# Gastrointestinal Safety of Antithrombotic Drug Regimens

> **NIH AHRQ R01** · MAYO CLINIC ARIZONA · 2020 · $394,737

## Abstract

ABSTRACT
Patients with atrial fibrillation, post-acute coronary syndrome and venous thromboembolism are
prescribed antithrombotic drugs (antiplatelet agents and oral anticoagulants) in dual and triple
combinations. These drugs independently cause gastrointestinal bleeding (GIB) from mucosal
defects or vascular abnormalities of the gastrointestinal tract. Cardiac patients are the fastest
growing at-risk group due to the rapidly aging US population, their high-burden of co-morbidity,
frequent antithrombotic polypharmacy and prescription of new antithrombotic drugs with higher
incidence of GI adverse events. The real-world GIB risk of antithrombotic agents used in
combination in a diverse cardiac population has yet to be characterized. Furthermore, we have
previously demonstrated poor performance of existing risk scores (HAS-BLED, CHA2DS2-VASC
etc.) for the prediction of non- warfarin antithrombotic drug bleeding; scores frequently used in
the clinical setting despite their inaccuracy. Absence of knowledge regarding the real-world risk
of antithrombotic-GIB, and the inability to accurately predict which patients will bleed, hampers
patient counselling regarding a frequently occurring adverse event which is known to cause
morbidity and mortality among cardiac patients. We propose to fill this knowledge gap by
quantifying GIB risk in a large, geographically diverse cohort of elderly and non-elderly cardiac
patients with atrial fibrillation, venous thromboembolism or post-acute coronary syndrome. GIB
associated with antithrombotic drug combinations will be stratified by underlying cardiac
conditions; incidence rates (events/100 patient-years) and propensity-matched Cox proportional
models (with 95% confidence intervals) will be used to estimate outcome. We will examine
heterogeneity of safety effects related to age, chronic co-morbidity, and hepatic or renal
dysfunction. Machine learning techniques will then be used to derive and validate a highly
sensitive algorithm for the prediction of antithrombotic-related GIB. Discovery of such an
algorithm is the first step in the future application of a predictive model in any evidence-based
clinical delivery platform, such as a decision rule or risk calculator.

## Key facts

- **NIH application ID:** 9916670
- **Project number:** 5R01HS025402-04
- **Recipient organization:** MAYO CLINIC ARIZONA
- **Principal Investigator:** NEENA S ABRAHAM
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2020
- **Award amount:** $394,737
- **Award type:** 5
- **Project period:** 2017-07-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9916670

## Citation

> US National Institutes of Health, RePORTER application 9916670, Gastrointestinal Safety of Antithrombotic Drug Regimens (5R01HS025402-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9916670. Licensed CC0.

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