# Treatment implications of heterogeneity in acute respiratory failure risk among patients with hospital-onset sepsis

> **NIH NIH K01** · UNIVERSITY OF COLORADO DENVER · 2024 · $167,832

## Abstract

Project Summary/Abstract
Patients with hospital-onset sepsis (HOS) frequently receive delayed treatment and have nearly 3-fold greater
risk of acute respiratory failure (ARF) and death than patients with community-onset sepsis, yet remain an
understudied population. The current absence of data characterizing heterogeneity in clinical presentation,
ARF risk, and treatment benefit, presents a critical barrier to designing interventions that improve treatment
timing and prevent ARF for the most vulnerable patients. The candidate’s long-term career goal is to build an
independently funded research program advancing precision approaches to HOS and ARF treatment. As an
essential next step, the overall objective of this project is to create new knowledge about HOS heterogeneity
and progression to ARF to inform the future development of treatment strategies tailored to patients’ individual
organ failure risks and anticipated benefits from specific interventions. In preliminary studies, the candidate has
built a retrospective cohort of HOS patients admitted to five organizationally diverse hospitals of an academic
health system, and preliminary analyses have demonstrated an association between timing of antimicrobial
administration for HOS and progression to ARF. This project will expand this cohort in order to complete the
following aims: 1) identify latent phenotypes of HOS illness presentation using consensus k-means clustering
accounting for informative missingness and including baseline patient factors, measures of organ dysfunction
and severity of illness, and measures of degree and rapidity of clinical deterioration, 2) develop a novel model
to predict ARF among patients with HOS using super learner machine learning predictive modeling including
patient factors and physiologic data at sepsis onset; and 3) assess the association of antimicrobial treatment
delays with progression to ARF among patients with HOS using inverse probability of treatment weighting to
account for confounding by indication, and estimate heterogeneity of this effect by underlying ARF risk. To
successfully complete these aims and acquire the necessary skills to transition to research independence, the
candidate has developed a training plan that includes formal didactic training, research seminars, works in
progress, and scientific meeting presentations focused on methods in machine learning, predictive modeling,
and causal inference. Her career development will be supported by close guidance from her mentorship team
who have deep content and methodologic expertise in relevant fields for this work.

## Key facts

- **NIH application ID:** 10886878
- **Project number:** 1K01HL169843-01A1
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Jennifer Claire Ginestra
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $167,832
- **Award type:** 1
- **Project period:** 2024-05-01 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10886878

## Citation

> US National Institutes of Health, RePORTER application 10886878, Treatment implications of heterogeneity in acute respiratory failure risk among patients with hospital-onset sepsis (1K01HL169843-01A1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10886878. Licensed CC0.

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