# Improving Diagnostic Accuracy for Acute Heart Failure

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2022 · $1,352,224

## Abstract

PROJECT SUMMARY/ABSTRACT
Acute heart failure (HF) is highly morbid, lethal, and costly. It is a difficult diagnosis to make given its symptoms
and signs overlap with other cardiac and non-cardiac conditions. In the emergency department (ED),
misdiagnosis of acute HF is common and associated with adverse outcomes. Biomarker testing can facilitate
accurate diagnosis; however, natriuretic peptides (NP) are the only guideline recommend biomarker of HF for
diagnostic testing, and are better for ruling-out, rather than ruling-in, acute HF. Even with NP testing, in
contemporary clinical practice misdiagnosis of acute HF still occurs in 10 to 45% of patients presenting to the
ED with dyspnea. Clinical prediction models including multiple biomarkers hold promise for improving
diagnostic accuracy. The few prior studies investigating a multiple biomarker approach for diagnosing acute HF
were limited by constraint to highly correlated markers from known biologic pathways, relatively small sample
sizes, lack of inclusion of all a priori selected biomarkers into a single model, and absence of validation
cohorts. Our study design addresses these limitations. Recent advances in “omics” enable novel biomarker
discovery on a larger scale and investigations less “biased” by existing knowledge. Thus, our overarching
hypothesis is a multi-marker model incorporating novel proteins discovered with plasma proteomics improves
diagnostic accuracy for acute HF. In preliminary work, we performed a proof of concept study utilizing plasma
proteomics to discover a multi-marker panel of 21 biomarkers which improved diagnostic accuracy for acute
HF beyond current clinical practice using clinical data and NP levels. Our promising preliminary data motivate
broader discovery in a larger sample size with subsequent derivation and validation of a multi-marker model for
diagnosing acute HF in independent samples of adequate size. Our specific aims are to: 1) expand the
discovery cohort and refine the multi-marker panel of 21 biomarkers to improve diagnostic accuracy for acute
HF, 2) derive a model for diagnosing acute HF incorporating the 21-biomarker panel, 3) test performance of
the multi-marker model in a prospective validation cohort, and 4) assess the incremental value of the multi-
marker model for diagnosing acute HF. In aim 1, existing plasma samples from 989 patients will be used to
assay 925 proteins to discover a smaller set of novel biomarkers most strongly associated with an adjudicated
acute HF diagnosis. In aim 2, we will utilize an existing prospective observational cohort, EMROC-AHF, to
derive the multi-marker model in 1,000 patients who presented to the ED with acute dyspnea. In aim 3, from
four EDs in Detroit, MI and Nashville, TN we will prospectively recruit a new sample of 1,000 patients
presenting with acute dyspnea and adjudicate the presence of acute HF by cardiologist panel review. In aim 4,
we will compare our multi-marker model against the current clinical ...

## Key facts

- **NIH application ID:** 10405617
- **Project number:** 5R01HL153607-02
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** SEAN PATRICK COLLINS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,352,224
- **Award type:** 5
- **Project period:** 2021-05-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10405617

## Citation

> US National Institutes of Health, RePORTER application 10405617, Improving Diagnostic Accuracy for Acute Heart Failure (5R01HL153607-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10405617. Licensed CC0.

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