Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia: a landmark study.

AIMS: Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up. METHODS AND RESULTS: We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6-3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79-0.87) and calibration slope of 0.97. CONCLUSION: The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)-positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.

Prognostic significance of echocardiographic deformation imaging in adult congenital heart disease.

BACKGROUND: Due to medical and surgical advancements, the population of adult patients with congenital heart disease (ACHD) is growing. Despite successful therapy, ACHD patients face structural sequalae, placing them at increased risk for heart failure and arrhythmias. Left and right ventricular function are important predictors for adverse clinical outcomes. In acquired heart disease it has been shown that echocardiographic deformation imaging is of superior prognostic value as compared to conventional parameters as ejection fraction. However, in adult congenital heart disease, the clinical significance of deformation imaging has not been systematically assessed and remains unclear. METHODS: According to the Preferred Reporting Items for Systematic Reviews checklist, this systematic review included studies that reported on the prognostic value of echocardiographic left and/or right ventricular strain by 2-dimensional speckle tracking for hard clinical end-points (death, heart failure hospitalization, arrhythmias) in the most frequent forms of adult congenital heart disease. RESULTS: In total, 19 contemporary studies were included. Current data shows that left ventricular and right ventricular global longitudinal strain (GLS) predict heart failure, transplantation, ventricular arrhythmias and mortality in patients with Ebstein's disease and tetralogy of Fallot, and that GLS of the systemic right ventricle predicts heart failure and mortality in patients post atrial switch operation or with a congenitally corrected transposition of the great arteries. CONCLUSIONS: Deformation imaging can potentially impact the clinical decision making in ACHD patients. Further studies are needed to establish disease-specific reference strain values and ranges of impaired strain that would indicate the need for medical or structural intervention.

Adherence to subcutaneous interferon beta-1a treatment among patients with relapsing multiple sclerosis: the MAIN-MS study.

Introduction and background: Adherence is a critical factor for optimal clinical outcomes in multiple sclerosis (MS) treatment. This study investigated the adherence and clinical outcomes of MS patients treated with subcutaneous (sc) interferon (IFN) (ß)-1a, an established immunomodulatory treatment for relapsing MS. The benefits of a patient support programme (PSP) were also studied. Methods: This phase-IV prospective, observational multicentre study enrolled patients with relapsing MS who were treated with sc IFN ß-1a for 24 months was conducted at 53 centres across 17 countries. The primary endpoint was adherence to sc IFN ß-1a treatment, as assessed using Morisky Green Levine Medication Adherence Scale (MGLS) scores at 24 months. The MGLS is a self-reported diagnostic tool to address medication non-adherence, with a score ranging from 0 to 4, with 0 representing high adherence, 1-2 representing medium adherence, and 3-4 representing low adherence. Other endpoints included time to study and treatment discontinuation over 24 months, the proportion of relapse-free patients, and Expanded Disability Status Scale (EDSS) progression (defined as ≥1.0 point increase sustained for 3 months) at 24 months. A subgroup analysis was performed for endpoints based on patients assigned to PSP (yes/no-PSP versus non-PSP subgroup). Results: Of the 577 patients enrolled, 408 had evaluable MGLS scores at 24 months. A total of 336 (58.2%; 95% confidence interval [CI]: 54.1-62.3%) patients reported high adherence, 57 (9.9%; 95% CIs: 7.6-12.7%) reported medium adherence, and 15 (2.6%; 95% CI: 1.5-4.3%) reported low adherence at 24 months. The PSP subgroup reported higher adherence (n = 206; 65.8%) than the non-PSP subgroup (n = 130; 56.5%). By 24 months, 52.2% of the patients were relapse-free and 17.2% patients experienced ≥1 relapse. Expanded Disability Status Scale progression was observed in 12.3% of patients. Over the 24-month period, 30.8% of the patients discontinued treatment, and the most common reasons for treatment discontinuation were adverse events (AEs, 10.4%), being lost to followup (7.1%), and a lack of efficacy (5.5%). Overall, 39.6% patients experienced ≥1 AE, which ranged from mild to moderate. Conclusion: The study demonstrated high adherence to sc IFN ß-1a treatment with an added benefit of PSP participation. More than half of the patients remained relapse-free over a 24-month period. No new safety concerns to sc IFN ß-1a treatment were observed. Clinical trial registration: https://clinicaltrials.gov/study/NCT02921035, NCT02921035.

Deep neural network-based clustering of deformation curves reveals novel disease features in PLN pathogenic variant carriers.

Echocardiographic deformation curves provide detailed information on myocardial function. Deep neural networks (DNNs) may enable automated detection of disease features in deformation curves, and improve the clinical assessment of these curves. We aimed to investigate whether an explainable DNN-based pipeline can be used to detect and visualize disease features in echocardiographic deformation curves of phospholamban (PLN) p.Arg14del variant carriers. A DNN was trained to discriminate PLN variant carriers (n = 278) from control subjects (n = 621) using raw deformation curves obtained by 2D-speckle tracking in the longitudinal axis. A visualization technique was used to identify the parts of these curves that were used by the DNN for classification. The PLN variant carriers were clustered according to the output of the visualization technique. The DNN showed excellent discriminatory performance (C-statistic 0.93 [95% CI 0.87-0.97]). We identified four clusters with PLN-associated disease features in the deformation curves. Two clusters showed previously described features: apical post-systolic shortening and reduced systolic strain. The two other clusters revealed novel features, both reflecting delayed relaxation. Additionally, a fifth cluster was identified containing variant carriers without disease features in the deformation curves, who were classified as controls by the DNN. This latter cluster had a very benign disease course regarding development of ventricular arrhythmias. Applying an explainable DNN-based pipeline to myocardial deformation curves enables automated detection and visualization of disease features. In PLN variant carriers, we discovered novel disease features which may improve individual risk stratification. Applying this approach to other diseases will further expand our knowledge on disease-specific deformation patterns. Overview of the deep neural network-based pipeline for feature detection in myocardial deformation curves. Firstly, phospholamban (PLN) p.Arg14del variant carriers and controls were selected and a deep neural network (DNN) was trained to detect the PLN variant carriers. Subsequently, a clustering-based approach was performed on the attention maps of the DNN, which revealed 4 distinct phenotypes of PLN variant carriers with different prognoses. Moreover, a cluster without features and a benign prognosis was detected.

The added value of abnormal regional myocardial function for risk prediction in arrhythmogenic right ventricular cardiomyopathy.

AIMS: A risk calculator for individualized prediction of first-time sustained ventricular arrhythmia (VA) in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients has recently been developed and validated (www.ARVCrisk.com). This study aimed to investigate whether regional functional abnormalities, measured by echocardiographic deformation imaging, can provide additional prognostic value. METHODS AND RESULTS: From two referral centres, 150 consecutive patients with a definite ARVC diagnosis, no prior sustained VA, and an echocardiogram suitable for deformation analysis were included (aged 41 ± 17 years, 50% female). During a median follow-up of 6.3 (interquartile range 3.1-9.8) years, 37 (25%) experienced a first-time sustained VA. All tested left and right ventricular (LV and RV) deformation parameters were univariate predictors for first-time VA. While LV function did not add predictive value in multivariate analysis, two RV deformation parameters did; RV free wall longitudinal strain and regional RV deformation patterns remained independent predictors after adjusting for the calculator-predicted risk [hazard ratio 1.07 (95% CI 1.02-1.11); P = 0.004 and 4.45 (95% CI 1.07-18.57); P = 0.040, respectively] and improved its discriminative value (from C-statistic 0.78 to 0.82 in both; Akaike information criterion change > 2). Importantly, all patients who experienced VA within 5 years from the echocardiographic assessment had abnormal regional RV deformation patterns at baseline. CONCLUSIONS: This study showed that regional functional abnormalities measured by echocardiographic deformation imaging can further refine personalized arrhythmic risk prediction when added to the ARVC risk calculator. The excellent negative predictive value of normal RV deformation could support clinicians considering the timing of implantable cardioverter defibrillator implantation in patients with intermediate arrhythmic risk.

Effect of BNT162b2 mRNA booster vaccination on VO2 max in recreational athletes: A prospective cohort study.

Background and Aims: The goal of the present study was to systematically evaluate the effect of a booster vaccination with the BNT162b2 messenger RNA (mRNA; Pfizer-BioNTech®) vaccine on maximum oxygen uptake (VO2 max), potential signs of (peri)myocarditis, and sports participation. Methods: Recreational athletes who were scheduled to undergo booster vaccination were evaluated with transthoracic echocardiography, serum measurements of high-sensitivity C-reactive protein(hsCRP) and high-sensitivity troponin I, and a bicycle cardiopulmonary exercise test (CPET) with serum lactate evaluation before the booster vaccine administration. Seven days postvaccination the test battery was repeated. Additionally, the subjects were asked to fill in a questionnaire on side effects and a subjective evaluation of their relative training volume and intensity as compared to the weeks before vaccination. Results: A group of 42 analysed athletes showed a statistically significant 2.7% decrease in VO2 max after vaccination (mean standard error of mean pre: 48.6 (1.4) ml/kg/min; post: 47.3 (1.4) ml/kg/min; p = 0.004). A potentially clinically relevant decrease of 8.6% or more occurred in 8 (19%) athletes. Other CPET parameters and lactate curves were comparable. We found no serological or echocardiographic evidence of (peri)myocarditis. A slight but significant increase in hsCRP was noted 1 week after vaccination. Side effects were mild and sports participation was generally unchanged or mildly decreased after vaccination. Conclusion: In our population of recreational endurance athletes, booster vaccination with the BNT162b2 mRNA vaccine resulted in a statistically significant decrease in VO2max 7 days after vaccination. The clinical impact hereof needs to be further determined. No major adverse events were observed.

Echocardiographic Deformation Imaging for Early Detection of Genetic Cardiomyopathies: JACC Review Topic of the Week.

Clinical screening of the relatives of patients with genetic cardiomyopathies is challenging, as they often lack detectable cardiac abnormalities at presentation. Life-threatening adverse events can already occur in these early stages of disease, so sensitive tools to reveal the earliest signs of disease are needed. The utility of echocardiographic deformation imaging for early detection has been explored for this population in multiple studies but has not been broadly implemented in clinical practice. The authors discuss contemporary evidence on the utility of deformation imaging in relatives of patients with genetic cardiomyopathies. The available body of data shows that deformation imaging reveals early disease-specific abnormalities in dilated cardiomyopathy, hypertrophic cardiomyopathy, and arrhythmogenic cardiomyopathy. Deformation imaging seems promising to enhance the screening and follow-up protocols in relatives, and the authors propose measures to accelerate its implementation in clinical care.

Optimal echocardiographic assessment of myocardial dysfunction for arrhythmic risk stratification in phospholamban mutation carriers.

AIMS: Phospholamban (PLN) p.Arg14del mutation carriers are at risk of developing malignant ventricular arrhythmias (VAs) and/or heart failure. Currently, left ventricular ejection fraction (LVEF) plays an important role in risk assessment for VA in these individuals. We aimed to study the incremental prognostic value of left ventricular mechanical dispersion (LVMD) by echocardiographic deformation imaging for prediction of sustained VA in PLN p.Arg14del mutation carriers. METHODS AND RESULTS: We included 243 PLN p.Arg14del mutation carriers, which were classified into three groups according to the '45/45' rule: (i) normal left ventricular (LV) function, defined as preserved LVEF ≥45% with normal LVMD ≤45 ms (n = 139), (ii) mechanical LV dysfunction, defined as preserved LVEF ≥45% with abnormal LVMD >45 ms (n = 63), and (iii) overt LV dysfunction, defined as reduced LVEF <45% (n = 41). During a median follow-up of 3.3 (interquartile range 1.8-6.0) years, sustained VA occurred in 35 individuals. The negative predictive value of having normal LV function at baseline was 99% [95% confidence interval (CI): 92-100%] for developing sustained VA. The positive predictive value of mechanical LV dysfunction was 20% (95% CI: 15-27%). Mechanical LV dysfunction was an independent predictor of sustained VA in multivariable analysis [hazard ratio adjusted for VA history: 20.48 (95% CI: 2.57-162.84)]. CONCLUSION: LVMD has incremental prognostic value on top of LVEF in PLN p.Arg14del mutation carriers, particularly in those with preserved LVEF. The '45/45' rule is a practical approach to echocardiographic risk stratification in this challenging group of patients. This approach may also have added value in other diseases where LVEF deterioration is a relative late marker of myocardial dysfunction.

Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders.

Aims: Deep neural networks (DNNs) perform excellently in interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for novel applications such as detection of reduced ejection fraction (EF). Despite these promising developments, implementation is hampered by the lack of trustworthy techniques to explain the algorithms to clinicians. Especially, currently employed heatmap-based methods have shown to be inaccurate. Methods and results: We present a novel pipeline consisting of a variational auto-encoder (VAE) to learn the underlying factors of variation of the median beat ECG morphology (the FactorECG), which are subsequently used in common and interpretable prediction models. As the ECG factors can be made explainable by generating and visualizing ECGs on both the model and individual level, the pipeline provides improved explainability over heatmap-based methods. By training on a database with 1.1 million ECGs, the VAE can compress the ECG into 21 generative ECG factors, most of which are associated with physiologically valid underlying processes. Performance of the explainable pipeline was similar to 'black box' DNNs in conventional ECG interpretation [area under the receiver operating curve (AUROC) 0.94 vs. 0.96], detection of reduced EF (AUROC 0.90 vs. 0.91), and prediction of 1-year mortality (AUROC 0.76 vs. 0.75). Contrary to the 'black box' DNNs, our pipeline provided explainability on which morphological ECG changes were important for prediction. Results were confirmed in a population-based external validation dataset. Conclusions: Future studies on DNNs for ECGs should employ pipelines that are explainable to facilitate clinical implementation by gaining confidence in artificial intelligence and making it possible to identify biased models.

Repetitive Immune-Mediated Noninfectious Endocarditis Necessitating 5 Mitral Valve Replacements.

We present a young patient who had to undergo 5 mitral valve replacements (MVR) because of a repetitive immune-mediated noninfectious endocarditis. The patient was treated with multiple anti-inflammatory drugs and high-dose prednisone. After the fifth MVR, the patient remained in stable condition using Anakinra after 22 months of follow-up. (Level of Difficulty: Advanced.).

Prediction of ventricular arrhythmia in phospholamban p.Arg14del mutation carriers-reaching the frontiers of individual risk prediction.

AIMS: This study aims to improve risk stratification for primary prevention implantable cardioverter defibrillator (ICD) implantation by developing a new mutation-specific prediction model for malignant ventricular arrhythmia (VA) in phospholamban (PLN) p.Arg14del mutation carriers. The proposed model is compared to an existing PLN risk model. METHODS AND RESULTS: Data were collected from PLN p.Arg14del mutation carriers with no history of malignant VA at baseline, identified between 2009 and 2020. Malignant VA was defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. A prediction model was developed using Cox regression. The study cohort consisted of 679 PLN p.Arg14del mutation carriers, with a minority of index patients (17%) and male sex (43%), and a median age of 42 years [interquartile range (IQR) 27-55]. During a median follow-up of 4.3 years (IQR 1.7-7.4), 72 (10.6%) carriers experienced malignant VA. Significant predictors were left ventricular ejection fraction, premature ventricular contraction count/24 h, amount of negative T waves, and presence of low-voltage electrocardiogram. The multivariable model had an excellent discriminative ability {C-statistic 0.83 [95% confidence interval (CI) 0.78-0.88]}. Applying the existing PLN risk model to the complete cohort yielded a C-statistic of 0.68 (95% CI 0.61-0.75). CONCLUSION: This new mutation-specific prediction model for individual VA risk in PLN p.Arg14del mutation carriers is superior to the existing PLN risk model, suggesting that risk prediction using mutation-specific phenotypic features can improve accuracy compared to a more generic approach.

Echocardiographic deformation imaging unmasks global and regional mechanical dysfunction in patients with idiopathic ventricular fibrillation: A multicenter case-control study.

BACKGROUND: Idiopathic ventricular fibrillation (IVF) is diagnosed in patients with sudden onset of ventricular fibrillation of unidentified origin. New diagnostic tools that can detect subtle abnormalities are needed to diagnose and treat patients with an underlying substrate. OBJECTIVE: The purpose of this study was to explore echocardiographic deformation characteristics in IVF patients. METHODS: Echocardiograms were analyzed with deformation imaging by 2-dimensional speckle tracking. Global and regional measurements of the left ventricle (LV) and right ventricle (RV) were performed. Regional LV deformation patterns were evaluated for the presence of postsystolic shortening. Regional RV deformation patterns were classified as type I (normal) or type II/III (abnormal). RESULTS: In total, 47 IVF patients (mean age 45 years; left ventricular ejection fraction [LVEF] 56%) and 47 healthy controls (mean age 41 years; LVEF 60%) were included. IVF patients showed more global deformation abnormalities as indicated by lower LV global longitudinal strain (18.5% ± 2.6% vs 21.6% ± 1.8%; P <.001) and higher LV mechanical dispersion (41 ± 12 ms vs 26 ± 6 ms; P <.001). In addition, IVF patients showed more regional LV postsystolic shortening compared to healthy controls (50% vs 11%; P <.001). Abnormal RV deformation patterns were observed in 16% of IVF patients and in none of the control subjects (P <.001). CONCLUSION: We were able to show both regional and global echocardiographic deformation abnormalities in IVF patients. This study provides evidence that localized myocardial disease is present in a subset of IVF patients.

Discovering and Visualizing Disease-Specific Electrocardiogram Features Using Deep Learning: Proof-of-Concept in Phospholamban Gene Mutation Carriers.

BACKGROUND: ECG interpretation requires expertise and is mostly based on physician recognition of specific patterns, which may be challenging in rare cardiac diseases. Deep neural networks (DNNs) can discover complex features in ECGs and may facilitate the detection of novel features which possibly play a pathophysiological role in relatively unknown diseases. Using a cohort of PLN (phospholamban) p.Arg14del mutation carriers, we aimed to investigate whether a novel DNN-based approach can identify established ECG features, but moreover, we aimed to expand our knowledge on novel ECG features in these patients. METHODS: A DNN was developed on 12-lead median beat ECGs of 69 patients and 1380 matched controls and independently evaluated on 17 patients and 340 controls. Differentiating features were visualized using Guided Gradient Class Activation Mapping++. Novel ECG features were tested for their diagnostic value by adding them to a logistic regression model including established ECG features. RESULTS: The DNN showed excellent discriminatory performance with a c-statistic of 0.95 (95% CI, 0.91-0.99) and sensitivity and specificity of 0.82 and 0.93, respectively. Visualizations revealed established ECG features (low QRS voltages and T-wave inversions), specified these features (eg, R- and T-wave attenuation in V2/V3) and identified novel PLN-specific ECG features (eg, increased PR-duration). The logistic regression baseline model improved significantly when augmented with the identified features (P<0.001). CONCLUSIONS: A DNN-based feature detection approach was able to discover and visualize disease-specific ECG features in PLN mutation carriers and revealed yet unidentified features. This novel approach may help advance diagnostic capabilities in daily practice.

A head-to-head comparison of speckle tracking echocardiography and feature tracking cardiovascular magnetic resonance imaging in right ventricular deformation.

AIMS: Speckle tracking echocardiography (STE) and feature tracking cardiovascular magnetic resonance imaging (FT-CMR) are advanced imaging techniques which are both used for quantification of global and regional myocardial strain. Direct comparisons of STE and FT-CMR regarding right ventricular (RV) strain analysis are limited. We aimed to study clinical performance, correlation and agreement of RV strain by these techniques, using arrhythmogenic right ventricular cardiomyopathy (ARVC) as a model for RV disease. METHODS AND RESULTS: We enrolled 110 subjects, including 34 patients with definite ARVC, 30 preclinical relatives of ARVC patients, and 46 healthy control subjects. Global and regional RV longitudinal peak strain (PS) were measured by STE and FT-CMR. Both modalities showed reduced strain values in ARVC patients compared to ARVC relatives (STE global PS: P < 0.001; FT-CMR global PS: P < 0.001) and reduced strain values in ARVC relatives compared to healthy control subjects (STE global PS: P = 0.042; FT-CMR global PS: P = 0.084). There was a moderate, albeit significant correlation between RV strain values obtained by STE and FT-CMR [global PS r = 0.578 (95% confidence interval 0.427-0.697), P < 0.001]. Agreement between the techniques was weak (limits of agreement for global PS: ±11.8%). Correlation and agreement both deteriorated when regional strain was studied. CONCLUSION: RV STE and FT-CMR show a similar trend within the spectrum of ARVC and have significant correlation, but inter-modality agreement is weak. STE and FT-CMR may therefore both individually have added value for assessment of RV function, but RV PS values obtained by these techniques currently cannot be used interchangeably in clinical practice.

Altered atrial cytosolic calcium handling contributes to the development of postoperative atrial fibrillation.

AIMS: Atrial fibrillation (AF) is a commonly occurring arrhythmia after cardiac surgery (postoperative AF, poAF) and is associated with poorer outcomes. Considering that reduced atrial contractile function is a predictor of poAF and that Ca2+ plays an important role in both excitation-contraction coupling and atrial arrhythmogenesis, this study aims to test whether alterations of intracellular Ca2+ handling contribute to impaired atrial contractility and to the arrhythmogenic substrate predisposing patients to poAF. METHODS AND RESULTS: Right atrial appendages were obtained from patients in sinus rhythm undergoing open-heart surgery. Cardiomyocytes were investigated by simultaneous measurement of [Ca2+]i and action potentials (APs, patch-clamp). Patients were followed-up for 6 days to identify those with and without poAF. Speckle-tracking analysis of preoperative echocardiography revealed reduced left atrial contraction strain in poAF patients. At the time of surgery, cellular Ca2+ transients (CaTs) and the sarcoplasmic reticulum (SR) Ca2+ content were smaller in the poAF group. CaT decay was slower in poAF, but the decay of caffeine-induced Ca2+ transients was unaltered, suggesting preserved sodium-calcium exchanger function. In agreement, western blots revealed reduced SERCA2a expression in poAF patients but unaltered phospholamban expression/phosphorylation. Computational modelling indicated that reduced SERCA activity promotes occurrence of CaT and AP alternans. Indeed, alternans of CaT and AP occurred more often and at lower stimulation frequencies in atrial myocytes from poAF patients. Resting membrane potential and AP duration were comparable between both groups at various pacing frequencies (0.25-8 Hz). CONCLUSIONS: Biochemical, functional, and modelling data implicate reduced SERCA-mediated Ca2+ reuptake into the SR as a major contributor to impaired preoperative atrial contractile function and to the pre-existing arrhythmogenic substrate in patients developing poAF.

Exploring the Correlation Between Fibrosis Biomarkers and Clinical Disease Severity in PLN p.Arg14del Patients.

Background: Pathogenic variants in phospholamban (PLN, like p. Arg14del), are found in patients diagnosed with arrhythmogenic (ACM) and dilated cardiomyopathy (DCM). Fibrosis formation in the heart is one of the hallmarks in PLN p.Arg14del carriers. During collagen synthesis and breakdown, propeptides are released into the circulation, such as procollagen type I carboxy-terminal propeptide (PICP) and C-terminal telopeptide collagen type I (ICTP). Aim: To investigate if PICP/ICTP levels in blood are correlative biomarkers for clinical disease severity and outcome in PLN p.Arg14del variant carriers. Methods: Serum and EDTA blood samples were collected from 72 PLN p.Arg14del carriers (age 50.5 years, 63% female) diagnosed with ACM (n = 12), DCM (n = 14), and preclinical variant carriers (n = 46). PICP levels were measured with an enzyme-linked immune sorbent assay and ICTP with a radio immuno-assay. Increased PICP/ICTP ratios suggest a higher collagen deposition. Clinical data including electrocardiographic, and imaging results were adjudicated from medical records. Results: No correlation between PICP/ICTP ratios and late gadolinium enhancement (LGE) was found. Moderate correlations were found between the PICP/ICTP ratio and end-diastolic/systolic volume (both r s = 0.40, n = 23, p = 0.06). PICP/ICTP ratio was significantly higher in patients with T wave inversion (TWI), especially in leads V4-V6, II, III, and aVF (p < 0.022) and in patients with premature ventricular contractions (PVCs) during an exercise tolerance test (p = 0.007). Conclusion: High PICP/ICTP ratios correlated with clinical parameters, such as TWI and PVCs. Given the limited size and heterogeneity of the patient group, additional studies are required to substantiate the incremental prognostic value of these fibrosis biomarkers in PLN p.Arg14del patients.

Early Mechanical Alterations in Phospholamban Mutation Carriers: Identifying Subclinical Disease Before Onset of Symptoms.

OBJECTIVES: This study aimed to explore echocardiographic characteristics of phospholamban (PLN) p.Arg14del mutation carriers to investigate whether structural and/or functional abnormalities could be identified before onset of symptoms. BACKGROUND: Carriers of the genetic PLN p.Arg14del mutation may develop arrhythmogenic and/or dilated cardiomyopathy. Overt disease is preceded by a pre-symptomatic phase of variable length in which disease expression seems to be absent. METHODS: PLN p.Arg14del mutation carriers with an available echocardiogram were included. Mutation carriers were classified as pre-symptomatic if they had no history of ventricular arrhythmias (VAs), a premature ventricular complex count of <500/24 h, and a left ventricular (LV) ejection fraction of ≥45%. In addition, we included 70 control subjects with similar age and sex distribution as the pre-symptomatic mutation carriers. Comprehensive echocardiographic analysis (including deformation imaging) was performed. RESULTS: The final study population consisted of 281 PLN p.Arg14del mutation carriers, 139 of whom were classified as pre-symptomatic. In comparison to control subjects, pre-symptomatic mutation carriers had lower global longitudinal strain and higher LV mechanical dispersion (both p < 0.001). In addition, post-systolic shortening (PSS) in the LV apex was observed in 43 pre-symptomatic mutation carriers (31%) and in none of the control subjects. During a median follow-up of 3.2 years (interquartile range: 2.1 to 5.6 years) in 104 pre-symptomatic mutation carriers, nonsustained VA occurred in 13 (13%). Presence of apical PSS was the strongest echocardiographic predictor of VA (multivariable hazards ratio: 5.11; 95% confidence interval [CI]: 1.37 to 19.08; p = 0.015), which resulted in a negative predictive value of 96% (95% CI: 89% to 98%) and a positive predictive value of 29% (95% CI: 21% to 40%). CONCLUSIONS: Global and regional LV mechanical alterations in PLN p.Arg14del mutation carriers precede arrhythmic symptoms and overt structural disease. Pre-symptomatic mutation carriers with normal deformation patterns in the apex are at low risk of developing VA within 3 years, whereas mutation carriers with apical PSS appear to be at higher risk.

Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology.

The combination of big data and artificial intelligence (AI) is having an increasing impact on the field of electrophysiology. Algorithms are created to improve the automated diagnosis of clinical ECGs or ambulatory rhythm devices. Furthermore, the use of AI during invasive electrophysiological studies or combining several diagnostic modalities into AI algorithms to aid diagnostics are being investigated. However, the clinical performance and applicability of created algorithms are yet unknown. In this narrative review, opportunities and threats of AI in the field of electrophysiology are described, mainly focusing on ECGs. Current opportunities are discussed with their potential clinical benefits as well as the challenges. Challenges in data acquisition, model performance, (external) validity, clinical implementation, algorithm interpretation as well as the ethical aspects of AI research are discussed. This article aims to guide clinicians in the evaluation of new AI applications for electrophysiology before their clinical implementation.

Development of an algorithm for automatic classification of right ventricle deformation patterns in arrhythmogenic right ventricular cardiomyopathy.

BACKGROUND: Different disease stages of arrhythmogenic right ventricular cardiomyopathy (ARVC) can be identified by right ventricle (RV) longitudinal deformation (strain) patterns. This requires assessment of the onset of shortening, (systolic) peak strain, and postsystolic index, which is time-consuming and prone to inter- and intra-observer variability. The aim of this study was to design and validate an algorithm to automatically classify RV deformation patterns. METHODS: We developed an algorithm based on specific local characteristics from the strain curves to detect the parameters required for classification. Determination of the onset of shortening by the algorithm was compared to manual determination by an experienced operator in a dataset containing 186 RV strain curves from 26 subjects carrying a pathogenic plakophilin-2 (PKP2) mutation and 36 healthy subjects. Classification agreement between operator and algorithm was solely based on differences in onset shortening, as the remaining parameters required for classification of RV deformation patterns could be directly obtained from the strain curves. RESULTS: The median difference between the onset of shortening determined by the experienced operator and by the automatic detector was 5.3 ms [inter-quartile range (IQR) 2.7-8.6 ms]. 96% of the differences were within 1 time frame. Both methods correlated significantly with ρ = 0.97 (P < .001). For 26 PKP2 mutation carriers, there was 100% agreement in classification between the algorithm and experienced operator. CONCLUSION: The determination of the onset of shortening by the experienced operator was comparable to the algorithm. Our computer algorithm seems a promising method for the automatic classification of RV deformation patterns. The algorithm is publicly available at the MathWorks File Exchange.