L’amiodarone en fibrillation auriculaire chez les patients avec et sans dysfonction ventriculaire gauche sévère : une étude combinée de AFFIRM et AF-CHF

Objectif: Déterminer si l’efficacité de l’amiodarone pour le maintien du rythme sinusal varie selon la fonction systolique ventriculaire gauche. Contexte: Malgré un profil de sécurité établi en insuffisance cardiaque, nous ignorons si l’efficacité de l’amiodarone et son impact sur différentes issues cardiovasculaires sont modulés par la fonction ventriculaire gauche. Méthode: Nous avons effectué une analyse combinée de 3307 patients (âgés de 68,0±0,9 ans ; 31,1% de femmes) recrutés dans les études AFFIRM et AF-CHF qui ont été randomisés au contrôle du rythme par l’amiodarone (N=1107) ou au contrôle de la fréquence cardiaque (N=2200). Résultats: Chez les patients sous amiodarone, la survie sans fibrillation auriculaire était de 84% et de 45% à 1 et 5 ans respectivement, sans égard à la fraction d’éjection ventriculaire gauche (P=0,8754, ajusté). De façon similaire, la proportion moyenne ajustée de temps en fibrillation auriculaire (15,0±1,8%) n’a pas été influencée par la fraction d’éjection (P=0,6094). Durant le suivi, 1963 patients (59,4%) ont requis au moins une hospitalisation, incluant 1401 (42,6%) patients hospitalisés pour cause cardiovasculaire. Les taux ajustés d’hospitalisation pour toutes causes et pour cause cardiovasculaire étaient similaires entre les patients sous amiodarone et ceux dans le groupe de contrôle de la fréquence dans l’ensemble de la population ainsi que dans les sous-groupes de patients avec et sans dysfonction ventriculaire gauche sévère. De façon similaire, les taux ajustés de mortalité globale et cardiovasculaire étaient similaires entre chez les patients sous amiodarone et ceux traités par le contrôle de la fréquence dans l’ensemble de la population ainsi que dans les sous-groupes de patients avec et sans dysfonction ventriculaire gauche sévère. Conclusions: L’efficacité de l’amiodarone pour le maintien du rythme sinusal n’est pas influencée par la fonction ventriculaire gauche. Le contrôle du rythme avec l’amiodarone s’associe à des taux de mortalité et d’hospitalisation comparables au contrôle de la fréquence à la fois chez les patients avec et sans dysfonction ventriculaire gauche sévère.Objectives: To determine whether amiodarone’s efficacy in maintaining sinus rhythm varies according to left ventricular systolic function. Background: Despite amiodarone’s established safety profile in heart failure, it is unknown whether its impact on cardiovascular outcomes is modulated by ventricular function. Methods: We conducted a pooled analysis of 3307 patients (age 68.0±0.9 years; 31.1% female) enrolled in AFFIRM and AF-CHF trials who were randomized to rhythm control with amiodarone (N=1107) or rate control (N=2200). Results: In amiodarone-treated patients, freedom from recurrent atrial fibrillation was 84% and 45% at 1 and 5 years, respectively, with no differences according to left ventricular function (adjusted P=0.8754). Similarly, the adjusted mean proportion of time in atrial fibrillation (15.0±1.8%) did not vary according to ventricular function (P=0.6094). During follow-up, 1963 (59.4%) patients required at least one hospitalization, with 1401 (42.6%) patients hospitalized for a cardiovascular reason. Adjusted all-cause and cardiovascular hospitalization rates were similar with amiodarone versus rate control in the overall population and in subgroups of patients with and without severe left ventricular dysfunction. Similarly adjusted all-cause and cardiovascular mortality rates were similar with amiodarone versus rate control, overall and in subgroups of patients with and without severe left ventricular dysfunction. Conclusions: Amiodarone’s efficacy in maintaining sinus rhythm and reducing the burden of atrial fibrillation is similar in patients with and without left ventricular dysfunction. Rhythm control with amiodarone was associated with similar mortality and hospitalisation rates when compared to rate control in patients with and without severe left ventricular dysfunction

Vers une meilleure identification des patients à risque d’arythmies ventriculaires en cardiopathie arythmogène du ventricule droit

Introduction : La cardiopathie arythmogène du ventricule droit (CAVD) est une pathologie d’origine génétique se traduisant par un remplacement cicatriciel qui affecte de façon prédominante le ventricule droit (VD). Le diagnostic est complexe car il repose sur un ensemble de critères cliniques plutôt que sur un seul test diagnostic. L’atteinte du VD se traduit de façon prédominante par des arythmies ventriculaires qui peuvent parfois conduire à la complication la plus redoutée de cette affection : la mort subite. La prédiction et la prévention de celle-ci sont des enjeux cruciaux de la prise en charge de cette maladie. Objectifs : Ce travail vise à améliorer la prise en charge des patients atteints de CAVD de deux façons distinctes. Premièrement, en tentant de faciliter le diagnostic par la validation des critères diagnostiques en vigueur. Deuxièmement, en améliorant la stratification du risque d’arythmie ventriculaires soutenues et plus spécifiquement celui de la mort subite et des arythmies potentiellement mortelles (tachycardie ventriculaire > 250 bpm, fibrillation ventriculaire) en créant des modèles de prédiction du risque permettant de déterminer le risque individuel de chaque patient. Résultats : Article 1 - Un total de 407 patients consécutifs référés pour une résonnance magnétique cardiaque pour suspicion de CAVD ont été inclus. De ceux-ci, 66 (16%) ont reçu un diagnostic définitif selon le critère de référence établi pour cette étude: le consensus d’un panel d’experts. Globalement, les critères performent bien avec une sensibilité et spécificité à 92%. Cependant, certains critères tels l’ECG haute amplitude (SAECG) et certains critères reliés à l’histoire familiale ne sont pas discriminants. Le retrait de ces critères pourrait réduire le nombre de faux positifs sans pour autant augmenter le nombre de faux négatifs (net reclassification improvement de 4,3%, p=0,019). De plus, la combinaison des critères électrocardiographiques et de la présence d’arythmies ventriculaires a une sensibilité de 100%, ce qui peut faciliter dans certains cas le dépistage en limitant la nécessité de recourir à l’imagerie. Pour les articles 2 et 3, une base de données incluant des patients avec un diagnostic définitif de CAVD a été assemblée à partir de bases de données provenant de six pays (Canada, États-Unis, Pays-Bas, Suède, Norvège, Suisse). Article 2 - Un total de 528 patients sans histoire antérieure d’arythmies ventriculaires soutenues a été inclus pour développer un modèle de prédiction de risque. De ceux-ci, 146 (27,7%) ont subi un événement arythmique durant un suivi médian de 4,8 ans. Des huit prédicteurs initialement identifiés (âge inférieur au diagnostic, sexe masculin, syncope cardiaque récente, nombre de dérivations avec des inversions des ondes T, fardeau d’extrasystoles ventriculaires (ESV) en 24h, tachycardie ventriculaire non-soutenue et fractions d’éjection des ventricules gauche et droit), sept ont été retenus dans le modèle, excluant seulement la fraction d’éjection du ventricule gauche (FEVG). Le modèle peut distinguer adéquatement entre les patients avec et sans événement (C-index de 0,77) avec un optimisme minimal (courbe de calibration de 0,93). L’utilisation de cet algorithme permettrait de réduire l’utilisation de défibrillateurs implantables de 20% par rapport à l’algorithme du consensus le plus largement utilisé. Article 3 - Une cohorte de 864 patients incluant à la fois ceux avec et sans histoire antérieure d’arythmie ventriculaire soutenue a été assemblée. Durant un suivi médian de 5,75 ans, 93 patients ont eu un épisode d’arythmie rapide selon la définition préalablement établie. Des huit facteurs de risque cités ci-haut, seulement quatre ont été retenus dans le modèle : l’âge plus jeune au diagnostic, sexe masculin, fardeau d’ESV en 24h et nombre de dérivations avec des inversions des ondes T. Fait à noter, les événements antérieurs ne se sont pas avérés prédicteurs d’arythmies potentiellement mortelles subséquentes. Le modèle peut distinguer adéquatement entre les patients avec et sans événement (C-index de 0,74) et présente un optimisme minimal avec une courbe de calibration de 0,95. Conclusion : Bien que les critères diagnostiques en vigueur pour la CAVD aient une performance adéquate, ceux-ci peuvent être simplifiés et améliorés par le retrait de certains de ces critères. L’absence de critères électrocardiographiques combinés et d’arythmies ventriculaires peut exclure une CAVD, ce qui peut en simplifier le dépistage. Chez les patients atteints de CAVD, la prédiction du risque et la sélection des patients pour l’implantation d’un défibrillateur peuvent être facilités grâce à deux modèles complémentaires de prédiction du risque permettant de prédire les événements arythmiques soutenus dans le premier et plus spécifiquement les arythmies ventriculaires potentiellement mortelles dans le deuxième. Ces outils sont particulièrement utiles dans une approche de prise de décision partagée.Introduction: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic pathology resulting in a fibro-fatty replacement predominantly affecting the right ventricle. The diagnosis is complex and is based on a set of clinical criteria. Involvement of the right ventricle predominantly results in ventricular arrhythmias which constitutes the most common presentation but can also lead to the most feared consequence: sudden cardiac death. Predicting and preventing this catastrophic outcome are crucial in the management of this disease. Objectives: This work aims to improve the management of patients with ARVC in two distinct ways. First, by attempting to facilitate the diagnosis by validating the currently used diagnostic criteria. Second by improving risk stratification for sustained ventricular arrhythmias and specifically life-threatening ventricular arrhythmias (LTVA defined as ventricular tachycardia > 250 bpm, ventricular fibrillation, and sudden death) by creating risk prediction models to derive individual risk. Results: Manuscript 1: a total of 407 patients referred for cardiac magnetic resonance for suspected ARVC were consecutively enrolled. Of these, 66 (16%) received a definitive diagnosis of ARVC by the determined endpoint: the consensus of an expert panel. Overall, the criteria performed well with a sensitivity and specificity of 92%. However, certain criteria such as the signal averaged electrocardiogram (SAECG) and certain criteria related to family history failed to discriminate. Removing these criteria could reduce false positives without increasing false negatives (net reclassification improvement of 4.3%, P = 0.019). In addition, the electrocardiographic criteria and the presence of arrhythmia had a sensitivity of 100%, which can facilitate screening in some cases by making imaging optional. For manuscripts 2 and 3, a cohort including patients with a definitive diagnosis of ARVC was assembled from databases in 6 countries (Canada, United States, Netherlands, Sweden, Norway, Switzerland). Manuscript 2: a total of 528 patients with no previous history of sustained ventricular arrhythmias were included to develop a risk prediction model. Of these, 146 (27.7%) had an arrhythmic event during a median follow-up of 4.8 years. Of the eight predictors initially identified (younger age at diagnosis, male sex, recent cardiac syncope, the number of leads with T wave inversions on the ECG, burden of extrasystoles in 24 hours, non-sustained ventricular tachycardia and left and right ventricular ejection fraction), seven were retained in the model, excluding only left ventricular ejection fraction. The model adequately distinguished between patients with and without an arrhythmic event (C-index of 0.77) with minimal optimism (calibration slope of 0.93). Using this prediction model would reduce the use of defibrillators by 20% compared with the most commonly used consensus based on a risk factor approach. Manuscript 3: a cohort including both patients with and without a prior history of ventricular arrhythmia of 864 patients was assembled. During a follow-up of 5.75 years, 93 patients had an LTVA as defined above. Of the 8 risk factors cited above, only 4 were retained in the model: younger age at diagnosis, male sex, burden of extrasystoles in 24 hours and number of leads with T-wave inversions. Importantly, previous events are not predictive of these subsequent life-threatening arrhythmias. The model adequately distinguished between patients with and without an event (C-index of 0.74) with minimal optimism (calibration slope of 0.95). Conclusion: Although the current diagnostic criteria for ARVC perform adequately, they can be simplified and improved by removing underperforming individual criteria. The absence of any ECG criteria and ventricular arrhythmias may rule out ARVC, which may simplify screening. In patients with ARVC, risk prediction and patient selection for a defibrillator can be facilitated by two complementary risk prediction models for sustained arrhythmic events or more specifically for LTVA. These tools are particularly useful in a shared decision-making approach for implantable cardioverter defibrillator implantation

Arrhythmic Risk Stratification in Arrhythmogenic Right Ventricular Cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an heritable cardiomyopathy characterized by a predominantly arrhythmic presentation. It represents the leading cause of sudden cardiac death (SCD) among athletes and poses a significant morbidity treat in the general population. As a causative treatment for ARVC is still not available, the placement of an implantable cardioverter defibrillator (ICD) represent the current cornerstone for SCD prevention in this setting. Thanks to international ARVC-dedicated efforts, significant steps have been achieved in recent years towards an individualized, patient-centered risk stratification approach. A novel risk calculator algorithm estimating the 5 year risk of arrhythmias of patients with ARVC have been introduced in clinical practice and subsequently validated. The purpose of this article is to summarize the body of evidence that has allowed the development of this tool and to discuss the best way to implement its use in the care of an individual patient

Arrhythmic risk stratification in arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable cardiomyopathy characterized by a predominantly arrhythmic presentation. It represents the leading cause of sudden cardiac death (SCD) among athletes and poses a significant morbidity threat in the general population. As a causative treatment for ARVC is still not available, the placement of an implantable cardioverter defibrillator represents the current cornerstone for SCD prevention in this setting. Thanks to international ARVC-dedicated efforts, significant steps have been achieved in recent years towards an individualized, patient-centred risk stratification approach. A novel risk calculator algorithm estimating the 5-year risk of arrhythmias of patients with ARVC has been introduced in clinical practice and subsequently validated. The purpose of this article is to summarize the body of evidence that has allowed the development of this tool and to discuss the best way to implement its use in the care of an individual patient

Comparing clinical performance of current implantable cardioverter-defibrillator implantation recommendations in arrhythmogenic right ventricular cardiomyopathy

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) patients have an increased risk of ventricular arrhythmias (VA). Four implantable cardioverter-defibrillator (ICD) recommendation algorithms are available The International Task Force Consensus (‘ITFC’), an ITFC modification by Orgeron et al. (‘mITFC’), the AHA/HRS/ACC guideline for VA management (‘AHA’), and the HRS expert consensus statement (‘HRS’). This study aims to validate and compare the performance of these algorithms in ARVC. METHODS AND RESULTS: We classified 617 definite ARVC patients (38.5 ± 15.1 years, 52.4% male, 39.2% prior sustained VA) according to four algorithms. Clinical performance was evaluated by sensitivity, specificity, ROC-analysis, and decision curve analysis for any sustained VA and for fast VA (>250 b.p.m.). During 6.4 [2.8–11.5] years follow-up, 282 (45.7%) patients experienced any sustained VA, and 63 (10.2%) fast VA. For any sustained VA, ITFC and mITFC provide higher sensitivity than AHA and HRS (94.0–97.8% vs. 76.7–83.5%), but lower specificity (15.9–32.0% vs. 42.7%-60.1%). Similarly, for fast VA, ITFC and mITFC provide higher sensitivity than AHA and HRS (95.2–97.1% vs. 76.7–78.4%) but lower specificity (42.7–43.1 vs. 76.7–78.4%). Decision curve analysis showed ITFC and mITFC to be superior for a 5-year sustained VA risk ICD indication threshold between 5–25% or 2–9% for fast VA. CONCLUSION: The ITFC and mITFC provide the highest protection rates, whereas AHA and HRS decrease unnecessary ICD placements. ITFC or mITFC should be used if we consider the 5-year threshold for ICD indication to lie within 5–25% for sustained VA or 2–9% for fast VA. These data will inform decision-making for ICD placement in ARVC

Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy: external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator

Aims Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and sudden cardiac death (SCD). In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). This study aimed to externally validate this prediction model in a large international multicentre cohort and to compare its performance with the risk factor approach recommended for implantable cardioverter-defibrillator (ICD) use by published guidelines and expert consensus.Methods and results In a retrospective cohort of 429 individuals from 29 centres in North America and Europe, 103 (24%) experienced sustained VA during a median follow-up of 5.02 (2.05-7.90) years following diagnosis of ARVC. External validation yielded good discrimination [C-index of 0.70 (95% confidence interval-CI 0.65-0.75)] and calibration slope of 1.01 (95% CI 0.99-1.03). Compared with the three published consensus-based decision algorithms for ICD use in ARVC (Heart Rhythm Society consensus on arrhythmogenic cardiomyopathy, International Task Force consensus statement on the treatment of ARVC, and American Heart Association guidelines for VA and SCD), the risk calculator performed better with a superior net clinical benefit below risk threshold of 35%.Conclusion Using a large independent cohort of patients, this study shows that the ARVC risk model provides good prognostic information and outperforms other published decision algorithms for ICD use. These findings support the use of the model to facilitate shared decision making regarding ICD implantation in the primary prevention of SCD in ARVC

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

Aims Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients.Methods and results Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 +/- 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P &lt;0.001).Conclusion Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com).</p

Sudden Cardiac Death Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy: A Multinational Collaboration

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. METHODS: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. RESULTS: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism. CONCLUSIO

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

AIMS: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. METHODS AND RESULTS: Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P < 0.001). CONCLUSION: Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com)