# Improving Diagnostic Accuracy for Acute Heart Failure > **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2021 · $2,349,037 ## 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:** 10209800 - **Project number:** 1R01HL153607-01A1 - **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER - **Principal Investigator:** SEAN PATRICK COLLINS - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $2,349,037 - **Award type:** 1 - **Project period:** 2021-05-15 → 2025-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10209800 ## Citation > US National Institutes of Health, RePORTER application 10209800, Improving Diagnostic Accuracy for Acute Heart Failure (1R01HL153607-01A1). Retrieved via AI Analytics 2026-06-24 from https://api.ai-analytics.org/grant/nih/10209800. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*