Geographic variation in the diagnosis of cardiomyopathies in a universal healthcare system: a nationwide study of hypertrophic and arrhythmogenic right ventricular cardiomyopathy in Denmark

Scritto il 25/09/2026
da Priya Bhardwaj

Open Heart. 2026 Sep 25;13(2):e004493. doi: 10.1136/openhrt-2026-004493.

ABSTRACT

BACKGROUND: In Denmark, hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular cardiomyopathy (ARVC) are primarily diagnosed and managed in specialised inherited cardiac disease clinics, making them suitable for registry-based studies of diagnostic patterns. Both conditions are associated with substantial morbidity, yet nationwide data on prevalence and geographic variation remain limited. We aimed to describe the prevalence and regional distribution of HCM and ARVC in Denmark.

METHODS: In this nationwide registry-based study, we included individuals with a diagnosis of HCM or ARVC in Denmark as of 1 July 2024, matched 1:10 to the general population by age and sex. Data on comorbidities, socioeconomic factors and geographic distribution were obtained from national registries. Municipalities were classified by degree of urbanisation.

RESULTS: A total of 4705 individuals were identified, of whom 90% had HCM and 10% had ARVC. The prevalence of HCM was 71 per 100 000 individuals, while ARVC prevalence was 8.1 per 100 000. Compared with the Capital Region, all other regions had significantly higher prevalence of HCM, ranging from 61.4 per 100 000 in the Capital Region to 80.3 per 100 000 in Zealand and was significantly higher in thinly populated than densely populated areas. In contrast, ARVC prevalence showed no significant regional variation and no significant urban-rural differences. Socioeconomic characteristics were broadly similar to the general population.

CONCLUSIONS: In Denmark, HCM shows significant geographic and urban-rural variation in diagnosed prevalence, whereas ARVC is more uniformly distributed. These findings suggest that healthcare organisation and referral patterns may contribute to variation in disease detection.

PMID:42791014 | DOI:10.1136/openhrt-2026-004493