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.Conclusions:LTVA events in patients with ARVC can be predicted by a novel simple prediction model using only 4 clinical predictors. Prior sustained VA and the extent of functional heart disease are not associated with subsequent LTVA events.Cardiolog

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)

Metamodelling Messages Conveyed in Five Statistical Mechanical Textbooks from 1936 to 2001

Modelling is a significant aspect of doing physics and it is important how this activity is taught. This paper focuses on the explicit or implicit messages about modelling conveyed to the student in the treatments of phase transitions in statistical mechanics textbooks at beginning graduate level. Five textbooks from the 1930s to the present are analysed with respect to their messages about the following issues: What is a good model? What is the purpose of modelling? What does it mean to understand a natural phenomenon? It is argued that these texts give the student quite different perceptions of these issues and thus what of it means to do physics