Improving Diagnostic Accuracy for Acute Heart Failure (INDICATE-HF)

Acute heart failure is a common reason for emergency department visits and hospitalization, but the diagnosis can be challenging because of non-specific symptoms and signs. The current diagnostic approach to acute heart failure has modest accuracy, leading to delayed diagnosis and treatment, which associate with worse prognosis. Prior work suggests diagnostic accuracy can be improved with the addition of multiple circulating biomarkers discovered through proteomics, and this study will derive and validate a multi-marker model to improve diagnostic accuracy for acute heart failure in the emergency department.

Study Overview

• Status: Active, not recruiting
• Conditions: Dyspnea; Acute Heart Failure; Dyspnea; Cardiac

Detailed Description

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. The current study is designed to address these limitations. Recent advances in "omics" enable novel biomarker discovery on a larger scale and investigations less "biased" by existing knowledge. The overarching hypothesis of this study is that a multi-marker model incorporating novel proteins discovered with plasma proteomics improves diagnostic accuracy for acute HF. In a preliminary proof of concept study plasma proteomics was utilized 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. These 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. The specific aims of this study are to: 1) discover a 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, and 3) test performance of the multi-marker model in a prospective validation cohort. In aim 1, existing plasma samples from ~900 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, an existing prospective observational cohort, EMROC-AHF, will be utilized to derive the multi-marker model in ~900 patients who presented to the ED with acute dyspnea. In aim 3, from four EDs in Detroit, MI and Nashville, TN a new sample will prospectively recruit ~1,000 patients presenting with acute dyspnea and adjudicate the presence of acute HF by cardiologist panel review. Given the burden of HF, the frequency of inaccurate diagnosis and its adverse consequences, this study will address a significant unmet need by improving diagnostic accuracy for acute HF.

• Study Type: Observational
• Enrollment (Estimated): 2800

Contacts and Locations

Study Locations

• United States
  • Tennessee
    • Nashville, Tennessee, United States, 37232
      • Vanderbilt University Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Adults (18 years or older) presenting with the chief complaint of dyspnea and in whom the ED physician is considering the diagnosis of acute HF, based on an order for measurement of NP levels (either BNP or NT-proBNP) or a chest x-ray will be included. Patients whose dyspnea is due to trauma, those who are on chronic hemodialysis, and patients whose primary presentation is consistent with acute coronary syndrome will be excluded.

Description

For enrollment into the prospective cohort for Outcome 3.

Inclusion Criteria:

1. Willing to adhere to the study protocol
2. Able to provide written consent
3. English or Spanish speaking
4. Adult, defined as 18 years or older
5. Primary reason for presentation to the ED is dyspnea
6. ED physician is considering a diagnosis of HF, defined by ordering a NP test and/or a chest x-ray

Exclusion Criteria:

1. History of end-stage renal disease for which hemodialysis is needed
2. Dyspnea due to primary presentation of an acute coronary syndrome or trauma

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
Aim 1/Outcome 1; Secondary analysis of frozen plasma samples from the existing STRATIFY cohort of patients with and without acute heart failure presenting to emergency departments. n= ~900
Aim2/Outcome 2; Secondary analysis of frozen plasma samples from the existing EMROC cohort of patients with and without acute heart failure presenting to emergency departments. n= ~900
Aim 3/Outcome 3; Prospective recruitment of approximately 1000 patients with and w/o acute heart failure presenting to emergency departments.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Biomarker Discovery	Define the multi-marker panel of 21 proteins that may improve diagnostic accuracy for acute heart failure	Enrollment
Model derivation for diagnosing acute HF	derive a model for diagnosing acute HF incorporating the 21-biomarker panel from outcome 1	Enrollment
Model validation for diagnosing acute HF	test performance of the multi-marker model (from outcome 2) in a prospective validation cohort	Enrollment

Collaborators and Investigators

• Sponsor: Vanderbilt University Medical Center
• Collaborators: Wayne State University
• Investigators: Principal Investigator: Deepak Gupta, MD, MSCI, Vanderbilt University Medical Center

Study record dates

Study Major Dates

• Study Start (Actual): August 31, 2021
• Primary Completion (Estimated): June 30, 2025
• Study Completion (Estimated): June 30, 2025

Study Registration Dates

• First Submitted: May 4, 2021
• First Submitted That Met QC Criteria: May 12, 2021
• First Posted (Actual): May 13, 2021

Study Record Updates

• Last Update Posted (Actual): June 4, 2024
• Last Update Submitted That Met QC Criteria: June 2, 2024
• Last Verified: June 1, 2024

More Information

Terms related to this study

• Keywords: heart failure; acute heart failure
• Additional Relevant MeSH Terms: Heart Diseases; Cardiovascular Diseases; Respiratory Tract Diseases; Respiration Disorders; Signs and Symptoms, Respiratory; Heart Failure; Dyspnea
• Other Study ID Numbers: 210941

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No