Analyzing a decade of Czech national health registry data (2015–2024) covering the full population, a claims-based staging algorithm classified 27.8% of Czechs as Stage A heart failure (HF) and 8.2% as Stage B in 2024. Age-standardized prevalence rose 9.5% and 19.2% respectively — increases exceeding what population aging alone explains. One-year mortality climbed steeply: 0.69% at Stage A, 1.69% at Stage B, 3.06% at Stage C, and 7.27% at Stage D. Critically, over 95% of 52,172 incident clinical HF cases had previously met administrative criteria for preclinical disease.
This preprint, not yet peer-reviewed, offers one of the largest population-scale mappings of the full HF continuum attempted using routine administrative data. Most HF epidemiology focuses on symptomatic patients, leaving the preclinical iceberg largely unmeasured. By demonstrating that nearly all clinical cases were preceded by detectable preclinical stages, the data strengthen the case for earlier surveillance and intervention windows. The 10-fold mortality gradient from Stage A to Stage D provides compelling population-level evidence that staging genuinely stratifies risk. Limitations include the inherent imprecision of ICD-10 and claims-based classification — administrative codes cannot replicate biomarker or imaging-confirmed staging — and Czech-specific healthcare patterns may limit generalizability. Still, if validated in other national datasets, this scalable framework could reshape how health systems identify and prioritize prevention in the vast, largely invisible preclinical HF population.
