Predicting sudden cardiac death in genetic heart disease

Trans-Atlantic Differences in Approach to Sudden Death Prevention in Patients With Hypertrophic Cardiomyopathy

The American approach to predicting sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy diverges from the European method in that it relies on major risk factors independently justifying the implantation of an implantable cardioverter-defibrillator for primary prevention, whereas the European approach uses a mathematical equation to estimate a 5-year risk percentage. The aim of this review is to outline the differences between the American and European guidelines and to show how they have arisen. Furthermore, it will provide insight into the future of SCD risk prediction in patients with hypertrophic cardiomyopathy. The American SCD risk prediction method has high sensitivity but limited specificity, whereas the European method has the opposite. These differences in sensitivity and specificity likely contribute to the fact that primary prevention implantable cardioverter-defibrillator utilization is twofold higher in the United States. It is highly likely that new insights and new imaging modalities will enhance prediction models in the near future. Genotyping could potentially assume a significant role. Left ventricular global longitudinal strain was recently shown to be an independent predictor of SCD. Furthermore, after late gadolinium enhancement, additional cardiac magnetic resonance techniques such as T1 mapping and diffusion tensor imaging are showing encouraging outcomes in predicting SCD. Ultimately, it is conceivable that integrating diverse morphological and genetic characteristics through deep learning will yield novel insights and enhance SCD prediction methods.

Re-evaluating the Incidence and Prevalence of Clinical Hypertrophic Cardiomyopathy: An Epidemiological Study of Olmsted County, Minnesota

OBJECTIVE

To contemporaneously reappraise the incidence-rate, prevalence, and natural history of hypertrophic cardiomyopathy (HCM) in Olmsted County, Minnesota, from 1984 to 2015.

PATIENTS AND METHODS

A validated medical-record linkage system collecting information for residents of Olmsted County was used to identify all cases of HCM between January 1, 1984, and December 31, 2015. After adjudication of records from Mayo Clinic and Olmsted Medical Center, data relating to diagnoses and outcomes were abstracted. The calculated incidence rate and prevalence were standardized to the US 1980 White population (age- and sex-adjusted) and compared with a prior study examining the years 1975-1984.

RESULTS

Two hundred seventy subjects with HCM were identified. The age- and sex-adjusted incidence rate was 6.6 per 100,000 person-years, and the point prevalence of HCM on January 1, 2016, was 89 per 100,000 population. The incidence rate and point prevalence of HCM on January 1, 2016, standardized to the US 1980 White population (age- and sex-adjusted), were 6.7 (95% CI, 7.1 to 8.8) per 100,000 person-years and 81.5 per 100,000 population, respectively. The incidence rate of HCM increased each decade since the index study. Individuals with HCM had a higher overall standardized mortality rate than the general population with an observed to expected HR of 1.44 (95% CI, 1.21 to 1.71; P<.001) which improved by each decade.

CONCLUSION

The incidence and prevalence of HCM are higher than rates reported from a prior study in the same community examining the years 1975-1984, but lower than other study cohorts. The risk of mortality in HCM remains higher than expected, albeit with improvement in rates of mortality observed each decade during the study period.

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.