# Hypertension Prediction and Identification in All of Us

> **NIH NIH R03** · UNIVERSITY OF FLORIDA · 2023 · $152,500

## Abstract

PROJECT SUMMARY
This application aims to use existing data within the All of Us Researcher Workbench to improve our ability to
identify hypertension (HTN) patients at increased risk for apparent treatment resistant hypertension (aTRH)
and adverse cardiovascular outcomes. Resistant hypertension describes a subset of hypertensive individuals
with uncontrolled blood pressure (BP) despite the use of three or more antihypertensive medications, or BP
control that requires four or more antihypertensive medications. The term aTRH is used for resistant
hypertension when pseudoresistance (e.g. medication nonadherence, white coat effect) cannot be excluded.
The prevalence of aTRH was recently estimated at ~17-19% among adults taking antihypertensive
medications. HTN is a major risk factor for adverse cardiovascular outcomes such as acute myocardial
infarction, stroke, and heart failure. Additionally, when compared to controlled hypertension patients, patients
with aTRH are at increased risk for adverse cardiovascular outcomes, target organ damage, and all-cause
mortality. Although there are numerous first-line antihypertensive drugs to lower blood pressure and ultimately
prevent adverse cardiovascular outcomes, there is great inter-patient variability in antihypertensive drug
response. It is poorly understood why patients respond differently to the same drug, why some patients
develop aTRH, and why some patients experience adverse cardiovascular outcomes. Our central hypothesis
is that HTN patients and subpopulations at increased risk for aTRH and adverse cardiovascular outcomes
associated with HTN can be identified through clinical factors, biochemical factors, genomic factors, and
patient reported data. To test our central hypothesis we will complete the following Specific Aims: 1)
Characterize aTRH and adverse cardiovascular outcomes in HTN patients by health care institutions, urban
versus rural areas, and geographic regions, using longitudinal electronic health record (EHR)-based data, and
2) Identify early signs of aTRH and adverse cardiovascular outcomes in HTN patients by health care
institutions, urban versus rural areas, and geographic regions, using EHR-based data, genomic data, and data
from surveys and wearables. To achieve these aims, we will utilize existing data from the All of Us Researcher
Workbench. The All of Us Research Program is enrolling a diverse group of persons in the United States, and
including multiple types of real-world data (e.g. EHR, demographic, wearables, patient surveys, genomic). We
will deploy our validated HTN algorithms to determine observed rates of HTN, aTRH, and adverse
cardiovascular outcomes. We will identify characteristics of aTRH and adverse cardiovascular outcomes in
HTN patients. We will also use multivariable regression analyses and machine-learning models to identify
predictors (EHR-based, genomic, patient reported) of aTRH and adverse cardiovascular outcomes. We will
examine characteristics and predictor...

## Key facts

- **NIH application ID:** 10797850
- **Project number:** 1R03HL172123-01
- **Recipient organization:** UNIVERSITY OF FLORIDA
- **Principal Investigator:** Caitrin W McDonough
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $152,500
- **Award type:** 1
- **Project period:** 2023-09-10 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10797850

## Citation

> US National Institutes of Health, RePORTER application 10797850, Hypertension Prediction and Identification in All of Us (1R03HL172123-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10797850. Licensed CC0.

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