 31, 2019). We evaluated the association of symptoms with sudden cardiac arrest in the discovery population and validated our results in the replication population by use of logistic regression models., Findings: We identified 1672 individuals with sudden cardiac arrest from the PRESTO study, of whom 411 patients (mean age 65·7 [SD 12·4] years; 125 women and 286 men) were included in the analysis for the discovery population. From a total of 76 734 calls to emergency medical services, 1171 patients (mean age 61·8 [SD 17·3] years; 643 women, 514 men, and 14 participants without data for sex) were included in the control group. Patients with sudden cardiac arrest were more likely to have dyspnoea (168 [41%] of 411 vs 262 [22%] of 1171; p<0·0001), chest pain (136 [33%] vs 296 [25%]; p=0·0022), diaphoresis (50 [12%] vs 90 [8%]; p=0·0059), and seizure-like activity (43 [11%] vs 77 [7%], p=0·011). Symptom frequencies and patterns differed significantly by sex. Among men, chest pain (odds ratio [OR] 2·2, 95% CI 1·6-3·0), dyspnoea (2·2, 1·6-3·0), and diaphoresis (1·7, 1·1-2·7) were significantly associated with sudden cardiac arrest, whereas among women, only dyspnoea was significantly associated with sudden cardiac arrest (2·9, 1·9-4·3). 427 patients with sudden cardiac arrest (mean age 62·2 [SD 13·5]; 122 women and 305 men) were included in the analysis for the replication population and 1238 patients (mean age 59·3 [16·5] years; 689 women, 548 men, and one participant missing data for sex) were included in the control group. Findings were mostly consistent in the replication population; however, notable differences included that, among men, diaphoresis was not associated with sudden cardiac arrest and chest pain was associated with sudden cardiac arrest only in the sex-stratified multivariable analysis., Interpretation: The prevalence of warning symptoms was sex-specific and differed significantly between patients with sudden cardiac arrest and controls. Warning symptoms hold promise for prediction of imminent sudden cardiac arrest but might need to be augmented with additional features to maximise predictive power., Funding: US National Heart Lung and Blood Institute., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background Out-of-hospital sudden cardiac arrest (SCA) is a leading cause of mortality, making prevention of SCA a public health priority. No studies have evaluated predictors of SCA risk among Hispanic or Latino individuals in the United States. Methods and Results In this case-control study, adult SCA cases ages 18-85 (n=1,468) were ascertained in the ongoing Ventura Pre diction of S udden Death in Mul t i-Ethnic C o mmunities (PRESTO) study (2015-2021) in Ventura County, California. Control subjects were selected from 3033 Hispanic or Latino participants who completed Visit 2 examinations (2014-2017) at the San Diego site of the HCHS/SOL (Hispanic Community Health Survey/Study of Latinos). We used logistic regression to evaluate the association of clinical factors with SCA. Among Hispanic or Latino SCA cases (n=295) and frequency-matched HCHS/SOL controls (n=590) (70.2% men with mean age 63.4 and 61.2 years, respectively), the following clinical variables were associated with SCA in models adjusted for age, sex, and other clinical variables: chronic kidney disease (odds ratio [OR], 7.3 [95% CI, 3.8-14.3]), heavy drinking (OR, 4.5 [95% CI, 2.3-9.0]), stroke (OR, 3.1 [95% CI, 1.2-8.0]), atrial fibrillation (OR, 3.7 [95% CI, 1.7-7.9]), coronary artery disease (OR, 2.9 [95% CI, 1.5-5.9]), heart failure (OR, 2.5 [95% CI, 1.2-5.1]), and diabetes (OR, 1.5 [95% CI, 1.0-2.3]). Conclusions In this first population-based study, to our knowledge, of SCA risk predictors among Hispanic or Latino adults, chronic kidney disease was the strongest risk factor for SCA, and established cardiovascular disease was also important. Early identification and management of chronic kidney disease may reduce SCA risk among Hispanic or Latino individuals, in addition to prevention and treatment of cardiovascular disease.

Study Objective: The proportion of nonshockable sudden cardiac arrests (pulseless electrical activity and asystole) continues to rise. Survival is lower than shockable (ventricular fibrillation [VF]) sudden cardiac arrests, but there is little community-based information on temporal trends in the incidence and survival from sudden cardiac arrests based on presenting rhythms. We investigated community-based temporal trends in sudden cardiac arrest incidence and survival by presenting rhythm., Methods: We prospectively evaluated the incidence of each presenting sudden cardiac arrest rhythm and survival outcomes for out-of-hospital events in the Portland, Oregon metro area (population of approximately 1 million, 2002 to 2017). We limited inclusion to cases of likely cardiac cause with resuscitation attempted by emergency medical services., Results: Out of 3,723 overall sudden cardiac arrest cases, 908 (24%) presented with pulseless electrical activity, 1,513 (41%) with VF, and 1,302 (35%) with asystole. The incidence of pulseless electrical activity-sudden cardiac arrest remained stable over 4-year periods (9.6/100,000 in 2002 to 2005, 7.4/100,000 in 2006 to 2009, 5.7/100,000 in 2010 to 2013, and 8.3/100,000 in 2014 to 2017; unadjusted beta [β] -0.56; 95% confidence interval [CI], -3.98 to 2.85). The incidence of VF-sudden cardiac arrests decreased over time (14.6/100,000 in 2002 to 2005, 13.4/100,000 in 2006 to 2009, 12.0/100,000 in 2010 to 2013, and 11.6/100,000 in 2014 to 2017; unadjusted β -1.05; 95% CI, -1.68 to -0.42) and asystole-sudden cardiac arrests (8.6/100,000 in 2002 to 2005, 9.0/100,000 in 2006 to 2009, 10.3/100,000 in 2010 to 2013, and 15.7/100,000 in 2014 to 2017; unadjusted β 2.25; 95% CI -1.24 to 5.73) did not change significantly over time. Survival increased over time for pulseless electrical activity-sudden cardiac arrests (5.7%, 4.3%, 9.6%, 13.6%; unadjusted β 2.8%; 95% CI 1.3 to 4.4) and VF-sudden cardiac arrests (27.5%, 29.8%, 37.9%, 36.6%; unadjusted β 3.5%; 95% CI 1.4 to 5.6), but not for asystole-sudden cardiac arrests (1.7%, 1.6%, 4.0%, 2.4%; unadjusted β 0.3%; 95% CI, -0.4 to 1.1). Enhancements in the emergency medical services system's pulseless electrical activity-sudden cardiac arrest management were temporally associated with the increasing pulseless electrical activity survival rates., Conclusions: Over a 16-year period, the incidence of VF/ventricular tachycardia decreased over time, but pulseless electrical activity incidence remained stable. Survival from both VF-sudden cardiac arrests and pulseless electrical activity-sudden cardiac arrests increased over time with a more than 2-fold increase for pulseless electrical activity-sudden cardiac arrests., (Copyright © 2023 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Nonischemic cardiomyopathy (NICM) is common and patients are at significant risk for early mortality secondary to ventricular arrhythmias. Current guidelines recommend implantable cardioverter-defibrillator (ICD) therapy to decrease sudden cardiac death (SCD) in patients with heart failure and reduced left ventricular ejection fraction. However, in randomized clinical trials comprised solely of patients with NICM, primary prevention ICDs did not confer significant mortality benefit. Moreover, left ventricular ejection fraction has limited sensitivity and specificity for predicting SCD. Therefore, precise risk stratification algorithms are needed to define those at the highest risk of SCD. This review examines mechanisms of sudden arrhythmic death in patients with NICM, discusses the role of ICD therapy and treatment of heart failure for prevention of SCD in patients with NICM, examines the role of cardiac magnetic resonance imaging and computational modeling for SCD risk stratification, and proposes new strategies to guide future clinical trials on SCD risk assessment in patients with NICM., Competing Interests: Funding Support and Author Disclosures Dr Chrispin has received consulting fees from Biosense Webster; and has received honorarium from Abbott. Dr Navara has equity ownership in SafeBeat Rx. Dr Torbe has ownership of Boston Scientific stocks. Dr Cheung has received consulting fees from Abbott, Biotronik, and Boston Scientific; has received research grant support from Boston Scientific; and has received fellowship grant support from Abbott, Biosense, Biotronik, Boston Scientific, and Medtronic. Dr Lakdawala has received research support from Pfizer Inc; and has received consulting fees from Pfizer Inc, Bristol Myers Squibb, Cytokinetics, and Tenaya Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Disclosures None.

Background: Sports activity among older adults is rising, but there is a lack of community-based data on sports-related sudden cardiac arrest (SrSCA) in the elderly., Objectives: In this study, the authors investigated the prevalence and characteristics of SrSCA among subjects ≥65 years of age in a large U.S., Methods: All out-of-hospital sudden cardiac arrests (SCAs) were prospectively ascertained in the Portland, Oregon, USA, metro area (2002-2017), and Ventura County, California, USA (2015-2021) (catchment population ∼1.85 million). Detailed information was obtained for SCA warning symptoms, circumstances, and lifetime clinical history. Subjects with SCA during or within 1 hour of cessation of sports activity were categorized as SrSCA., Results: Of 4,078 SCAs among subjects ≥65 years of age, 77 were SrSCA (1.9%; 91% men). The crude annual SrSCA incidence among age ≥65 years was 3.29/100,000 in Portland and 2.10/100,000 in Ventura. The most common associated activities were cycling, gym activity, and running. SrSCA cases had lower burden of cardiovascular risk factors (P = 0.03) as well as comorbidities (P < 0.005) compared with non-SrSCA. Based on conservative estimates of community residents ≥65 years of age who participate in sports activity, the SrSCA incidence was 28.9/100,000 sport participation years and 18.4/100,000 sport participation years in Portland and Ventura, respectively. Crude survival to hospital discharge rate was higher in SrSCA, but the difference was nonsignificant after adjustment for confounding factors., Conclusions: Among free-living community residents age ≥65 years, SrSCA is uncommon, predominantly occurs in men, and is associated with lower disease burden than non-SrSCA. These results suggest that the risk of SrSCA is low, and probably outweighed by the high benefit of exercise., Competing Interests: Funding Support and Author Disclosures This work is funded, in part, by National Institutes of Health, National Heart, Lung, and Blood Institute grants R01HL145675 and R01HL147358 (to Dr Chugh). Dr Holmstrom was supported by the Sigrid Juselius Foundation, The Finnish Cultural Foundation, Instrumentarium Science Foundation, Orion Research Foundation, and Paavo Nurmi Foundation. Dr Chugh holds the Pauline and Harold Price Chair in Cardiac Electrophysiology at Cedars-Sinai. The funding sources had no involvement in the preparation of this work or the decision to submit for publication. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Early during the coronavirus disease 2019 (COVID-19) pandemic, higher sudden cardiac arrest (SCA) incidence and lower survival rates were reported. However, ongoing effects on SCA during the evolving pandemic have not been evaluated., Objective: The purpose of this study was to assess the impact of COVID-19 on SCA during 2 years of the pandemic., Methods: In a prospective study of Ventura County, California (2020 population 843,843; 44.1% Hispanic), we compared SCA incidence and outcomes during the first 2 years of the COVID-19 pandemic to the prior 4 years., Results: Of 2222 out-of-hospital SCA cases identified, 907 occurred during the pandemic (March 2020 to February 2022) and 1315 occurred prepandemic (March 2016 to February 2020). Overall age-standardized annual SCA incidence increased from 39 per 100,000 (95% confidence [CI] 37-41) prepandemic to 54 per 100,000 (95% CI 50-57; P <.001) during the pandemic. Among Hispanics, incidence increased by 77%, from 38 per 100,000 (95% CI 34-43) to 68 per 100,000 (95% CI 60-76; P <.001). Among non-Hispanics, incidence increased by 26%, from 39 per 100,000 (95% CI 37-42; P <.001) to 50 per 100,000 (95% CI 46-54). SCA incidence rates closely tracked COVID-19 infection rates. During the pandemic, SCA survival was significantly reduced (15% to 10%; P <.001), and Hispanics were less likely than non-Hispanics to receive bystander cardiopulmonary resuscitation (45% vs 55%; P = .005) and to present with shockable rhythm (15% vs 24%; P = .003)., Conclusion: Overall SCA rates remained consistently higher and survival outcomes consistently lower, with exaggerated effects during COVID infection peaks. This longer evaluation uncovered higher increases in SCA incidence among Hispanics, with worse resuscitation profiles. Potential ethnicity-specific barriers to acute SCA care warrant urgent evaluation and intervention., (Copyright © 2023 Heart Rhythm Society. All rights reserved.)

Sudden cardiac arrest due to lethal ventricular arrhythmias is a major cause of mortality worldwide and results in more years of potential life lost than any individual cancer. Most of these sudden cardiac arrest events occur unexpectedly in individuals who have not been identified as high-risk due to the inadequacy of current risk stratification tools. Artificial intelligence tools are increasingly being used to solve complex problems and are poised to help with this major unmet need in the field of clinical electrophysiology. By leveraging large and detailed datasets, artificial intelligence-based prediction models have the potential to enhance the risk stratification of lethal ventricular arrhythmias. This review presents a synthesis of the published literature and a discussion of future directions in this field., Competing Interests: Disclosure: LH is a postdoctoral fellow visiting from the Research Unit of Internal Medicine, Medical Research Center Oulu, the University of Oulu and Oulu University Hospital, Oulu, Finland; and receives funding from the Sigrid Juselius Foundation, the Finnish Cultural Foundation, Instrumentarium Science Foundation, Orion Research Foundation and Paavo Nurmi Foundation. DO has received grants from Alexion, consulting fees from EchoIQ, InVision and Pfizer, is on the ASE AI Taskforce, and has stocks in InVision. DD has received grants from the National Institutes of Health and royalties from Cedars Sinai Medical Center. All other authors have no conflicts of interest to declare., (Copyright © 2023, Radcliffe Cardiology.)

Background: Undiagnosed chronic kidney disease (CKD) is a common and usually asymptomatic disorder that causes a high burden of morbidity and early mortality worldwide. We developed a deep learning model for CKD screening from routinely acquired ECGs., Methods: We collected data from a primary cohort with 111,370 patients which had 247,655 ECGs between 2005 and 2019. Using this data, we developed, trained, validated, and tested a deep learning model to predict whether an ECG was taken within one year of the patient receiving a CKD diagnosis. The model was additionally validated using an external cohort from another healthcare system which had 312,145 patients with 896,620 ECGs between 2005 and 2018., Results: Using 12-lead ECG waveforms, our deep learning algorithm achieves discrimination for CKD of any stage with an AUC of 0.767 (95% CI 0.760-0.773) in a held-out test set and an AUC of 0.709 (0.708-0.710) in the external cohort. Our 12-lead ECG-based model performance is consistent across the severity of CKD, with an AUC of 0.753 (0.735-0.770) for mild CKD, AUC of 0.759 (0.750-0.767) for moderate-severe CKD, and an AUC of 0.783 (0.773-0.793) for ESRD. In patients under 60 years old, our model achieves high performance in detecting any stage CKD with both 12-lead (AUC 0.843 [0.836-0.852]) and 1-lead ECG waveform (0.824 [0.815-0.832])., Conclusions: Our deep learning algorithm is able to detect CKD using ECG waveforms, with stronger performance in younger patients and more severe CKD stages. This ECG algorithm has the potential to augment screening for CKD., (© 2023. The Author(s).)

Viral illnesses like SARS-CoV-2 have pathologic effects on nonrespiratory organs in the absence of direct viral infection. We injected mice with cocktails of rodent equivalents of human cytokine storms resulting from SARS-CoV-2/COVID-19 or rhinovirus common cold infection. At low doses, COVID-19 cocktails induced glomerular injury and albuminuria in zinc fingers and homeoboxes 2 (Zhx2) hypomorph and Zhx2+/+ mice to mimic COVID-19-related proteinuria. Common Cold cocktail induced albuminuria selectively in Zhx2 hypomorph mice to model relapse of minimal change disease, which improved after depletion of TNF-α, soluble IL-4Rα, or IL-6. The Zhx2 hypomorph state increased cell membrane to nuclear migration of podocyte ZHX proteins in vivo (both cocktails) and lowered phosphorylated STAT6 activation (COVID-19 cocktail) in vitro. At higher doses, COVID-19 cocktails induced acute heart injury, myocarditis, pericarditis, acute liver injury, acute kidney injury, and high mortality in Zhx2+/+ mice, whereas Zhx2 hypomorph mice were relatively protected, due in part to early, asynchronous activation of STAT5 and STAT6 pathways in these organs. Dual depletion of cytokine combinations of TNF-α with IL-2, IL-13, or IL-4 in Zhx2+/+ mice reduced multiorgan injury and eliminated mortality. Using genome sequencing and CRISPR/Cas9, an insertion upstream of ZHX2 was identified as a cause of the human ZHX2 hypomorph state.

Background: The identification of circulating biomarkers specific for sudden cardiac arrest (SCA) could enhance risk prediction. Of particular interest are biomarkers specific to SCA, independent of coronary artery disease (CAD)., Objective: The purpose of this study was to identify biomarkers of SCA obtained close to the SCA event., Methods: Twenty cases (survivors of SCA) and 40 age- and sex-matched controls were compared, with a replication analysis of 29 cases matched to 57 controls. A secondary analysis compared 20 SCA cases to 20 controls with CAD. Blood samples were obtained from SCA survivors at a median of 11 months after the SCA event. Proteins were analyzed on a mass spectrometer using data-independent acquisition; a subset of cytokines were analyzed using immunoassays; and 1153 lipids (13 classes) were analyzed. A false discovery rate P value of <.05 identified associated proteins., Results: Patients had a mean age of 58 years (range 25-87 years), and 70% were male. A total of 26 protein biomarkers associated with SCA when cases were compared with controls, of which 20 differentiated SCA from CAD. The replication analysis identified 8 of 26 biomarkers, of which 6 were not overlapping with CAD. The top identified biological processes involved the extracellular matrix, coagulation cascades, and platelet activation. Lipids in the lysophosphatidylcholine class were implicated in SCA through the CAD pathway., Conclusion: We identified a panel of novel blood biomarkers specifically associated with SCA, including several that may be involved outside the CAD pathway. These biomarkers could have mechanistic significance and the potential to enhance clinical prediction of SCA., (Copyright © 2022 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)