Blue Protocol and Eko Artificial Intelligence Are Best (BEA-BEST) (BEA-BEST)

This is an observational study that will be enrolling University of Louisville patients who present to the Emergency Department in Acute Respiratory Failure. This study will be to determine if the addition of Eko AI-assisted lung auscultation examination to a standard of care Pulmonary POCUS + assists with acute respiratory failure diagnosis.

Study Overview

• Status: Recruiting
• Conditions: Acute Respiratory Failure
• Intervention / Treatment: Device: Auscultation

Detailed Description

Once identified and consented, the subject will undergo both POCUS and AI-assisted lung auscultation using an Eko CORE stethoscope. The POCUS protocol described here is the standard of care for patients who present in acute respiratory failure to the Emergency Room and both groups will receive this standardized care during the study.

Upon hospital discharge, the final discharge diagnosis will be used as the ground truth for assessing the accuracy of the POCUS protocol. The POCUS exam and the EkoAI exam may be performed wherever the subject is located in the hospital when first enrolled in the study. If possible, both exams should be performed immediately, in either order. They will be performed by the same examiner.

Both the POCUS and the EkoAI exam will be analysed by an investigator blinded to the final diagnosis.

• Study Type: Observational
• Enrollment (Estimated): 100

Contacts and Locations

• Study Contact: Name: Andrea M Reyes Vega, M.D.; Phone Number: 5028528884; Email: a0reye02@louisville.edu
• Study Contact Backup: Name: Rodrigo Cavallazzi, M.D.; Email: rodrigo.cavallazzi@louisville.edu

Study Locations

• United States
  • Kentucky
    • Louisville, Kentucky, United States, 40202
      • Recruiting
      • University of Louisville
      • Contact: Andrea Reyes, MD; Phone Number: 5028528884; Email: andrea.reyesvega@louisville.edu
      • Contact: Rodrigo Cavallazzi, MD; Phone Number: 5028525841; Email: r0cava01@louisville.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 100 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients 18years and older, presenting to the Emergency Department in acute respiratory failure.

These patients may or may not have a diagnosis of chronic lung disease. It may be necessary to enroll more than 100 subjects in order to achieve 100 completed datasets.

Description

Inclusion Criteria:

• Adults aged 18 years or older presenting to the ED or admitted to the hospital within 12 hours of enrollment
• Acute respiratory failure defined as new onset shortness of breath initiated within the last 7 days, and new or increasing need for oxygen therapy
• The patient or patient's legal health care proxy consents to participation

Exclusion Criteria:

Unwillingness to consent

• Patients with trauma as the cause of ARF
• Patients with pneumothorax as the cause of ARF
• Inability to perform pulmonary POCUS or lung auscultation (e.g. dressing on the chest)
• Unwilling or unable to complete the minimum of 12 lung sound stethoscope recordings.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Acute Respiratory failure; Patients presenting to the Emergency Department in acute respiratory failure. These patients may or may not have a diagnosis of chronic lung disease.	Device: Auscultation; This study will be to determine if the addition of Eko AI-assisted lung auscultation examination to a standard of care Pulmonary POCUS + assists with acute respiratory failure diagnosis.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Measure the accuracy of POCUS for the diagnosis of acute respiratory failure	POCUS consists of an ultrasound examination at bedside. We will perform lung ultrasound and the pattern of lung ultrasound will be used to diagnose the cause of acute respiratory failure. The reference standard will be the the final diagnosis by the clinician. The accuracy measures will include sensitivity, specificity, positive predictive value, and negative predictive value.	2 years
Measure the accuracy of POCUS plus Eko for the diagnosis of acute respiratory failure. AI-assisted lung auscultation for the diagnosis of the case of acute respiratory failure.	POCUS was described above. Ekos consists of a digital stethoscope. The lung auscultation pattern will be used to determine the cause of acute respiratory failure. POCUS and Eko will be integrated to establish the cause of acute respiratory failure. The reference standard will be the final diagnosis by the clinician.	2 years
Agreement between POCUS and Eko CORE	We will measure Kappa statistic.	2 years

Collaborators and Investigators

• Sponsor: University of Louisville
• Collaborators: Eko Devices, Inc.
• Investigators: Principal Investigator: Rodrigo Cavallazzi, MD, University of Louisville

Study record dates

Study Major Dates

• Study Start (Actual): September 9, 2021
• Primary Completion (Estimated): April 30, 2025
• Study Completion (Estimated): April 30, 2025

Study Registration Dates

• First Submitted: August 1, 2021
• First Submitted That Met QC Criteria: November 19, 2021
• First Posted (Actual): December 3, 2021

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: January 17, 2025
• Last Verified: June 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Respiratory Tract Diseases; Respiration Disorders; Respiratory Insufficiency
• Other Study ID Numbers: 21.0389

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: No