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Characterizing apparent treatment resistant hypertension in the United States: insights from the All of Us Research
Mona Alshahawey1,2, Eissa Jafari1,3, Steven M Smith4
1Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, United States.
Background:
Hypertension (HTN) remains a significant public health concern and the primary modifiable risk factor for cardiovascular disease, which is the leading cause of death in the United States. We applied our validated HTN computable phenotypes within the All of Us Research Program to uncover prevalence and characteristics of HTN and apparent treatment-resistant hypertension (aTRH) in United States.
Methods:
Within the All of Us Researcher Workbench, we built a retrospective cohort (January 1, 2008-July 1, 2023), identifying all adults with available age data, at least one blood pressure (BP) measurement, prescribed at least one antihypertensive medication, and with at least one SNOMED "Essential hypertension" diagnosis code.
Results:
We identified 99 461 participants with HTN who met the eligibility criteria. Following the application of our computable phenotypes, an overall population of 81 462 were further categorized to aTRH (14.4%), stable-controlled HTN (SCH) (39.5%), and Other HTN (46.1%). Compared to participants with SCH, participants with aTRH were older, more likely to be of Black or African American race, had higher levels of social deprivation, and a heightened prevalence of comorbidities such as hyperlipidemia and diabetes. Heart failure, chronic kidney disease, and diabetes were the comorbidities most strongly associated with aTRH. β-blockers were the most prescribed antihypertensive medication. At index date, the overall BP control rate was 62%.
Discussion And Conclusion:
All of Us provides a unique opportunity to characterize HTN in the United States. Consistent findings from this study with our prior research highlight the interoperability of our computable phenotypes.
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