Outcomes of Cardiac Screening in Adolescent Soccer Players.

BACKGROUND: Reports on the incidence and causes of sudden cardiac death among young athletes have relied largely on estimated rates of participation and varied methods of reporting. We sought to investigate the incidence and causes of sudden cardiac death among adolescent soccer players in the United Kingdom. METHODS: From 1996 through 2016, we screened 11,168 adolescent athletes with a mean (±SD) age of 16.4±1.2 years (95% of whom were male) in the English Football Association (FA) cardiac screening program, which consisted of a health questionnaire, physical examination, electrocardiography, and echocardiography. The FA registry was interrogated to identify sudden cardiac deaths, which were confirmed with autopsy reports. RESULTS: During screening, 42 athletes (0.38%) were found to have cardiac disorders that are associated with sudden cardiac death. A further 225 athletes (2%) with congenital or valvular abnormalities were identified. After screening, there were 23 deaths from any cause, of which 8 (35%) were sudden deaths attributed to cardiac disease. Cardiomyopathy accounted for 7 of 8 sudden cardiac deaths (88%). Six athletes (75%) with sudden cardiac death had had normal cardiac screening results. The mean time between screening and sudden cardiac death was 6.8 years. On the basis of a total of 118,351 person-years, the incidence of sudden cardiac death among previously screened adolescent soccer players was 1 per 14,794 person-years (6.8 per 100,000 athletes). CONCLUSIONS: Diseases that are associated with sudden cardiac death were identified in 0.38% of adolescent soccer players in a cohort that underwent cardiovascular screening. The incidence of sudden cardiac death was 1 per 14,794 person-years, or 6.8 per 100,000 athletes; most of these deaths were due to cardiomyopathies that had not been detected on screening. (Funded by the English Football Association and others.).

Non-invasive detection of exercise-induced cardiac conduction abnormalities in sudden cardiac death survivors in the inherited cardiac conditions.

AIMS: Rate adaptation of the action potential ensures spatial heterogeneities in conduction across the myocardium are minimized at different heart rates providing a protective mechanism against ventricular fibrillation (VF) and sudden cardiac death (SCD), which can be quantified by the ventricular conduction stability (V-CoS) test previously described. We tested the hypothesis that patients with a history of aborted SCD due to an underlying channelopathy or cardiomyopathy have a reduced capacity to maintain uniform activation following exercise. METHODS AND RESULTS: Sixty individuals, with (n = 28) and without (n = 32) previous aborted-SCD event underwent electro-cardiographic imaging recordings following exercise treadmill test. These included 25 Brugada syndrome, 13 hypertrophic cardiomyopathy, 12 idiopathic VF, and 10 healthy controls. Data were inputted into the V-CoS programme to calculate a V-CoS score that indicate the percentage of ventricle that showed no significant change in ventricular activation, with a lower score indicating the development of greater conduction heterogeneity. The SCD group, compared to those without, had a lower median (interquartile range) V-CoS score at peak exertion [92.8% (89.8-96.3%) vs. 97.3% (94.9-99.1%); P < 0.01] and 2 min into recovery [95.2% (91.1-97.2%) vs. 98.9% (96.9-99.5%); P < 0.01]. No significant difference was observable later into recovery at 5 or 10 min. Using the lowest median V-CoS scores obtained during the entire recovery period post-exertion, SCD survivors had a significantly lower score than those without for each of the different underlying aetiologies. CONCLUSION: Data from this pilot study demonstrate the potential use of this technique in risk stratification for the inherited cardiac conditions.

Adapting the role of handheld echocardiography during the COVID-19 pandemic: A practical guide.

The COVID-19 pandemic has altered our approach to inpatient echocardiography delivery. There is now a greater focus to address key clinical questions likely to make an immediate impact in management, particularly during the period of widespread infection. Handheld echocardiography (HHE) can be used as a first-line assessment tool, limiting scanning time and exposure to high viral load. This article describes a potential role for HHE during a pandemic. We propose a protocol with a reporting template for a focused core dataset necessary in delivering an acute echocardiography service in the setting of a highly contagious disease, minimising risk to the operator. We cover the scenarios typically encountered in the acute cardiology setting and how an expert trained echocardiography team can identify such pathologies using a limited imaging format and include cardiac presentations encountered in those patients acutely unwell with COVID-19.

Cardiac Sarcoidosis multi-center randomized controlled trial (CHASM CS- RCT).

Approximately 5% of patients with sarcoidosis have clinically manifest cardiac involvement. Clinical features of Cardiac Sarcoidosis are dependent on the location, extent, and activity of the disease. First line therapy is usually with prednisone and this is recommended based on clinician experience, expert opinion and small observational cohorts. There are no published clinical trials in cardiac sarcoidosis and multiple experts in the field have called for randomized clinical trials to answer important patient care questions. Corticosteroid are associated with multiple adverse effects including hypertension, diabetes, weight gain, osteoporosis, and increased risk of infections. In contrast Methotrexate is generally well tolerated and is increasingly used in other forms of sarcoidosis. OBJECTIVES: The Cardiac Sarcoidosis Multi-Center Randomized Controlled Trial (CHASM CS-RCT; NCT03593759) is a multicenter randomized controlled trial designed to evaluate the optimal initial treatment strategy for patients with active cardiac sarcoidosis. We hypothesize that (1) a low dose prednisone/methotrexate combination will have non-inferior efficacy to standard dose prednisone and that (2) the low dose prednisone/ methotrexate combination will result in significantly better quality of life than standard dose prednisone, as a result of reduced burden of side effects. METHODS/DESIGN: Eligible study subjects will have active clinically manifest cardiac sarcoidosis presenting with one or more of the following clinical findings: advanced conduction system disease, significant sinus node dysfunction, non-sustained or sustained ventricular arrhythmia, left ventricular dysfunction or right ventricular dysfunction. Subjects will be randomized in a 1:1 ratio to prednisone 0.5 mg/kg/day for 6 months (maximum dose 30 mg daily) OR to prednisone 20 mg daily for 1 month, then 10 mg daily for 1 month, then 5 mg daily for one month then stop AND methotrexate 15-20 mg once weekly for 6 months. The primary endpoint is summed perfusion rest score on 6-month PET (blinded core-lab review). The summed perfusion rest score is measure of myocardial fibrosis/scar. The design is non-inferiority with a sample size of 97 per group. DISCUSSION: Given the multiorgan system potential adverse side effects of prednisone, proving noninferiority of an alternate regimen would be sufficient to make the alternative compare favorably to standard dose steroids. This is the first ever clinical trial in cardiac sarcoidosis and thus in addition to the listed goals of the trial, we will also establish a multi-center, multinational cardiac sarcoidosis clinical trials network. Such a collaborative infrastructure will enable a new era of high quality data to guide physicians when treating cardiac sarcoidosis patients.

Ventricular conduction stability test: a method to identify and quantify changes in whole heart activation patterns during physiological stress.

AIMS: Abnormal rate adaptation of the action potential is proarrhythmic but is difficult to measure with current electro-anatomical mapping techniques. We developed a method to rapidly quantify spatial discordance in whole heart activation in response to rate cycle length changes. We test the hypothesis that patients with underlying channelopathies or history of aborted sudden cardiac death (SCD) have a reduced capacity to maintain uniform activation following exercise. METHODS AND RESULTS: Electrocardiographical imaging (ECGI) reconstructs >1200 electrograms (EGMs) over the ventricles from a single beat, providing epicardial whole heart activation maps. Thirty-one individuals [11 SCD survivors; 10 Brugada syndrome (BrS) without SCD; and 10 controls] with structurally normal hearts underwent ECGI vest recordings following exercise treadmill. For each patient, we calculated the relative change in EGM local activation times (LATs) between a baseline and post-exertion phase using custom written software. A ventricular conduction stability (V-CoS) score calculated to indicate the percentage of ventricle that showed no significant change in relative LAT (<10 ms). A lower score reflected greater conduction heterogeneity. Mean variability (standard deviation) of V-CoS score over 10 consecutive beats was small (0.9 ± 0.5%), with good inter-operator reproducibility of V-CoS scores. Sudden cardiac death survivors, compared to BrS and controls, had the lowest V-CoS scores post-exertion (P = 0.011) but were no different at baseline (P = 0.50). CONCLUSION: We present a method to rapidly quantify changes in global activation which provides a measure of conduction heterogeneity and proof of concept by demonstrating SCD survivors have a reduced capacity to maintain uniform activation following exercise.

Prevalence of spontaneous type I ECG pattern, syncope, and other risk markers in sudden cardiac arrest survivors with Brugada syndrome.

INTRODUCTION: A spontaneous type I electrocardiogram (ECG) pattern and/or unheralded syncope are conventionally used as risk markers for primary prevention of sudden cardiac arrest/death (SCA/SCD) in Brugada syndrome (BrS). In this study, we determine the prevalence of conventional and newer markers of risk in those with and without previous aborted SCA events. METHODS: All patients with BrS were identified at our institute. History of symptoms was obtained from medical tests or from interviews. Other markers of risk were also obtained, such as presence of (1) spontaneous type I pattern, (2) fractionated QRS (fQRS), (3) early repolarization (ER) pattern, (4) late potentials on signal-averaged ECG (SAECG), and (5) response to programmed electrical stimulation. RESULTS: In 133 patients with Bars, 10 (7%) patients (mean age = 39 ± 11 years; nine males) were identified with a previous ventricular fibrillation/ventricular tachycardia episode (n = 8) or requiring cardio-pulmonary resuscitation (n = 2). None of these patients had a prior history of syncope before their SCA event. Only two (20%) patients reported a history of palpitations or dizziness. None had apneic breathing and three (30%) patients had a family history of SCA. From their ECGs, a spontaneous pattern was only found in one (10%) of these patients. Further, 10% of patients had fQRS, 17% had late potentials on SAECG, 20% had deep S waves in lead I, and 10% had an ER pattern in the peripheral leads. No significant differences were observed in the non-SCA group. CONCLUSION: The majority of BrS patients with previous aborted SCA events did not have a spontaneous type I and/or prior history of syncope. Conventional and newer markers of risk appear to only have limited ability to predict SCA.

Repolarization abnormalities unmasked with exercise in sudden cardiac death survivors with structurally normal hearts.

BACKGROUND: Models of cardiac arrhythmogenesis predict that nonuniformity in repolarization and/or depolarization promotes ventricular fibrillation and is modulated by autonomic tone, but this is difficult to evaluate in patients. We hypothesize that such spatial heterogeneities would be detected by noninvasive ECG imaging (ECGi) in sudden cardiac death (SCD) survivors with structurally normal hearts under physiological stress. METHODS: ECGi was applied to 11 SCD survivors, 10 low-risk Brugada syndrome patients (BrS), and 10 controls undergoing exercise treadmill testing. ECGi provides whole heart activation maps and >1,200 unipolar electrograms over the ventricular surface from which global dispersion of activation recovery interval (ARI) and regional delay in conduction were determined. These were used as surrogates for spatial heterogeneities in repolarization and depolarization. Surface ECG markers of dispersion (QT and Tpeak-end intervals) were also calculated for all patients for comparison. RESULTS: Following exertion, the SCD group demonstrated the largest increase in ARI dispersion compared to BrS and control groups (13 ± 8 ms vs. 4 ± 7 ms vs. 4 ± 5 ms; P = 0.009), with baseline dispersion being similar in all groups. In comparison, surface ECG markers of dispersion of repolarization were unable to discriminate between the groups at baseline or following exertion. Spatial heterogeneities in conduction were also present following exercise but were not significantly different between SCD survivors and the other groups. CONCLUSION: Increased dispersion of repolarization is apparent during physiological stress in SCD survivors and is detectable with ECGi but not with standard ECG parameters. The electrophysiological substrate revealed by ECGi could be the basis of alternative risk-stratification techniques.

Machine learning-derived cycle length variability metrics predict spontaneously terminating ventricular tachycardia in implantable cardioverter defibrillator recipients.

Aims: Implantable cardioverter defibrillator (ICD) therapies have been associated with increased mortality and should be minimized when safe to do so. We hypothesized that machine learning-derived ventricular tachycardia (VT) cycle length (CL) variability metrics could be used to discriminate between sustained and spontaneously terminating VT. Methods and results: In this single-centre retrospective study, we analysed data from 69 VT episodes stored on ICDs from 27 patients (36 spontaneously terminating VT, 33 sustained VT). Several VT CL parameters including heart rate variability metrics were calculated. Additionally, a first order auto-regression model was fitted using the first 10 CLs. Using features derived from the first 10 CLs, a random forest classifier was used to predict VT termination. Sustained VT episodes had more stable CLs. Using data from the first 10 CLs only, there was greater CL variability in the spontaneously terminating episodes (mean of standard deviation of first 10 CLs: 20.1 ± 8.9 vs. 11.5 ± 7.8 ms, P < 0.0001). The auto-regression coefficient was significantly greater in spontaneously terminating episodes (mean auto-regression coefficient 0.39 ± 0.32 vs. 0.14 ± 0.39, P < 0.005). A random forest classifier with six features yielded an accuracy of 0.77 (95% confidence interval 0.67 to 0.87) for prediction of VT termination. Conclusion: Ventricular tachycardia CL variability and instability are associated with spontaneously terminating VT and can be used to predict spontaneous VT termination. Given the harmful effects of unnecessary ICD shocks, this machine learning model could be incorporated into ICD algorithms to defer therapies for episodes of VT that are likely to self-terminate.

Ventricular Conduction Stability Noninvasively Identifies an Arrhythmic Substrate in Survivors of Idiopathic Ventricular Fibrillation.

Background Idiopathic ventricular fibrillation (VF) is a diagnosis of exclusion following normal cardiac investigations. We sought to determine if exercise-induced changes in electrical substrate could distinguish patient groups with various ventricular arrhythmic pathophysiological conditions and identify patients susceptible to VF. Methods and Results Computed tomography and exercise testing in patients wearing a 252-electrode vest were combined to determine ventricular conduction stability between rest and peak exercise, as previously described. Using ventricular conduction stability, conduction heterogeneity in idiopathic VF survivors (n=14) was compared with those surviving VF during acute ischemia with preserved ventricular function following full revascularization (n=10), patients with benign ventricular ectopy (n=11), and patients with normal hearts, no arrhythmic history, and negative Ajmaline challenge during Brugada family screening (Brugada syndrome relatives; n=11). Activation patterns in normal subjects (Brugada syndrome relatives) are preserved following exercise, with mean ventricular conduction stability of 99.2±0.9%. Increased heterogeneity of activation occurred in the idiopathic VF survivors (ventricular conduction stability: 96.9±2.3%) compared with the other groups combined (versus 98.8±1.6%; P=0.001). All groups demonstrated periodic variation in activation heterogeneity (frequency, 0.3-1 Hz), but magnitude was greater in idiopathic VF survivors than Brugada syndrome relatives or patients with ventricular ectopy (7.6±4.1%, 2.9±2.9%, and 2.8±1.2%, respectively). The cause of this periodicity is unknown and was not replicable by introducing exercise-induced noise at comparable frequencies. Conclusions In normal subjects, ventricular activation patterns change little with exercise. In contrast, patients with susceptibility to VF experience activation heterogeneity following exercise that requires further investigation as a testable manifestation of underlying myocardial abnormalities otherwise silent during routine testing.

Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia.

Background: Accurately determining arrhythmia mechanism from a 12-lead electrocardiogram (ECG) of supraventricular tachycardia can be challenging. We hypothesized a convolutional neural network (CNN) can be trained to classify atrioventricular re-entrant tachycardia (AVRT) vs atrioventricular nodal re-entrant tachycardia (AVNRT) from the 12-lead ECG, when using findings from the invasive electrophysiology (EP) study as the gold standard. Methods: We trained a CNN on data from 124 patients undergoing EP studies with a final diagnosis of AVRT or AVNRT. A total of 4962 5-second 12-lead ECG segments were used for training. Each case was labeled AVRT or AVNRT based on the findings of the EP study. The model performance was evaluated against a hold-out test set of 31 patients and compared to an existing manual algorithm. Results: The model had an accuracy of 77.4% in distinguishing between AVRT and AVNRT. The area under the receiver operating characteristic curve was 0.80. In comparison, the existing manual algorithm achieved an accuracy of 67.7% on the same test set. Saliency mapping demonstrated the network used the expected sections of the ECGs for diagnoses; these were the QRS complexes that may contain retrograde P waves. Conclusion: We describe the first neural network trained to differentiate AVRT from AVNRT. Accurate diagnosis of arrhythmia mechanism from a 12-lead ECG could aid preprocedural counseling, consent, and procedure planning. The current accuracy from our neural network is modest but may be improved with a larger training dataset.

Prevalence and diagnostic significance of de-novo 12-lead ECG changes after COVID-19 infection in elite soccer players.

BACKGROUND AND AIM: The efficacy of pre-COVID-19 and post-COVID-19 infection 12-lead ECGs for identifying athletes with myopericarditis has never been reported. We aimed to assess the prevalence and significance of de-novo ECG changes following COVID-19 infection. METHODS: In this multicentre observational study, between March 2020 and May 2022, we evaluated consecutive athletes with COVID-19 infection. Athletes exhibiting de-novo ECG changes underwent cardiovascular magnetic resonance (CMR) scans. One club mandated CMR scans for all players (n=30) following COVID-19 infection, despite the absence of cardiac symptoms or de-novo ECG changes. RESULTS: 511 soccer players (median age 21 years, IQR 18-26 years) were included. 17 (3%) athletes demonstrated de-novo ECG changes, which included reduction in T-wave amplitude in the inferior and lateral leads (n=5), inferior leads (n=4) and lateral leads (n=4); inferior T-wave inversion (n=7); and ST-segment depression (n=2). 15 (88%) athletes with de-novo ECG changes revealed evidence of inflammatory cardiac sequelae. All 30 athletes who underwent a mandatory CMR scan had normal findings. Athletes revealing de-novo ECG changes had a higher prevalence of cardiac symptoms (71% vs 12%, p<0.0001) and longer median symptom duration (5 days, IQR 3-10) compared with athletes without de-novo ECG changes (2 days, IQR 1-3, p<0.001). Among athletes without cardiac symptoms, the additional yield of de-novo ECG changes to detect cardiac inflammation was 20%. CONCLUSIONS: 3% of athletes demonstrated de-novo ECG changes post COVID-19 infection, of which 88% were diagnosed with cardiac inflammation. Most affected athletes exhibited cardiac symptoms; however, de-novo ECG changes contributed to a diagnosis of cardiac inflammation in 20% of athletes without cardiac symptoms.

Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. We here report results from the largest HCM genome-wide association study (GWAS) and multi-trait analysis (MTAG) including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We identified a total of 70 loci (50 novel) associated with HCM, and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants cause HCM. Mendelian randomization analyses support a causal role of increased LV contractility in both obstructive and non-obstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.

The Athletic ECG: A Line of Defense Against Misinterpretation.

A 17-year-old competitive athlete was found to have a minor electrocardiogram abnormality on routine screening. Cardiac magnetic resonance revealed evidence of marked myocarditis, allowing a subsequent safe abstinence from exercise. The case highlights the importance of careful electrocardiogram interpretation, especially in athletes, where physiologic adaptive changes can pose a diagnostic challenge. (Level of Difficulty: Intermediate.).

Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus dependence from other atrial tachycardia mechanisms.

Aims: Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard. Methods and results: We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77-0.95) compared to median expert electrophysiologist accuracy of 79% (range 70-84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output. Conclusion: We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.

The Brugada Type 1 Electrocardiogram and Ventricular Tachycardia With High-Dose Amitriptyline.

A 32-year-old woman with anorexia nervosa experienced ventricular tachycardia while on therapeutic-dose amitriptyline despite normal blood tests, imaging, and intracardiac recordings. Electrocardiograms over several years featured the Type 1 Brugada pattern. Careful electrocardiogram monitoring should be made if using high doses of amitriptyline, especially in those with low body weight. (Level of Difficulty: Intermediate.).

A Multicenter External Validation of a Score Model to Predict Risk of Events in Patients With Brugada Syndrome.

A multivariate risk score model was proposed by Sieira et al in 2017 for sudden death in Brugada syndrome; their validation in 150 patients was highly encouraging, with a C-index of 0.81; however, this score is yet to be validated by an independent group. A total of 192 records of patients with Brugada syndrome were collected from 2 centers in the United Kingdom and retrospectively scored according to a score model by Sieira et al. Data were compiled summatively over follow-up to mimic regular risk re-evaluation as per current guidelines. Sudden cardiac death survivor data were considered perievent to ascertain the utility of the score before cardiac arrest. Scores were compared with actual outcomes. Sensitivity in our cohort was 22.7%, specificity was 57.6%, and C-index was 0.58. In conclusion, up to 75% of cardiac arrest survivors in this cohort would not have been offered a defibrillator if evaluated before their event. This casts doubt on the utility of the score model for primary prevention of sudden death. Inherent issues with modern risk scoring strategies decrease the likelihood of success even in robustly designed tools such as the Sieira score model.

COVID-19 and its impact on the cardiovascular system.

OBJECTIVES: The clinical impact of SARS-CoV-2 has varied across countries with varying cardiovascular manifestations. We review the cardiac presentations, in-hospital outcomes and development of cardiovascular complications in the initial cohort of SARS-CoV-2 positive patients at Imperial College Healthcare National Health Service Trust, UK. METHODS: We retrospectively analysed 498 COVID-19 positive adult admissions to our institute from 7 March to 7 April 2020. Patient data were collected for baseline demographics, comorbidities and in-hospital outcomes, especially relating to cardiovascular intervention. RESULTS: Mean age was 67.4±16.1 years and 62.2% (n=310) were male. 64.1% (n=319) of our cohort had underlying cardiovascular disease (CVD) with 53.4% (n=266) having hypertension. 43.2%(n=215) developed acute myocardial injury. Mortality was significantly increased in those patients with myocardial injury (47.4% vs 18.4%, p<0.001). Only four COVID-19 patients had invasive coronary angiography, two underwent percutaneous coronary intervention and one required a permanent pacemaker implantation. 7.0% (n=35) of patients had an inpatient echocardiogram. Acute myocardial injury (OR 2.39, 95% CI 1.31 to 4.40, p=0.005) and history of hypertension (OR 1.88, 95% CI 1.01 to 3.55, p=0.049) approximately doubled the odds of in-hospital mortality in patients admitted with COVID-19 after other variables had been controlled for. CONCLUSION: Hypertension, pre-existing CVD and acute myocardial injury were associated with increased in-hospital mortality in our cohort of COVID-19 patients. However, only a low number of patients required invasive cardiac intervention.

Right ventricular pacing for hypertrophic obstructive cardiomyopathy: meta-analysis and meta-regression of clinical trials.

AIMS: Right ventricular pacing for left ventricular outflow tract gradient reduction in hypertrophic obstructive cardiomyopathy remains controversial. We undertook a meta-analysis for echocardiographic and functional outcomes. METHODS AND RESULTS: Thirty-four studies comprising 1135 patients met eligibility criteria. In the four blinded randomized controlled trials (RCTs), pacing reduced gradient by 35% [95% confidence interval (CI) 23.2-46.9, P < 0.0001], but there was only a trend towards improved New York Heart Association (NYHA) class [odds ratio (OR) 1.82, CI 0.96-3.44; P = 0.066]. The unblinded observational studies reported a 54.3% (CI 44.1-64.6, P < 0.0001) reduction in gradient, which was a 18.6% greater reduction than the RCTs (P = 0.0351 for difference between study designs). Observational studies reported an effect on unblinded NYHA class at an OR of 8.39 (CI 4.39-16.04, P < 0.0001), 450% larger than the OR in RCTs (P = 0.0042 for difference between study designs). Across all studies, the gradient progressively decreased at longer follow durations, by 5.2% per month (CI 2.5-7.9, P = 0.0001). CONCLUSION: Right ventricular pacing reduces gradient in blinded RCTs. There is a non-significant trend to reduction in NYHA class. The bias in assessment of NYHA class in observational studies appears to be more than twice as large as any genuine treatment effect.

Effectiveness of the 2014 European Society of Cardiology guideline on sudden cardiac death in hypertrophic cardiomyopathy: a systematic review and meta-analysis.

OBJECTIVE: In 2014, the European Society of Cardiology (ESC) recommended the use of a novel risk prediction model (HCM Risk-SCD) to guide use of implantable cardioverter defibrillators (ICD) for the primary prevention of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM). We sought to determine the performance of HCM Risk-SCD by conducting a systematic review and meta-analysis of articles reporting on the prevalence of SCD within 5 years of evaluation in low, intermediate and high-risk patients as defined by the 2014 guidelines (predicted risk <4%, 4%-<6% and ≥6%, respectively). METHODS: The protocol was registered with PROSPERO (registration number: CRD42017064203). MEDLINE and manual searches for papers published from October 2014 to December 2017 were performed. Longitudinal, observational cohorts of unselected adult patients, without history of cardiac arrest were considered. The original HCM Risk-SCD development study was included a priori. Data were pooled using a random effects model. RESULTS: Six (0.9%) out of 653 independent publications identified by the initial search were included. The calculated 5-year risk of SCD was reported in 7291 individuals (70% low, 15% intermediate; 15% high risk) with 184 (2.5%) SCD endpoints within 5 years of baseline evaluation. Most SCD endpoints (68%) occurred in patients with an estimated 5-year risk of ≥4% who formed 30% of the total study cohort. Using the random effects method, the pooled prevalence of SCD endpoints was 1.01% (95% CI 0.52 to 1.61) in low-risk patients, 2.43% (95% CI 1.23 to 3.92) in intermediate and 8.4% (95% CI 6.68 to 10.25) in high-risk patients. CONCLUSIONS: This meta-analysis demonstrates that HCM Risk-SCD provides accurate risk estimations that can be used to guide ICD therapy in accordance with the 2014 ESC guidelines. REGISTRATION NUMBER: PROSPERO CRD42017064203;Pre-results.