Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening

Background: Unexplained Left Ventricular Hypertrophy (ULVH) may be caused by genetic and non-genetic etiologies (e.g., sarcomere variants, cardiac amyloid, or Anderson-Fabry's disease). Identification of ULVH patients allows for early targeted treatment and family screening. Aim: To automatically identify patients with ULVH in electronic health record (EHR) data using two computer methods: text-mining and machine learning (ML). Methods: Adults with echocardiographic measurement of interventricular septum thickness (IVSt) were included. A text-mining algorithm was developed to identify patients with ULVH. An ML algorithm including a variety of clinical, ECG and echocardiographic data was trained and tested in an 80/20% split. Clinical diagnosis of ULVH was considered the gold standard. Misclassifications were reviewed by an experienced cardiologist. Sensitivity, specificity, positive, and negative likelihood ratios (LHR+ and LHR-) of both text-mining and ML were reported. Results: In total, 26,954 subjects (median age 61 years, 55% male) were included. ULVH was diagnosed in 204/26,954 (0.8%) patients, of which 56 had amyloidosis and two Anderson-Fabry Disease. Text-mining flagged 8,192 patients with possible ULVH, of whom 159 were true positives (sensitivity, specificity, LHR+, and LHR- of 0.78, 0.67, 2.36, and 0.33). Machine learning resulted in a sensitivity, specificity, LHR+, and LHR- of 0.32, 0.99, 32, and 0.68, respectively. Pivotal variables included IVSt, systolic blood pressure, and age. Conclusions: Automatic identification of patients with ULVH is possible with both Text-mining and ML. Text-mining may be a comprehensive scaffold but can be less specific than machine learning. Deployment of either method depends on existing infrastructures and clinical applications

Modeling the His-Purkinje Effect in Non-invasive Estimation of Endocardial and Epicardial Ventricular Activation

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm

Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity

Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects

A randomized controlled trial of eplerenone in asymptomatic phospholamban p.Arg14del carriers

INTRODUCTION Phospholamban (PLN; p.Arg14del) cardiomyopathy is an inherited disease caused by the pathogenic p.Arg14del variant in the PLN gene. Clinically, it is characterized by malignant ventricular arrhythmias and progressive heart failure.1,2 Cardiac fibrotic tissue remodelling occurs early on in PLN p.Arg14del carriers.3,4 Eplerenone was deemed a treatment candidate because of its beneficial effects on ventricular remodelling and antifibrotic properties.5,6 We conducted the multicentre randomized trial ‘intervention in PHOspholamban RElated CArdiomyopathy STudy’ (i-PHORECAST) to assess whether treatment with eplerenone of asymptomatic PLN p.Arg14del carriers attenuates disease onset and progression

Prevalence and Disease Expression of Pathogenic and Likely Pathogenic Variants Associated With Inherited Cardiomyopathies in the General Population

BACKGROUND: Pathogenic and likely pathogenic variants associated with arrhythmogenic right ventricular cardiomyopathy (ARVC), dilated cardiomyopathy (DCM), and hypertrophic cardiomyopathy (HCM) are recommended to be reported as secondary findings in genome sequencing studies. This provides opportunities for early diagnosis, but also fuels uncertainty in variant carriers (G+), since disease penetrance is incomplete. We assessed the prevalence and disease expression of G+ in the general population. METHODS: We identified pathogenic and likely pathogenic variants associated with ARVC, DCM and/or HCM in 200 643 UK Biobank individuals, who underwent whole exome sequencing. We calculated the prevalence of G+ and analyzed the frequency of cardiomyopathy/heart failure diagnosis. In undiagnosed individuals, we analyzed early signs of disease expression using available electrocardiography and cardiac magnetic resonance imaging data. RESULTS: We found a prevalence of 1:578, 1:251, and 1:149 for pathogenic and likely pathogenic variants associated with ARVC, DCM and HCM respectively. Compared with controls, cardiovascular mortality was higher in DCM G+ (odds ratio 1.67 [95% CI 1.04; 2.59], P =0.030), but similar in ARVC and HCM G+ ( P ≥0.100). Cardiomyopathy or heart failure diagnosis were more frequent in DCM G+ (odds ratio 3.66 [95% CI 2.24; 5.81], P =4.9×10 −7 ) and HCM G+ (odds ratio 3.03 [95% CI 1.98; 4.56], P =5.8×10 −7 ), but comparable in ARVC G+ ( P =0.172). In contrast, ARVC G+ had more ventricular arrhythmias ( P =3.3×10 −4 ). In undiagnosed individuals, left ventricular ejection fraction was reduced in DCM G+ ( P =0.009). CONCLUSIONS: In the general population, pathogenic and likely pathogenic variants associated with ARVC, DCM, or HCM are not uncommon. Although G+ have increased mortality and morbidity, disease penetrance in these carriers from the general population remains low (1.2–3.1%). Follow-up decisions in case of incidental findings should not be based solely on a variant, but on multiple factors, including family history and disease expression

Prolonged Electromechanical Interval Unmasks Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy in the Subclinical Stage

INTRODUCTION: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is characterized by high incidence of ventricular arrhythmias. Overt ARVD/C is preceded by a subclinical stage with lack of detectable ECG and structural abnormalities. Activation delay is present before structural abnormalities and is a hallmark of arrhythmogenesis. Deformation imaging may unmask activation delay in the subclinical stage. METHODS: Three groups were compared: (1) mutation-positive definite ARVD/C-patients fulfilling 2010 Task Force criteria (TFC) (n = 44); (2) asymptomatic mutation carriers not fulfilling TFC and without history of ventricular arrhythmias (n = 31); and (3) controls (n = 30). All underwent ECG and echocardiographic deformation imaging. As a surrogate for local activation delay the electromechanical interval (EMI) was measured, defined as time between onset-QRS and onset of shortening. Arrhythmic outcome (PVC-count, VT) of asymptomatic mutation carriers was correlated with EMI and ECG TFC. RESULTS: In definite ARVD/C-patients, EMI was prolonged in all lateral RV segments. In asymptomatic mutation carriers, prolonged EMI was detected in the subtricuspid area in 14/31. Terminal activation duration ≥55 milliseconds (definition: supporting information) was the only ECG abnormality in this group (8/31). After a mean follow-up of 4.2 ± 3.1 years 10/31 asymptomatic mutation carriers experienced arrhythmic outcome. Prolonged subtricuspid EMI was the only parameter significantly associated with arrhythmogenesis during follow-up. CONCLUSION: In ARVD/C-patients, EMI prolongation was present throughout the RV. In asymptomatic mutation carriers, prolonged EMI in the subtricuspid area is often detected without any additional abnormalities. These preliminary results indicate that prolonged EMI is a new parameter unmasking activation delay in the subclinical stage and may contribute to risk stratification