# Risk-based Patient Monitoring for Pediatric Cardiac Patients

> **NIH NIH R44** · ETIOMETRY, LLC · 2020 · $999,708

## Abstract

Abstract
 During a successful Phase 2 effort, Etiometry collaborated with multiple world-class
pediatric centers to develop, validate, and deploy novel analytics that combine multiple
physiologic data streams into a probabilistic assessment of inadequate oxygen delivery to
critically ill patients. The analytics were integrated into the Etiometry Platform with the goal of
improving physician situational awareness and preventing adverse outcomes in post-surgical
pediatric cardiac patients in the ICU. During this time the platform and the analytics received
FDA 510(k) clearance and were deployed in six pediatric Cardiac Intensive Care Units (CICUs).
The Phase 2B effort will build on these achievements by expanding the platform’s capabilities
and respective FDA cleared indications. The Etiometry Platform will integrate the new analytics
into formal ICU patient care protocols that will be evaluated in a multi-center multi-arm
adaptive randomization clinical trial. If successful, the results of will be used to support FDA
clearance with specific claims of clinical effectiveness. The ultimate objective of the proposed
SBIR effort will be demonstrate that the clinical analytics can significantly affect clinical
outcomes of critically ill pediatric patients.

## Key facts

- **NIH application ID:** 9931264
- **Project number:** 5R44HL117340-07
- **Recipient organization:** ETIOMETRY, LLC
- **Principal Investigator:** Dimitar Valeriev Baronov
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $999,708
- **Award type:** 5
- **Project period:** 2012-07-13 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9931264

## Citation

> US National Institutes of Health, RePORTER application 9931264, Risk-based Patient Monitoring for Pediatric Cardiac Patients (5R44HL117340-07). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9931264. Licensed CC0.

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