JACC: Clinical Electrophysiology

Background: Accurate identification of macro-reentrant atrial tachycardia (AT) circuits is critical for successful ablation but remains challenging with conventional mapping techniques. The aim of this study was to automatically detect macro-reentrant AT loops from high-density local activation time (LAT) maps. Methods: We developed an algorithm for automated detection of macro-reentrant AT circuits using LAT-derived directed graphs. Compared to previous graph-based approaches, the algorithm is designed to identify the fastest-conducting reentrant pathways and cluster them by rotational orientation (clockwise vs. counterclockwise) to distinguish single- from dual-loop circuits. The algorithm was applied retrospectively to 60 macro-reentrant scar-related AT cases mapped with CARTO or Ensite from two institutions. The results were compared with blinded expert electrophysiologist annotations of loop location and single- vs. dual-loop classification. Results: The 60 cases included 16 right atrial and 44 left atrial ATs from 51 patients. Expert review identified 57% single-loop and 43% dual-loop circuits. Compared with expert annotation, the algorithm correctly identified anatomical loop locations with 88% accuracy and correctly distinguished single- vs. dual-loop ATs in 93% of cases. Conclusion: Our LAT graph-based algorithm automatically identified single- and dual-loop macro-reentrant AT circuits. Localizing these pathways may provide insight into circuit mechanisms and help guide ablation.

BackgroundSympathetic modulation via the stellate ganglia is increasingly recognized as a contributor to ventricular arrhythmogenesis after myocardial infarction. However, the mechanisms by which autonomic remodeling interacts with chronic infarct substrates to shape arrhythmic vulnerability remain incompletely understood. ObjectivesTo test the hypothesis that left- and right-sided stellate ganglion-mediated SNS modulation differentially reshapes ventricular arrhythmic vulnerability in chronic post-infarcted substrates, and that the RVI detects changes in vulnerability beyond conventional stimulation-based inducibility. MethodsFourteen patient-specific ventricular models with chronic post-infarcted remodeling were reconstructed from imaging data. A total of 336 simulations were performed under different combinations of stellate ganglion modulation, border zone remodeling, and fibroblast density. Arrhythmic vulnerability was quantified using 3D RVI mapping during paced rhythms and compared with conventional stimulation-based inducibility outcomes. ResultsStellate ganglion modulation induced marked, regionally heterogeneous changes in repolarization timing, resulting in lower and more negative RVI values in vulnerable regions. More negative RVI values reflect increased propensity for wavefront-waveback interaction and reentry initiation. Across the cohort, stellate modulation consistently decreased RVImin, even when inducibility outcomes remained unchanged. These findings indicate that SNS modulation can create a substrate more permissive to reentry independently of whether ventricular arrhythmia is triggered during programmed stimulation. ConclusionsStellate ganglion-mediated sympathetic modulation dynamically reshapes ventricular arrhythmic vulnerability in chronic post-infarcted substrates. RVI provides a spatially resolved, vulnerability-based metric that complements inducibility testing by revealing autonomic-substrate interactions underlying arrhythmogenesis Condensed AbstractSympathetic modulation via the stellate ganglia can alter ventricular repolarization and promote arrhythmogenesis after myocardial infarction, yet clinical responses remain heterogeneous. Using 14 patient-specific post-infarction ventricular models, we simulated left- and right-sided stellate modulation across combinations of border zone remodeling and fibrosis (336 simulations). Stellate modulation induced regionally heterogeneous repolarization shortening and reduced RVI values, even when programmed stimulation inducibility remained unchanged. These findings suggest that RVI captures substrate-level vulnerability beyond binary induction testing and may improve mechanistic assessment of autonomic-substrate interactions in chronic infarct substrates.

ObjectivePulsed field ablation (PFA) relies on irreversible electroporation to create nonthermal cardiac lesions, yet real-time indicators of electroporation progression and validated lethal electric field thresholds remain limited. This study aimed to develop a bioimpedance-based metric for real-time monitoring of cardiac electroporation, evaluate the impact of myocardial anisotropy under electroporation conditions, and derive waveform-specific lethal electric field thresholds. IntroductionCurrent PFA procedures lack direct intraoperative feedback on lesion formation, and uncertainty remains regarding the role of myocardial fiber orientation in shaping electric field distributions. Because electroporation dynamically alters tissue electrical properties, monitoring these changes during treatment may improve prediction of ablation outcomes. MethodsPFA was delivered to fresh ex vivo porcine ventricular tissue using clinically relevant and energy-matched waveforms with pulse widths from 1 to 100 {micro}s. Inter-burst broadband electrical impedance spectroscopy was performed using a low-voltage diagnostic waveform to quantify burst-resolved impedance changes. Lesions were visualized using metabolic staining, then finite element models incorporating nonlinear electroporation-dependent conductivity were used to compare anisotropic and homogenized electric field distributions. Lethal electric field thresholds were estimated by fitting simulated contours to measured lesion areas and validated using uniform electric fields generated by a parallel electrode array. ResultsAcross all waveforms, impedance measurements showed a rapid initial decrease followed by stabilization, indicating early electroporation saturation. Burst-to-burst percent change in impedance slope provided a consistent, waveform-agnostic metric of electroporation progression. Lesion morphology was not systematically influenced by fiber orientation, and modeling demonstrated that electroporation-induced conductivity increases homogenized tissue anisotropy. Lethal electric field thresholds increased with decreasing pulse width, ranging from 517 {+/-} 46 V/cm (100 {micro}s) to 1405 {+/-} 55 V/cm (1 {micro}s), and were validated under uniform field conditions. ConclusionBioimpedance-assisted monitoring enables real-time assessment of cardiac electroporation, while electroporation-induced homogenization supports simplified modeling and standardized PFA treatment design.

AimsGenome-wide association studies have identified numerous cardiac transcription factors in association with atrial fibrillation. Amongst these transcription factors, the paired-like homeodomain transcription factor 2 (PITX2) is the strongest genetic risk variant associated with atrial fibrillation. However, the downstream mechanisms of PITX2 are not completely understood. Here, we explore the role of PITX2 in oxidative metabolism and stress as a unifying mechanism of arrhythmogenesis. Methods and resultsTo identify PITX2 mechanisms, we performed transcriptomic analysis in Pitx2c-deficient neonatal rat atrial myocytes. We identify oxidative phosphorylation as the top dysregulated pathway and direct transcriptional targets lie in mitochondrial electron transport chain complexes I and IV. Using the Seahorse Extracellular Flux Analyzer, we identified a functional decrease in oxidative metabolism in Pitx2c-deficient cardiomyocytes. As electron transport chain complexes I and IV may generate reactive oxygen species (ROS) under mitochondrial dysfunction, we quantified mitochondrial specific ROS using MitoSOX and observed an increase in mitochondrial specific ROS in Pitx2c-deficient cardiomyocytes. We additionally assessed spontaneous cardiomyocyte calcium cycling using Fluo-8AM and observed an increased frequency of pro-arrhythmogenic mechanisms including early and delayed afterdepolarizations as inferred through calcium traces. Further, we identified sarcomere disassembly including a potential role of PITX2 in regulating Titin, where Pitx2c-deficient cardiomyocytes display Titin mis-localization within the sarcomeres. To assess whether ROS drives these phenotypes, we treated neonatal rat atrial myocytes with N-acetylcysteine, a potent ROS scavenger, and observed decreased early and delayed afterdepolarizations, as well as restoration of Titin localization. ConclusionPITX2C maintains atrial metabolism and redox balance; the loss of PITX2C results in reduced oxidative metabolism and an elevation in oxidative stress that ramifies cardiomyocyte dysfunction. Treatment with antioxidant restores AF-associated phenotypes including abnormal calcium cycling and sarcomere disassembly in Pitx2c-deficient atrial cardiomyocytes. TRANSLATIONAL PERSPECTIVEGenetic variants close to the PITX2 gene associate most strongly with atrial fibrillation. This study reveals a mechanistic link between multiple AF-associated phenotypes and mitochondrial dysfunction with subsequent accumulation of reactive oxygen species downstream of PITX2. Importantly, metabolic therapies and reducing oxidative stress may present a potential clinical strategy to reverse and prevent functional and structural remodelling related to AF.

Background: AI-enabled electrocardiographic age (AI-ECG age) is a digital biomarker of electrophysiological cardiac health. Although cardiovascular physiology exhibits circadian organization, the circadian behavior of AI-ECG age and its structural correlates have not been defined in AF-naive individuals. Objectives: To determine whether AI-ECG age exhibits reproducible circadian patterns and whether disruption of these patterns is associated with left atrial (LA) remodeling, a marker of atrial myopathy. Methods: Continuous single-lead wearable ECGs were analyzed from two independent prospective cohorts (S-Patch [ClinicalTrials.gov: NCT05119725, registered November 2021]; Memo Patch [ClinicalTrials.gov: NCT05355948, registered May 2022]). In AF-naive participants with 48 hours of data, AI-ECG age was estimated every 10 minutes. Unsupervised clustering was used to identify intrinsic circadian trajectories. For clinical interpretability, participants were classified using a day-night difference cutoff (Age 0.6 years) as Restorative (Age >0.6) or Disrupted (Age 0.6). We assessed phenotype reproducibility and examined associations with left atrial volume index (LAVI) using multivariable regression and meta-analysis. Results: Unsupervised learning consistently identified three circadian trajectory patterns across cohorts. Under the simplified binary classification, the Restorative phenotype was observed in approximately half of the participants (47.6-50.2%). Phenotype reproducibility was moderate (Cohen's 0.518; ICC=0.51-0.54) and was not fully explained by conventional heart rate variability measures. Among participants with echocardiography (n=122), the Disrupted phenotype was associated with higher LAVI (adjusted mean difference 6.09 mL/m2; 95% CI 1.46-10.72; p=0.010) and higher odds of severe LA enlargement (adjusted OR 4.17; 95% CI 1.58?10.99; p=0.004), with negligible heterogeneity (I2=0%). Conclusions: Wearable-derived AI-ECG age exhibits circadian patterns in AF-naive individuals, with unsupervised learning identifying distinct trajectories. Attenuation of a nocturnal decline the Disrupted phenotype is associated with left atrial enlargement, independent of conventional comorbidities and static AI-ECG age metrics. These findings suggest that circadian electrophysiological aging phenotyping may capture a dimension of atrial structural vulnerability not reflected by point-in-time assessments, and support prospective studies to evaluate its clinical utility.

Cardiac arrhythmias are abnormal heart rhythms characterized by disordered electrical dynamics that impair cardiac function and pose a major global burden of morbidity and mortality. Early and accurate prediction of arrhythmic anomalies from physiological time series is crucial for effective intervention, yet remains challenging due to the nonlinear, nonstationary, and individualized nature of cardiac dynamics. Despite significant advances in machine learning-based arrhythmia detection, most existing methods operate as static classifiers on electrocardiographic signals and lack online prediction, patient-specific adaptation, and mechanistic interpretability. From a dynamical-systems perspective, arrhythmias represent qualitative regime transitions, often preceded by subtle, temporally extended deviations that are difficult to detect in real time. Here we introduce CASCADE (Chaotic Attractor Sensitivity for Cardiac Anomaly Detection), an online and personalized anomaly forecasting framework built on a special type of reservoir computing called Dynamical Systems Machine Learning (DynML). DynML employs ensembles of continuous-time nonlinear dynamical systems as chaotic reservoirs to reconstruct and forecast short-term cardiac dynamics on a beat-to-beat basis, training only a linear readout. This design enables efficient online adaptation without retraining the underlying dynamical model. Rather than relying on static beat-level classification, CASCADE identifies arrhythmic events as failures of short-term predictability, manifested as statistically significant deviations between predicted and observed dynamics relative to subject-specific baselines. Detection performance is governed by the intrinsic dynamical complexity of the reservoir, quantified by topological entropy. Reservoirs operating near critical entropy regimes optimally amplify subtle, temporally extended irregularities in heartbeat dynamics, rendering incipient arrhythmic signatures linearly separable at the readout level. Topological entropy thus serves both as a predictor of model performance and a principled control parameter for reservoir design. When evaluated on the MIT-BIH Arrhythmia dataset, CASCADE achieved consistently high F1 scores, precision, recall, and overall accuracy across diverse patient populations, demonstrating strong generalizability across clinical and real-world settings. By integrating chaotic reservoir computing, entropy-guided tuning, and online personalized forecasting, CASCADE reframes arrhythmia detection as a problem of dynamical regime transition rather than static classification. This perspective provides a scalable, interpretable, and computationally efficient framework for real-time cardiac monitoring and early-warning clinical decision support.

Background: Patients with Fontan circulation experience significant morbidity from supraventricular tachyarrhythmias (SVTs). However, the electrophysiological features of SVT and the efficacy and safety of catheter ablation in patients with Fontan circulation are poorly understood. This study aimed to elucidate the electrophysiological features of SVT and evaluate the efficacy and safety of catheter ablation in patients with Fontan circulation. Methods: Forty-nine patients (age, 29.2{+/-}10.0 years; 27 males) with functional single ventricle and Fontan circulation who had undergone electrophysiological study for SVT were retrospectively enrolled. Parameters analyzed included underlying congenital heart disease, Fontan type, conduit puncture technique, tachycardia mechanisms, tachycardia origin site, acute success rate, procedure-related complications, and recurrence. Results: Fifty-nine SVTs were induced, and 69 catheter ablations were performed. The Fontan types included atriopulmonary connection (APC, 18.4%), lateral tunnel (LT, 38.8%), and extracardiac conduit (ECC, 42.9%). Inducible tachycardias included intra-atrial reentrant tachycardia (IART, 39.0%), focal atrial tachycardia (AT, 28.8%), atrioventricular reentrant tachycardia (11.9%), atrioventricular nodal reentrant tachycardia (10.2%), and atrioventricular reciprocating tachycardia involving the twin atrioventricular nodes (10.2%). The right atrial (RA) lateral wall was the most common location of IART and focal AT. The acute success and complication rates were 73.5% and 4.1%, respectively. Recurrence rate was 34.7% during follow-up of 78.0{+/-}71.9 months. The cumulative recurrence rate was significantly lower in patients who underwent LT or ECC Fontan procedures than in those who underwent the APC Fontan procedure (P<0.001). Conclusions: Catheter ablation for SVT is effective and safe in patients who have undergone LT and ECC Fontan procedures.

BackgroundPathogenic desmin (DES) variants have been implicated in early-onset atrial disease, yet the mechanisms by which desmin dysfunction alters atrial structure and function remain unclear. Desmin anchors the cytoskeleton to the nuclear envelope (NE) through the linker of nucleoskeleton and cytoskeleton (LINC) complex, suggesting that defects in this network may drive atrial cardiomyopathy. MethodsHuman desmin wild-type (WT) and the pathogenic variants p.S13F, p.N342D, and p.R454W were stably expressed in HL-1 atrial cardiomyocytes. Desmin organization, nuclear morphology, LINC-complex integrity (nesprin-3, lamin A/C), and DNA leakage, assessed by cyclic GMP-AMP synthase (cGAS), were analyzed by confocal microscopy. Action potential duration (APD) and calcium transients (CaT) were measured optically. Human myocardium samples from DES variant carriers were analyzed for validation. Data-independent acquisition (DIA) mass spectrometry profiled atrial proteomes from desmin-network (DN) and titin variant carriers and controls. The heat-shock proteins (HSPs) inducer geranylgeranylacetone (GGA) was evaluated for rescue effects. Resultsp.N342D caused severe filament-assembly defects with prominent perinuclear aggregates, whereas p.S13F showed mixed phenotypes with frequent perinuclear aggregates, and p.R454W largely preserved filamentous networks. p.N342D and p.S13F induced nuclear deformation with disrupted nesprin-3 and lamin A/C distribution. In p.N342D and p.S13F, desmin aggregates drove focal lamin A/C accumulation, nuclear envelope (NE) rupture, DNA leakage, and increased cGAS activation. DES variants significantly shortened APD20/90 and reduced CaT amplitude, indicating pro-arrhythmic electrical remodeling. Atrial proteomics revealed a DN-specific signature enriched for cytoskeletal, NE, intermediate filament, and chaperone pathways, consistent with the structural injury observed in vitro. GGA prevented desmin aggregation and nuclear morphology changes, and mitigated APD shortening in p.N342D-expressing cardiomyocytes. Human myocardium from DES variant carriers showed concordant desmin aggregation and polarized lamin A/C distribution. ConclusionsDES variants induce a desmin-dependent atrial cardiomyopathy characterized by cytoskeletal disorganization, disruption of LINC-complex, NE rupture with DNA leakage, and pro-arrhythmic electrophysiological remodeling. These findings provide mechanistic insight into how DN variants promote atrial disease. HSPs induction by GGA partially restores structural and functional integrity, identifying a potential therapeutic approach for desmin-related atrial cardiomyopathy. Clinical perspectiveWhat is new? O_LIPathogenic DES variants induce a previously unrecognized atrial cardiomyopathy characterized by desmin aggregation, and desmin-network (DN) collapse, disruption of the linker of nucleoskeleton and cytoskeleton (LINC) complex, and nuclear envelope rupture with DNA leakage. C_LIO_LIVariants that lead to desmin aggregation (e.g., p.N342D) cause focal lamin A/C polarization, cyclic GMP-AMP synthase (cGAS) activation, and structural injury at the nuclear envelope. C_LIO_LIDES variants produce pro-arrhythmic electrical remodeling, including action potential duration shortening and impaired Ca{superscript 2} handling in HL-1 atrial cardiomyocytes. C_LIO_LIAtrial proteomics from DN variant carriers reveals enrichment of pathways related to cytoskeletal, nuclear envelope, intermediate filament, and chaperone, supporting a desmin-dependent remodeling program. C_LIO_LIThe heat-shock protein inducer geranylgeranylacetone (GGA) prevents desmin aggregation, restores nuclear morphology, and mitigates electrical and Ca{superscript 2} handling remodeling. C_LI What are the clinical implications? O_LIThese findings establish DN dysfunction as a distinct cause of atrial cardiomyopathy, providing a mechanistic basis for the association between pathogenic DES variants and atrial arrhythmias, including atrial fibrillation. C_LIO_LINuclear envelope rupture and cytosolic DNA leakage represent new mechanistic evidence which links cytoskeletal injury and atrial arrhythmogenesis. C_LIO_LIIdentifying structural vulnerability in DES variant carriers fosters awareness of genetic counseling for atrial disease, enabling early detection and risk stratification. C_LIO_LIThe protective effects of GGA suggest that restoring proteostasis may be a therapeutic strategy for desmin-related atrial cardiomyopathy and potentially other genetic atrial diseases. C_LI Novelty and significance statementO_ST_ABSNoveltyC_ST_ABSThis study identifies a desmin-dependent atrial cardiomyopathy driven by cytoskeletal aggregation, LINC-complex disruption, and nuclear envelope rupture with DNA leakage. We show that pathogenic DES variants are associated with pro-arrhythmic molecular remodeling and that human atrial proteomics confirm nuclear envelope and cytoskeletal injury as core features. Importantly, the heat-shock protein-inducer GGA rescues structural, molecular, and electrophysiological defects, revealing a modifiable pathway in desmin-mediated atrial disease. SignificanceThese findings provide the first integrated mechanistic explanation linking DN variants to atrial cardiomyopathy. By uncovering nuclear envelope rupture and cGAS activation as key drivers of atrial cardiomyopathy, this work expands the molecular framework for inherited atrial disease and highlights proteostasis enhancement as a potential therapeutic strategy for patients carrying DES and related cytoskeletal variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/26348559v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1fb0bfborg.highwire.dtl.DTLVardef@cfc00borg.highwire.dtl.DTLVardef@1493578org.highwire.dtl.DTLVardef@1556b61_HPS_FORMAT_FIGEXP M_FIG C_FIG

Class imbalance in clinical electrocardiogram (ECG) datasets limits the diagnostic sensitivity of automated arrhythmia classifiers, particularly for rare but clinically significant beat types. We propose a three-stage hybrid generative pipeline that combines a spectral-guided conditional Variational Autoencoder (cVAE), a class-conditional latent Denoising Diffusion Probabilistic Model (DDPM), and a Quantum Latent Refinement (QLR) module built on parameterized quantum circuits to augment minority arrhythmia classes in the MIT-BIH Arrhythmia Database. The QLR module applies a bounded residual correction guided by Maximum Mean Discrepancy minimization to align synthetic latent distributions with real class-specific latent banks. A lightweight 1D MobileNetV2 classifier evaluated over five independent random seeds and four augmentation ratios serves as the downstream benchmark. Our findings establish latent diffusion augmentation as an effective strategy for imbalanced ECG classification and motivate further investigation of quantum-classical hybrid methods in cardiac diagnostics.

Background: Current risk assessment tools for guiding direct oral anticoagulant (DOAC) therapy for patients with atrial fibrillation (AF) based on clinical risk factors demonstrate modest predictive performance limiting clinical impact. Additionally, while guidelines recommend periodic reassessment of risk over time, there remains an absence of modelling solutions for capturing evolving risk in AF patients. Methods: Using UK electronic health records, we developed and validated the Transformer-based Risk assessment survival model (TRisk), an artificial intelligence model that predicts 12-month thromboembolic and bleeding events in AF patients by leveraging temporal patient journeys up to baseline. A cohort of 411,850 prevalent non-valvular AF patients aged [&ge;]18 years between 2010 and 2020 was identified from 1,442 English general practices. Practices were randomly allocated to derivation (n=1,079) and external validation (n=363) cohorts. TRisk was compared with CHA2DS2-VASc and CHA2DS2-VA for thromboembolic event prediction, and HAS-BLED and ORBIT for bleeding prediction, with subgroup analyses by sex, age, and baseline characteristics. A second validation of TRisk was also performed on 16,218 US AF patients between 2010 and 2023. A decision model compared outcomes and healthcare costs for TRisk versus standard care. Findings: TRisk achieved higher discrimination for thromboembolic event prediction (C-index: 0.82; 95% confidence interval [CI]: [0.81, 0.83]) as compared to CHA2DS2-VASc (0.71 [0.70, 0.73]) in UK validation. Application of TRisk to US data yielded similar C-index: 0.82 (0.80, 0.84). For bleeding prediction, TRisk (C-index: 0.70 [0.69-0.71]) outperformed both HAS-BLED (0.63; [0.61, 0.64]) and ORBIT (0.64; [0.63, 0.65]), with comparable US results (0.71; [0.69, 0.74]). The model remained well-calibrated across both populations and performed equitably across subgroups, including by race and during the COVID-19 pandemic. Impact analyses showed TRisk could reduce DOAC prescriptions by 8% in the UK and 7% in the US relative to guideline-recommended approaches, while preventing at least as many thromboembolic events. This refined approach would generate annual healthcare savings of GBP 5.5 million and USD 456.2 million in the UK and US respectively among patients initiating DOACs, rising to GBP 48.6 million and USD 1.8 billion when extended to all AF patients on DOACs. Interpretation: TRisk enabled more precise prediction for both thromboembolic and bleeding events across AF populations in UK and US compared to established clinical scoring systems. Incorporating TRisk into routine AF care would result in substantial cost savings without compromising the identification of true high-risk patients. Funding: None

BackgroundIncidence and recurrence of atrial fibrillation (AF) is associated with several lifestyle risk factors. Lifestyle and risk factor modification (LRFM) clinics could have a role in comprehensively addressing AF from a holistic patient-centred approach to improve clinical outcomes. MethodsWe performed a systematic review and meta-analysis of randomised controlled trials (RCTs) evaluating the role of LRFM clinics compared with usual care (UC) in patients with AF. The primary endpoint was atrial arrhythmia recurrence. Secondary endpoints were AF and heart failure (HF) related hospitalisation, cardiovascular death, stroke or transient ischaemic attack (TIA), and quality-of-life (QOL). ResultsA total of eleven RCTs with a total of 3364 patients were included (five RCTs performed in the context of AF ablation). Mean age was 58-73 years, 30% were female and 18% had persistent AF. Duration of follow-up ranged from 3-24 months. LRFM clinics significantly reduced the primary endpoint of arrhythmia recurrence compared with UC after catheter ablation (OR 0.34, 95% CI 0.23-0.51, p<0.001, I2=0%). LRFM clinics also reduced AF-related hospitalisation (OR 0.70, 95%CI 0.51-0.98, p=0.04, I2=21%) and improved QOL (mean improvement on Short Form 36 Questionnaire 8.90, 95% CI 7.6.91-10.90, p<0.001). There was no difference between LRFM clinics and UC for HF-related hospitalisation (p=0.16), cardiovascular deaths (p=0.79) or stroke/TIA (p=0.83). ConclusionIn this meta-analysis of RCTs, LRFM clinics reduced AF recurrence after ablation, reduced AF-related hospitalisation and improved QOL. This study supports a comprehensive multidisciplinary lifestyle risk modification model of care to improve clinical outcomes in patients with AF.

Objective: Abdominal aortic aneurysms (AAA) affect more than 1% of adults over 50 and carry significant mortality risk. Current surveillance relies on intermittent imaging (ultrasound or MRI) at 6--24 month intervals, which may miss rapid growth acceleration between visits. We investigate the feasibility of continuous aneurysm diameter tracking using peripheral pulse waves, like those detected by photoplethysmography (PPG) devices. Approach: We use a simplified one-dimensional hemodynamic model that simulates pulse wave propagation from the heart to the pedal digital artery. We first demonstrate diameter estimation when the hemodynamic model parameters defining systemic circulation are known within bounds for an individual, aggregating thousands of observations over hours or days. We then address the more challenging scenario where systemic circulation parameters are only known to be within wider population-level physiological bounds, using a sequential Monte Carlo approach that combines ensemble MCMC with Kalman filtering to marginalise over unknown parameters while tracking the aneurysm diameter. Both approaches are validated through 12-month tracking simulations with constant and accelerating aneurysm growth rates. Main results: While single-observation diameter estimation is fundamentally limited by noise and confounding variables, aggregating 1,600 measurements under baseline noise conditions reduces diameter uncertainty to 0.8~mm when patient-specific hemodynamic parameters are known within bounds. In this setting, tracking simulations across eight virtual patients achieve average root-mean-square error (RMSE) of $\sim$0.3~mm. When systemic parameters are known only within population-level bounds, joint Bayesian estimation over the full parameter space achieves a median RMSE of 0.65~mm (1.4$\pm$0.3~mm, mean$\pm$standard error) across 50 virtual patients, remaining within clinically relevant ranges despite the underlying parameters being only partially identifiable. Significance: These physically-grounded, computational results suggest that peripheral pulse wave monitoring through wearable PPG sensors could complement traditional imaging for aneurysm surveillance, potentially enabling earlier detection of growth acceleration and more timely clinical intervention.

Aims: Responses to remote pulmonary artery pressure data vary across programs. We evaluated SMART-HF, a structured pulmonary artery diastolic pressure (PAD)-guided workflow, in a community heart failure cohort. Methods: We retrospectively analysed adults with heart failure and an implanted pulmonary artery pressure sensor managed with SMART-HF. Pulmonary artery diastolic pressure (PAD) was calculated from prespecified 14-day windows at baseline, 90 days, and 6 months. Two hemodynamic management performance indices (HMPI) were prespecified: the 6-Month Delta HMPI (PAD reduction >2 mmHg from baseline) and the 90-Day Target HMPI (PAD [&le;]20 mmHg at 90 days). Exploratory analyses evaluated patients with baseline PAD >20 mmHg. Results: Of 37 patients, 36 had paired 90-day and 29 had paired 6-month windows. Mean PAD decreased from 18.3 +/- 7.0 to 16.1 +/- 6.3 mmHg at 90 days and from 18.8 +/- 6.8 to 15.5 +/- 5.8 mmHg at 6 months (both P < 0.001). The 90-Day Target HMPI was achieved in 26/36 (72.2%) and the 6-Month Delta HMPI in 19/29 (65.5%) [95% CI 45.7-82.1]. In the exploratory subgroup (baseline PAD >20 mmHg), mean PAD changes were -2.9 +/- 3.6 mmHg at 90 days (n = 19; P = 0.002) and -4.9 +/- 4.9 mmHg at 6 months (n = 15; P = 0.002). Conclusions: SMART-HF was associated with improved ambulatory pulmonary artery diastolic pressure control at 90 days and 6 months. Exploratory subgroup findings support further evaluation in patients with elevated baseline pulmonary artery diastolic pressure.

The left ventricle (LV) exhibits torsional deformation during systole, and mechanical relaxation begins during the isovolumic phase. Recent advances in imaging techniques, such as MRI, have revealed that myocardial tissue deformation and sarcomere length changes occur during the isovolumic relaxation phase, even when the chamber volume remains constant. Although such ventricular deformation during the isovolumic phase is considered important for blood ejection and filling efficiency, its mechanistic contribution to contraction and relaxation remains unresolved. In this study, we hypothesized that sarcomere length dynamics during the isovolumic phase affect the isovolumic contraction and relaxation time (IVCT and IVRT) by regulating the contraction force via the force-velocity relationship of ventricular myocytes. To investigate this hypothesis, we focused on experimentally reported differences in the relationship between sarcomere length and LV volume across the endocardial and epicardial layers, as described by Rodriguez et al. We constructed and compared two types of hemodynamic models within the same integrated framework consisting of a circulation model, a LV model, and a myocardial cell contraction model by Negroni-Lascano et al., which differ only in how sarcomere length is determined: a volume-based length model (VL model), in which sarcomere length is uniquely determined by LV volume, and a volume-force-coupled length model (VFL model), in which sarcomere length is determined by the balance between LV volume and contraction force. Simulation results showed that in the VFL model, compared to the VL model, sarcomere length changed during the isovolumic phase, leading to a decrease in contractile force and shortening of IVRT, which may contribute to improved hemodynamic efficiency. These results indicate that sarcomere length dynamics can mechanically regulate force decay during isovolumic relaxation, even under constant left ventricular volume. This study provides a theoretical framework for understanding the contributions of different layers within the LV wall to diastolic function during the isovolumic relaxation phase.

Background: Detection of disease progression is key to personalize treatment strategies in transthyretin cardiomyopathy (ATTR-CM), particularly with emerging therapies. Echocardiography can detect subtle longitudinal changes but is limited by operator dependence. This study evaluates agreement and reproducibility of fully automated, AI-assisted echocardiographic measurements under real-world conditions. Methods: This retrospective study included 62 patients with ATTR-CM undergoing 178 serial annual echocardiograms assessed by a reference cardiologist, a second cardiologist, a novice reader, and a fully automated AI algorithm (Us2.ai). Interrater agreement was assessed using Bland-Altman analysis and intraclass correlation coefficients (ICCs). Intrarater variability for human readers was derived from repeated blinded measurements, with limits of agreement (LoA = mean difference +/- 1.96 x SD) defining the smallest detectable change. AI repeatability was assessed using within-study pairwise differences. Results: AI showed moderate agreement with the reference cardiologist for IVSd and LVEDV (ICC 0.65 and 0.51), with biases of -1.9 mm and -39 mL, respectively. Interrater agreement between cardiologists was good (ICC 0.79 and 0.84) with minimal bias (-0.2 mm and +3 mL). Intrarater variability was moderate to excellent for both cardiologists (LoA 3.0 mm and 43 mL for the reference cardiologist; 2.7 mm and 31 mL for the second cardiologist). AI demonstrated comparable repeatability (LoA 3.6 mm and 37 mL), while the novice showed higher variability (5.1 mm and 61 mL). Conclusion: AI-based measurements demonstrated repeatability comparable to experienced cardiologists. Despite moderate agreement and systematic differences in volumetric assessments, their reproducibility supports automated analysis for longitudinal echocardiographic monitoring.

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and is strongly associated with increased risks of stroke, heart failure, and mortality. Traditional methods to predict AF and prognostic its associated risks often fail to capture the full complexity of AF patterns, limiting their predictive accuracy. In spite of the improvements achieved by machine learning (ML) techniques, state-of-the-art AF-focused predictors do not generally incorporate longitudinal data, reducing their capacity to model the dynamic and evolving nature of individual behaviors and physiological indicators over time. The absence of a longitudinal perspective restricts understanding of how AF risk develops and changes across prognostic windows. This study addresses these limitations by developing superior ML models tailored to predict adverse events within a longitudinal Portuguese cohort of individuals with AF. The work targets six clinical endpoints: stroke, all-cause death, cardiovascular death, heart failure hospitalizations, inpatient visits, and acute coronary syndrome. The predictors yielded an AUC of 0.65 for 1-year stroke prediction, outperforming CHA2DS_2-VASc (0.59). For all-cause mortality prediction, the models achieved an AUC of 0.78 against the 0.72 reference of GARFIELD-AF. In addition to predictive advances, the study identifies determinants of AF-related risks and introduces a prototype decision-support tool for clinical use.

Background Functional mitral regurgitation results from interacting mechanisms whose relative contributions vary between atrial and ventricular subtypes and shift dynamically within each heartbeat, producing temporal patterns that static analyses cannot capture. Objectives To identify which structural determinants predict mitral regurgitation variability beat to beat using Granger causality within vector autoregression, focusing on papillary muscle dynamics across subtypes. Methods Frame-level echocardiographic time series from 41 patients (21 atrial, 20 ventricular; 1,959 frames) were z-score standardised within patient. Individual (lag 3) and pooled (lag 2) vector autoregression models tested whether left ventricular volume, left atrial volume, papillary muscle length, and annulus diameter Granger-predict mitral regurgitation area. Results Individual models revealed marked heterogeneity. In pooled analysis, left ventricular volume was the strongest Granger predictor at short lags (atrial p=0.011; ventricular p=0.006), while left atrial volume emerged at longer lags (lag 7: atrial p=0.043; ventricular p=0.011). Systolic papillary muscle length was not predictive. Full-cycle analysis revealed a subtype-specific dissociation: papillary muscle length Granger-predicted regurgitation only in the ventricular subtype (p=0.001), while regurgitation predicted papillary muscle displacement only in the atrial subtype (p<0.001). Left ventricular volume dominated within-beat prediction but lost cross-beat relevance in the ventricular subtype, while left atrial volume gained cross-beat predictive relevance in the atrial subtype. No structural determinant correlated with severity cross-sectionally. Conclusions Beat-to-beat vector autoregression and Granger modelling reveals heterogeneous, subtype-specific temporal patterns with distinct temporal windows of predictability for ventricular loading and papillary geometry. This framework may support patient-specific temporal phenotyping of functional mitral regurgitation.

Background: Late gadolinium enhancement (LGE) quantification by cardiovascular magnetic resonance is central to risk stratification in hypertrophic cardiomyopathy (HCM), yet conventional techniques require contour tracing and region-of-interest (ROI) placement, which may reduce reproducibility and increase analysis time. We developed a novel visual standardized approach, the Visual Standardized Quantification of LGE (VISTAQ), that does not require myocardial contouring, arbitrary ROI positioning, or dedicated post-processing software. Methods: In this multicenter, multivendor retrospective study, LGE images from 400 patients (100 prior myocardial infarction, 250 HCM, 50 other non-ischemic heart diseases) were analyzed. VISTAQ subdivides each myocardial segment into transmural mini-segments and classifies LGE visually using predefined criteria, expressing global LGE burden as the percentage of positive mini-segments. Reproducibility was assessed in 250 patients across different observer expertise levels using intraclass correlation coefficients (ICC) and Bland?Altman analysis. In 100 HCM patients, VISTAQ was compared with conventional methods (mean+2SD, +5SD, +6SD, FWHM, visual thresholding). Prognostic performance was evaluated in 250 HCM patients over a median 5-year follow-up. Results: VISTAQ demonstrated excellent intra- and inter-observer reproducibility (ICC up to 0.98 and 0.97, respectively), consistent across disease subtypes. Compared with conventional techniques, VISTAQ showed similar ICC to FWHM but significantly lower net and absolute inter-observer differences (median absolute difference 1.3%). Mean+2SD markedly overestimated LGE, whereas mean+6SD slightly underestimated LGE compared with VISTAQ, mean+5SD, FWHM, and visual thresholding. Analysis time was substantially shorter with VISTAQ (median 105 vs. 375 seconds, p<0.0001). During follow-up, 21 hard cardiac events occurred in HCM population. An LGE threshold >10% predicted events with higher accuracy using VISTAQ (AUC 0.90; sensitivity 85%; specificity 94%) compared with mean+6SD (AUC 0.75; sensitivity 57%; specificity 93%). Conclusions: VISTAQ provides highly reproducible, time-efficient LGE quantification without dedicated software and demonstrates non-inferior prognostic discrimination in HCM compared with conventional threshold-based techniques.

BackgroundSodium-glucose co-transporter 2 (SGLT2) inhibitors have emerged as a cornerstone of heart failure (HF) therapy, yet the totality of randomized evidence -- including smaller trials -- has not been comprehensively synthesized. We aimed to evaluate the efficacy and safety of SGLT2 inhibitors across the full spectrum of HF. MethodsWe searched PubMed, Cochrane CENTRAL, ClinicalTrials.gov, and WHO ICTRP from inception to March 2026 for randomized controlled trials comparing any SGLT2 inhibitor with placebo or standard care in adults with HF. Primary outcomes were all-cause mortality (ACM) and HF hospitalization (HFH). We used random-effects models with Mantel-Haenszel risk ratios and Hartung-Knapp-Sidik-Jonkman confidence intervals. Certainty of evidence was assessed using GRADE. The protocol was registered prospectively (PROSPERO CRD420251167908). ResultsOf 6,239 records identified, 114 studies met inclusion criteria and 59 RCTs (29,692 participants) were included in quantitative synthesis. SGLT2 inhibitors significantly reduced ACM (RR 0.90 [0.83, 0.98], p = 0.016; 26 trials; I2 = 0%; low certainty) and HFH (RR 0.74 [0.69, 0.79], p < 0.001; 15 trials; I2 = 0%; moderate certainty). The composite of CVD and HFH was reduced (RR 0.80 [0.75, 0.85], p < 0.001; high certainty). Genital infections were significantly increased (RR 3.75 [1.72, 8.19], p = 0.007). Results were robust across 12 sensitivity analyses and 4 alternative statistical models. ConclusionsSGLT2 inhibitors reduce all-cause mortality, HF hospitalization, cardiovascular death, and serious adverse events in adults with HF, with an acceptable safety profile apart from increased genital infections. These findings support the use of SGLT2 inhibitors as a foundational therapy across the HF spectrum.

BackgroundVentricular assist devices (VADs) are used as treatment for end-stage heart failure in children and adults. We previously demonstrated decreased mitochondrial function and changes in cardiolipin, a mitochondrial phospholipid, in explanted pediatric and adult failing hearts. In this study, we tested the hypothesis that VAD unloading of failing hearts leads to positive changes in myocardial cardiolipin in both pediatric and adult hearts. MethodsVentricular tissue was collected from the same patient at time of VAD implantation and at transplant. Ejection fraction (EF), left ventricular internal diameter at end-diastole (LVIDd) and brain natriuretic peptide (BNP) were assessed pre- and post-VAD. Cardiolipin species from paired VAD core and explants were quantified using liquid chromatography mass spectrometry. Mitochondrial respiration was measured in ventricular tissue pre- and post-VAD in paired pediatric samples using the Oroboros Oxygraph-2k. ResultsVAD support led to increased EF and decreased LVIDd and BNP. The predominant cardiolipin species in cardiac mitochondria, tetralinoleoylcardiolipin, was positively remodeled in pediatric post-VAD myocardium, while adult post-VAD myocardium demonstrated significantly increased total cardiolipin and decreased oxidized cardiolipin but did not demonstrate the tetralinoleoylcardiolipin remodeling seen in pediatric hearts. In pediatric patients, VAD support resulted in significant increases in Complex I+II activity, and a trend toward increases in Complex I activity. ConclusionOur data demonstrate age-related differences in VAD-associated cardiolipin remodeling and suggest that improved mitochondrial function in pediatric VAD-supported hearts could be related to increased tetralinoleoylcardiolipin.