# Development of a Multi-scale closed loop model for hemorrhagic shock: a platform to assess REBOA performance

> **NIH NIH R01** · WAKE FOREST UNIVERSITY HEALTH SCIENCES · 2024 · $51,604

## Abstract

Project Summary:
 Hemorrhagic shock is the leading cause of early mortality in people aged 1-44 years old, following a
traumatic injury. A significant proportion of these early fatalities are associated with non-compressible truncal
hemorrhage (NCTH). Endovascular approaches such as Resuscitative Endovascular Balloon Occlusion of the
Aorta (REBOA) and Partial Resuscitative Endovascular Balloon Occlusion of the Aorta (pREBOA) have
evolved as an effective way to manage NCTH. However, the optimal implementation (i.e., occlusion size,
timing, and duration of device deployment) remains largely unknown since hemostatic control must be
maintained. Additionally, little is known about how the use of an endovascular hemorrhage control device alters
other aspects of resuscitation and critical care management, such as total pressor and fluid requirements.
 To address this knowledge gap, this diversity supplement project seeks to: (1) examine the impact of
partial and complete aortic occlusion on the effectiveness of resuscitation as measured by the total pressor
and crystalloid fluid requirements and (2) exploit machine learning approaches to identify early hemodynamic
patterns that are associated with hypoperfusion and inadequate resuscitation. Dr. Gomez has proposed a
detailed mentoring and training plan that will provide a strong foundation in research development and
grantsmanship, translational science, and quantitative analysis/modelling through formal didactic training,
workshops, conferences, research seminars beyond the experiences gathered through the conduct of
proposed research aims in this supplement and the parent grant. The environment at Wake Forest University
School of Medicine is excellent for this research with access to resources through the PI’s lab, the Center for
Translational Science Institute and Center for Artificial Intelligence that will provide supplementary professional
training in translational research and machine learning.
 The long-term goal of this project is to identify key hemodynamic and temporal patterns that are
associated with inadequate resuscitation and hypoperfusion such that improved resuscitation and vasopressor
management can be delivered to critically injured patients. Understanding how endovascular devices such as
REBOA and pREBOA alter vascular response and resuscitation across different hemorrhage levels will allow
us to better understand how to implement these devices into patient care, including the refinement of
automated critical care platforms. This proposed project will certainly aid in propelling Dr. Gomez’s carer in
academic medicine and translational science.

## Key facts

- **NIH application ID:** 10989204
- **Project number:** 3R01HL162633-02S1
- **Recipient organization:** WAKE FOREST UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Elaheh Rahbar
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $51,604
- **Award type:** 3
- **Project period:** 2024-03-08 → 2024-03-09

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10989204

## Citation

> US National Institutes of Health, RePORTER application 10989204, Development of a Multi-scale closed loop model for hemorrhagic shock: a platform to assess REBOA performance (3R01HL162633-02S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10989204. Licensed CC0.

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