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.

Impact of a Chronic Total Coronary Occlusion on the Incidence of Appropriate Implantable Cardioverter-Defibrillator Shocks and Mortality: A Substudy of the Dutch Outcome in ICD Therapy (DO-IT)) Registry.

BACKGROUND: Chronic total coronary occlusions (CTO) substantially increase the risk for sudden cardiac death. Among patients with chronic ischemic heart disease at risk for sudden cardiac death, an implantable cardioverter defibrillator (ICD) is the favored therapy for primary prevention of sudden cardiac death. This study sought to investigate the impact of CTOs on the risk for appropriate ICD shocks and mortality within a nationwide prospective cohort. METHODS AND RESULTS: This is a subanalysis of the nationwide Dutch-Outcome in ICD Therapy (DO-IT) registry of primary prevention ICD recipients in The Netherlands between September 2014 and June 2016 (n=1442). We identified patients with chronic ischemic heart disease (n=663) and assessed available coronary angiograms for CTO presence (n=415). Patients with revascularized CTOs were excluded (n=79). The primary end point was the composite of all-cause mortality and appropriate ICD shocks. Clinical follow-up was conducted for at least 2 years. A total of 336 patients were included, with an average age of 67±9 years, and 20.5% was female (n=69). An unrevascularized CTO was identified in 110 patients (32.7%). During a median follow-up period of 27 months (interquartile range, 24-32), the primary end point occurred in 21.1% of patients with CTO (n=23) compared with 11.9% in patients without CTO (n=27; P=0.034). Corrected for baseline characteristics including left ventricular ejection fraction, and the presence of a CTO was an independent predictor for the primary end point (hazard ratio, 1.82 [95% CI, 1.03-3.22]; P=0.038). CONCLUSIONS: Within this nationwide prospective registry of primary prevention ICD recipients, the presence of an unrevascularized CTO was an independent predictor for the composite outcome of all-cause mortality and appropriate ICD shocks.

Assessment of ICD eligibility in non-ischaemic cardiomyopathy patients: a position statement by the Task Force of the Dutch Society of Cardiology.

International guidelines recommend implantation of an implantable cardioverter-defibrillator (ICD) in non-ischaemic cardiomyopathy (NICM) patients with a left ventricular ejection fraction (LVEF) below 35% despite optimal medical therapy and a life expectancy of more than 1 year with good functional status. We propose refinement of these recommendations in patients with NICM, with careful consideration of additional risk parameters for both arrhythmic and non-arrhythmic death. These additional parameters include late gadolinium enhancement on cardiac magnetic resonance imaging and genetic testing for high-risk genetic variants to further assess arrhythmic risk, and age, comorbidities and sex for assessment of non-arrhythmic mortality risk. Moreover, several risk modifiers should be taken into account, such as concomitant arrhythmias that may affect LVEF (atrial fibrillation, premature ventricular beats) and resynchronisation therapy. Even though currently no valid cut-off values have been established, the proposed approach provides a more careful consideration of risks that may result in withholding ICD implantation in patients with low arrhythmic risk and substantial non-arrhythmic mortality risk.

ECG-only explainable deep learning algorithm predicts the risk for malignant ventricular arrhythmia in phospholamban cardiomyopathy.

BACKGROUND: Phospholamban (PLN) p.(Arg14del) variant carriers are at risk for development of malignant ventricular arrhythmia (MVA). Accurate risk stratification allows timely implantation of intracardiac defibrillators and is currently performed with a multimodality prediction model. OBJECTIVE: This study aimed to investigate whether an explainable deep learning-based approach allows risk prediction with only electrocardiogram (ECG) data. METHODS: A total of 679 PLN p.(Arg14del) carriers without MVA at baseline were identified. A deep learning-based variational auto-encoder, trained on 1.1 million ECGs, was used to convert the 12-lead baseline ECG into its FactorECG, a compressed version of the ECG that summarizes it into 32 explainable factors. Prediction models were developed by Cox regression. RESULTS: The deep learning-based ECG-only approach was able to predict MVA with a C statistic of 0.79 (95% CI, 0.76-0.83), comparable to the current prediction model (C statistic, 0.83 [95% CI, 0.79-0.88]; P = .054) and outperforming a model based on conventional ECG parameters (low-voltage ECG and negative T waves; C statistic, 0.65 [95% CI, 0.58-0.73]; P < .001). Clinical simulations showed that a 2-step approach, with ECG-only screening followed by a full workup, resulted in 60% less additional diagnostics while outperforming the multimodal prediction model in all patients. A visualization tool was created to provide interactive visualizations (https://pln.ecgx.ai). CONCLUSION: Our deep learning-based algorithm based on ECG data only accurately predicts the occurrence of MVA in PLN p.(Arg14del) carriers, enabling more efficient stratification of patients who need additional diagnostic testing and follow-up.

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.

Exercise does not influence development of phenotype in PLN p.(Arg14del) cardiomyopathy.

BACKGROUND: Endurance and frequent exercise are associated with earlier onset of arrhythmogenic right ventricular cardiomyopathy (ARVC) and ventricular arrhythmias (VA) in desmosomal gene variant carriers. Individuals with the pathogenic c.40_42del; p.(Arg14del) variant in the PLN gene are frequently diagnosed with ARVC or dilated cardiomyopathy (DCM). The aim of this study was to evaluate the effect of exercise in PLN p.(Arg14del) carriers. METHODS: In total, 207 adult PLN p.(Arg14del) carriers (39.1% male; mean age 53 ± 15 years) were interviewed on their regular physical activity since the age of 10 years. The association of exercise with diagnosis of ARVC, DCM, sustained VA and hospitalisation for heart failure (HF) was studied. RESULTS: Individuals participated in regular physical activities with a median of 1661 metabolic equivalent of task (MET) hours per year (31.9 MET-hours per week) until clinical presentation. The 50% most and least active individuals had a similar frequency of sustained VA (18.3% vs 18.4%; p = 0.974) and hospitalisation for HF (9.6% vs 8.7%; p = 0.827). There was no relationship between exercise and survival free from (incident) sustained VA (p = 0.65), hospitalisation for HF (p = 0.81), diagnosis of ARVC (p = 0.67) or DCM (p = 0.39) during follow-up. In multivariate analyses, exercise was not associated with sustained VA or HF hospitalisation during follow-up in this relatively not-active cohort. CONCLUSION: There was no association between the amount of exercise and the susceptibility to develop ARVC, DCM, VA or HF in PLN p.(Arg14del) carriers. This suggested unaffected PLN p.(Arg14del) carriers can safely perform mild-moderate exercise, in contrast to desmosomal variant carriers and ARVC patients.

A failed catheter ablation of atrial fibrillation is associated with more advanced remodeling and reduced efficacy of further thoracoscopic ablation.

INTRODUCTION AND OBJECTIVES: Recent observations suggest that patients with a previous failed catheter ablation have an increased risk of atrial fibrillation (AF) recurrence after subsequent thoracoscopic AF ablation. We assessed the risk of AF recurrence in patients with a previous failed catheter ablation undergoing thoracoscopic ablation. METHODS: We included patients from 3 medical centers. To correct for potential heterogeneity, we performed propensity matching to compare AF freedom (freedom from any atrial tachyarrhythmia> 30 s during 1-year follow-up). Left atrial appendage tissue was analyzed for collagen distribution. RESULTS: A total of 705 patients were included, and 183 had a previous failed catheter ablation. These patients had fewer risk factors for AF recurrence than ablation naïve controls: smaller indexed left atrial volume (40.9± 12.5 vs 43.0±12.5 mL/m2, P=.048), less congestive heart failure (1.5% vs 8.9%, P=.001), and less persistent AF (52.2% vs 60.3%, P=.067). However, AF history duration was longer in patients with a previous failed catheter ablation (6.5 [4-10.5] vs 4 [2-8] years; P<.001). In propensity matched analysis, patients with a failed catheter ablation were at a 68% higher AF recurrence risk (OR, 1.68; 95%CI, 1.20-2.15; P=.034). AF freedom was 61.1% in patients with a previous failed catheter ablation vs 72.5% in ablation naïve matched controls. On histology of the left atrial appendage (n=198), patients with a failed catheter ablation had a higher density of collagen fibers. CONCLUSIONS: Patients with a prior failed catheter ablation had fewer risk factors for AF recurrence but more frequently had AF recurrence after thoracoscopic AF ablation than ablation naïve patients. This may in part be explained by more progressed, subclinical, atrial fibrosis formation.

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.

Sex-specific aspects of phospholamban cardiomyopathy: The importance and prognostic value of low-voltage electrocardiograms.

BACKGROUND: A pathogenic variant in the gene encoding phospholamban (PLN), a protein that regulates calcium homeostasis of cardiomyocytes, causes PLN cardiomyopathy. It is characterized by a high arrhythmic burden and can progress to severe cardiomyopathy. Risk assessment guides implantable cardioverter-defibrillator therapy and benefits from personalization. Whether sex-specific differences in PLN cardiomyopathy exist is unknown. OBJECTIVE: The purpose of this study was to improve the accuracy of PLN cardiomyopathy diagnosis and risk assessment by investigating sex-specific aspects. METHODS: We analyzed a multicenter cohort of 933 patients (412 male, 521 female) with the PLN p.(Arg14del) pathogenic variant following up on a recently developed PLN risk model. Sex-specific differences in the incidence of risk model components were investigated: low-voltage electrocardiogram (ECG), premature ventricular contractions, negative T waves, and left ventricular ejection fraction. RESULTS: Sustained ventricular arrhythmias (VAs) occurred in 77 males (18.7%) and 61 females (11.7%) (P = .004). Of the 933 cohort members, 287 (31%) had ≥1 low-voltage ECG during follow-up (180 females [63%], 107 males [37%]; P = .006). Female sex, age, age at clinical presentation, and proband status predicted low-voltage ECG during follow-up (area under the curve: 0.78). Sustained VA-free survival was lowest in males with low-voltage ECG (P <.001). CONCLUSION: Low-voltage ECGs predict sustained VA and are a component of the PLN risk model. Low-voltage ECGs are more common in females, yet prognostic value is greater in males. Future studies should determine the impact of this difference on the risk prediction of PLN cardiomyopathy and possibly other cardiomyopathies.

The ß-angle can help guide clinical decisions in the diagnostic work-up of patients suspected of Brugada syndrome: a validation study of the ß-angle in determining the outcome of a sodium channel provocation test.

AIMS: In patients with Brugada syndrome (BrS) but without spontaneous Type-1 electrocardiogram, several electrocardiographic characteristics have been studied, including the ß-angle. Previous studies suggested that the ß-angle might be useful in distinguishing BrS-patients from patients with only suggestive repolarization patterns without performing sodium channel blocker provocation testing. In this study, we aimed to determine the diagnostic value of the ß-angle in patients suspected of BrS. METHODS AND RESULTS: A large cohort (n = 1430) of consecutive patients who underwent provocation testing was evaluated. ß-angles were measured in leads V1, V2, and their corresponding positions over the second and third intercostal space. Receiver-operating characteristic curves were constructed and the diagnostic accuracy of previously reported ß-angle cut-offs were calculated and evaluated. The importance of the ß-angle for predicting the provocation test outcome was determined using a prediction model constructed with logistic regression. The optimum ß-angle cut-off in our cohort for ruling out a positive provocation test was 15°; sensitivities were 80-98% and negative predictive values were 79-96% among the right precordial leads. Previously reported ß-angle cut-offs performed less well, indicated by lower Youden indices. In the optimism-corrected prediction model [C-statistic: 0.78 (95% CI: 0.75-0.81)], the ß-angle had large value (Z-score: 2.1-10.3) and aided construction of a nomogram to predict test outcome. CONCLUSION: To predict the outcome of provocation testing for BrS, the ß-angle alone does not demonstrate strong diagnostic characteristics. However, the ß-angle is an important variable to predict provocation test outcome and thus has added value.

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.

Dutch Outcome in Implantable Cardioverter-Defibrillator Therapy: Implantable Cardioverter-Defibrillator-Related Complications in a Contemporary Primary Prevention Cohort.

Background One third of primary prevention implantable cardioverter-defibrillator patients receive appropriate therapy, but all remain at risk of defibrillator complications. Information on these complications in contemporary cohorts is limited. This study assessed complications and their risk factors after defibrillator implantation in a Dutch nationwide prospective registry cohort and forecasts the potential reduction in complications under distinct scenarios of updated indication criteria. Methods and Results Complications in a prospective multicenter registry cohort of 1442 primary implantable cardioverter-defibrillator implant patients were classified as major or minor. The potential for reducing complications was derived from a newly developed prediction model of appropriate therapy to identify patients with a low probability of benefitting from the implantable cardioverter-defibrillator. During a follow-up of 2.2 years (interquartile range, 2.0-2.6 years), 228 complications occurred in 195 patients (13.6%), with 113 patients (7.8%) experiencing at least one major complication. Most common ones were lead related (n=93) and infection (n=18). Minor complications occurred in 6.8% of patients, with lead-related (n=47) and pocket-related (n=40) complications as the most prevailing ones. A surgical reintervention or additional hospitalization was required in 53% or 61% of complications, respectively. Complications were strongly associated with device type. Application of stricter implant indication results in a comparable proportional reduction of (major) complications. Conclusions One in 13 patients experiences at least one major implantable cardioverter-defibrillator-related complication, and many patients undergo a surgical reintervention. Complications are related to defibrillator implantations, and these should be discussed with the patient. Stricter implant indication criteria and careful selection of device type implanted may have significant clinical and financial benefits.

Improving electrocardiogram-based detection of rare genetic heart disease using transfer learning: An application to phospholamban p.Arg14del mutation carriers.

The pathogenic mutation p.Arg14del in the gene encoding Phospholamban (PLN) is known to cause cardiomyopathy and leads to increased risk of sudden cardiac death. Automatic tools might improve the detection of patients with this rare disease. Deep learning is currently the state-of-the-art in signal processing but requires large amounts of data to train the algorithms. In situations with relatively small amounts of data, like PLN, transfer learning may improve accuracy. We propose an ECG-based detection of the PLN mutation using transfer learning from a model originally trained for sex identification. The sex identification model was trained with 256,278 ECGs and subsequently finetuned for PLN detection (155 ECGs of patients with PLN) with two control groups: a balanced age/sex matched group and a randomly selected imbalanced population. The data was split in 10 folds and 20% of the training data was used for validation and early stopping. The models were evaluated with the area under the receiver operating characteristic curve (AUROC) of the testing data. We used gradient activation for explanation of the prediction models. The models trained with transfer learning outperformed the models trained from scratch for both the balanced (AUROC 0.87 vs AUROC 0.71) and imbalanced (AUROC 0.0.90 vs AUROC 0.65) population. The proposed approach was able to improve the accuracy of a rare disease detection model by transfer learning information from a non-manual annotated and abundant label with only limited data available.

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death.

AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.

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.

Computer versus cardiologist: Is a machine learning algorithm able to outperform an expert in diagnosing a phospholamban p.Arg14del mutation on the electrocardiogram?

BACKGROUND: Phospholamban (PLN) p.Arg14del mutation carriers are known to develop dilated and/or arrhythmogenic cardiomyopathy, and typical electrocardiographic (ECG) features have been identified for diagnosis. Machine learning is a powerful tool used in ECG analysis and has shown to outperform cardiologists. OBJECTIVES: We aimed to develop machine learning and deep learning models to diagnose PLN p.Arg14del cardiomyopathy using ECGs and evaluate their accuracy compared to an expert cardiologist. METHODS: We included 155 adult PLN mutation carriers and 155 age- and sex-matched control subjects. Twenty-one PLN mutation carriers (13.4%) were classified as symptomatic (symptoms of heart failure or malignant ventricular arrhythmias). The data set was split into training and testing sets using 4-fold cross-validation. Multiple models were developed to discriminate between PLN mutation carriers and control subjects. For comparison, expert cardiologists classified the same data set. The best performing models were validated using an external PLN p.Arg14del mutation carrier data set from Murcia, Spain (n = 50). We applied occlusion maps to visualize the most contributing ECG regions. RESULTS: In terms of specificity, expert cardiologists (0.99) outperformed all models (range 0.53-0.81). In terms of accuracy and sensitivity, experts (0.28 and 0.64) were outperformed by all models (sensitivity range 0.65-0.81). T-wave morphology was most important for classification of PLN p.Arg14del carriers. External validation showed comparable results, with the best model outperforming experts. CONCLUSION: This study shows that machine learning can outperform experienced cardiologists in the diagnosis of PLN p.Arg14del cardiomyopathy and suggests that the shape of the T wave is of added importance to this diagnosis.

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.

Handling missing predictor values when validating and applying a prediction model to new patients.

Missing data present challenges for development and real-world application of clinical prediction models. While these challenges have received considerable attention in the development setting, there is only sparse research on the handling of missing data in applied settings. The main unique feature of handling missing data in these settings is that missing data methods have to be performed for a single new individual, precluding direct application of mainstay methods used during model development. Correspondingly, we propose that it is desirable to perform model validation using missing data methods that transfer to practice in single new patients. This article compares existing and new methods to account for missing data for a new individual in the context of prediction. These methods are based on (i) submodels based on observed data only, (ii) marginalization over the missing variables, or (iii) imputation based on fully conditional specification (also known as chained equations). They were compared in an internal validation setting to highlight the use of missing data methods that transfer to practice while validating a model. As a reference, they were compared to the use of multiple imputation by chained equations in a set of test patients, because this has been used in validation studies in the past. The methods were evaluated in a simulation study where performance was measured by means of optimism corrected C-statistic and mean squared prediction error. Furthermore, they were applied in data from a large Dutch cohort of prophylactic implantable cardioverter defibrillator patients.