# Strategies to Innovate EmeRgENcy Care Clinical Trials Network ("SIREN") - Supplement

> **NIH NIH U24** · UNIVERSITY OF CINCINNATI · 2022 · $71,981

## Abstract

Project Summary and Abstract
This supplement requests support of effort for key individuals that will allow the University of
Pittsburgh site for the Strategies to Innovate Emergency Care Clinical Trials Network (SIREN) to
continue operations as a Hub for recruiting participants into emergency care research.
Supplemental support is requested to maintain operations between the end of regular funding
for the first 5 years of SIREN and start of the second 5 years of SIREN. Uninterrupted support
of the Hub will ensure successful enrollment of participants into the ongoing SIREN trials;
ICECAP, BOOST-3, and Peds-ICECAP. We will continue to support the ancillary studies for
these trials: PRECICECAP, Bio-BOOST and electro-BOOST. Our specific Aims remain: 1.
Provide administrative structure to rapidly implement and enroll in clinical trials of emergency
treatments. 2. Minimize time, cost and regulatory barriers to multicenter clinical trials in
emergency settings. 3. Explore innovative strategies to increase identification, recruitment, and
consent in emergency treatment trials. 4. Explore innovative strategies to increase quality of
emergency care data and to ensure retention of subjects enrolled in emergency settings.

## Key facts

- **NIH application ID:** 10622935
- **Project number:** 3U24NS100688-05S1
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** Gregory J. Fermann
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $71,981
- **Award type:** 3
- **Project period:** 2017-07-15 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10622935

## Citation

> US National Institutes of Health, RePORTER application 10622935, Strategies to Innovate EmeRgENcy Care Clinical Trials Network ("SIREN") - Supplement (3U24NS100688-05S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10622935. Licensed CC0.

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