The SMART-LV Pilot Study

NCT05630170 | Completed DMC

• 2 other identifiers: 2000034006No NIH funding
• Study Type: interventional
• Target: 10
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this pilot study is to evaluate the prospective performance of an image-based, smartphone-adaptable artificial intelligence electrocardiogram (AI-ECG) strategy to predict and detect left ventricular systolic dysfunction (LVSD) in a real-world setting.

Conditions

Left Ventricular Systolic Dysfunction

Outcome Measures

Primary Outcomes (1)

• Successful detection of asymptomatic LVSD by AI-ECG

  Device feasibility of AI-ECG will be evaluated by comparing the proportion of patients with LVSD on echocardiography among those with a high predicted probability of LVSD on an AI-ECG screen compared with the proportion of patients with LVSD on echocardiography in those with a negative AI-ECG screen. Higher proportions indicate successful detection of asymptomatic LVSD compared with routine clinical care.

  During study visit approximately 50 minutes

Study Arms (1)

AI-ECG

EXPERIMENTAL

A novel AI-ECG model developed at the Cardiovascular Data Science (CarDS) lab will be used as Software as Medical Device (SaMD) on ECG images for detection of LVSD.The AI-ECG model will be used on all participants undergoing a 12-lead ECG.

Device: AI-ECG

Interventions

AI-ECG DEVICE

A novel AI-ECG model developed at the Cardiovascular Data Science (CarDS) lab will be used as Software as Medical Device (SaMD) on ECG images for detection of LVSD.

AI-ECG

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Provision of signed and dated informed consent form.
• Stated willingness to comply with all study procedures and availability for the duration of the study

You may not qualify if:

• Patients who have undergone a prior echocardiogram.
• Patients with a prior diagnosis of left ventricular dysfunction, based on a documented low ejection fraction (EF) in the medical record.
• Patients with an intermediate predicted probability of low EF (10 to 80%)
• Patients with a prior diagnosis of heart failure as determined by International Classification of Diseases-10 diagnosis code for heart failure.
• Research opt-out patients

Sponsors & Collaborators

• Yale University: lead

Study Sites (1)

Yale New Haven Hospital

New Haven, Connecticut, 06520, United States

Location

MeSH Terms

Conditions

Ventricular Dysfunction, Left

Condition Hierarchy (Ancestors)

Ventricular Dysfunction; Heart Diseases; Cardiovascular Diseases

Study Officials

• Rohan Khera, MD, MS

  Yale University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: In the ECG repository of Yale New Haven Hospital, all patients undergoing a 12-lead screen in an outpatient setting, from whom 20 individuals, 10 each with high and low predicted probability of LVSD, will be invited for a limited echocardiogram to definitively evaluate for LVSD. The investigators will assess whether the AI-ECG model continues to have the reported discrimination and sensitivity of \>90% for LVSD diagnosis in a screening setting in outpatient routine clinical care.

Study Record Dates

• First Submitted: November 17, 2022
• First Posted: November 29, 2022
• Study Start: September 13, 2023
• Primary Completion: May 21, 2024
• Study Completion: May 22, 2024
• Last Updated: May 24, 2024

Record last verified: 2024-05

Locations

US (1)