# Identifying pre-sepsis opportunities for early, targeted intervention

> **NIH NIH R35** · KAISER FOUNDATION RESEARCH INSTITUTE · 2020 · $388,458

## Abstract

PROJECT SUMMARY
Sepsis kills an estimated 6 million people worldwide every year. Sepsis also contributes to as many as 50% of
US hospital deaths. Early treatment is the only universally recognized modifiable factor for improving sepsis
mortality. Thus, current treatment guidelines focus heavily on early sepsis care immediately following hospital
presentation. However, key national and global health authorities also emphasize the need to identify even
earlier pre-hospital opportunities to predict, recognize, or treat sepsis. Little is known about the presentation,
pace, and profile of infection in pre-sepsis patients. Understanding these characteristics could enable novel
pre-hospital approaches designed to mitigate, or even prevent, sepsis. Using an innovative translational
informatics approach, this project will identify and characterize pre-sepsis opportunities for early, targeted
intervention. To achieve this goal, my laboratory leverages comprehensive electronic medical record data,
advanced informatics methods, and the evaluation of novel care programs. Through this proposal, we will
develop and validate prediction models that identify patients in common pre-hospital settings at the highest risk
of impending sepsis, organ failure, and mortality. In the process, we will characterize the sepsis-related
symptom profiles that portend the highest risk of adverse outcomes. Findings will have broad and immediate
implications for patients, clinicians, and health systems. These results will also inform the design of sepsis
public health programs and future randomized clinical trials aimed at improving outcomes for this devastating
condition.

## Key facts

- **NIH application ID:** 9987339
- **Project number:** 5R35GM128672-03
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** Vincent Liu
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $388,458
- **Award type:** 5
- **Project period:** 2018-08-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9987339

## Citation

> US National Institutes of Health, RePORTER application 9987339, Identifying pre-sepsis opportunities for early, targeted intervention (5R35GM128672-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9987339. Licensed CC0.

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