Better data in, better research out: the data problem in resistant hypertension research

Better data in, better research out: the data problem in resistant hypertension research. Download PDF Subjects Genetics research Hypertension Defined to fail Resistant hypertension (RH) remains one of the most heterogeneous and inconsistently defined conditions in cardiovascular medicine. Despite the increased risk of major adverse cardiovascular events and the accompanying healthcare burden, the epidemiology, underlying biology, and optimal management of RH are poorly understood [ 1, 2 ].

One of the main reasons for this is limited data availability: inconsistent drug reporting, absent adherence data, and underpowered cohorts make solid phenotyping near impossible [ 3, 4 ]. Without a well-defined, large-scale phenotype, genomic discovery stalls before it can start. As a result, the genetic architecture of RH remains a largely unexplored landscape.

The marked difference in reported prevalence of RH across the globe underpins how poorly understood RH is. Estimates vary widely, ranging from 5% to 30% across global hypertension guidelines, and accompanying treatment strategies are often limited to the addition of further antihypertensive drugs [ 5, 6 ]. Embedded within this variability is a more fundamental issue: a substantial proportion of RH reflects pseudo-resistance rather than true treatment resistance [ 6 ].

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Medical Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always consult with qualified healthcare professionals for medical decisions and treatment options.