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The SMART-LV Pilot Study

Primary Purpose

Left Ventricular Systolic Dysfunction

Status
Recruiting
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
AI-ECG
Sponsored by
Yale University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional device feasibility trial for Left Ventricular Systolic Dysfunction

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • Yale New Haven HospitalRecruiting

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

AI-ECG

Arm Description

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.

Outcomes

Primary Outcome Measures

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.

Secondary Outcome Measures

Full Information

First Posted
November 17, 2022
Last Updated
September 15, 2023
Sponsor
Yale University
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1. Study Identification

Unique Protocol Identification Number
NCT05630170
Brief Title
The SMART-LV Pilot Study
Official Title
Pilot Evaluation for SMartphone-adaptable Artificial Intelligence for PRediction and DeTection of Left Ventricular Systolic Dysfunction
Study Type
Interventional

2. Study Status

Record Verification Date
September 2023
Overall Recruitment Status
Recruiting
Study Start Date
September 13, 2023 (Actual)
Primary Completion Date
October 2023 (Anticipated)
Study Completion Date
November 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Yale University

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

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.
Detailed Description
The SMART-LV pilot study will be a prospective cohort study in outpatient clinics at the Yale New Haven Hospital. Participants who have undergone a 12-lead electrocardiogram (ECGs) with either a high (≥80%) or low (<10%) probability of LVSD on AI-ECG algorithm, but without an echocardiogram done in the clinical setting for at least 90 days after the ECG, will be identified by electronic health record (EHR) and invited for a limited echocardiogram/cardiac ultrasonogram for assessing LV ejection fraction. The goal of the study is to evaluate the feasibility of recruiting patients and performing the study after pursuing a screening on 12-lead ECGs. The procedure currently used for detection of LVSD, echocardiograms, are inaccessible and expensive. Therefore, while AI-ECG-based algorithms using a smartphone- or web-based application can broaden access to screening, a thorough evaluation for this indication is needed before clinical adoption. The investigators intend to use the results as pilot data for sample size and drop-off rate estimation for a subsequent larger prospective cohort study aimed at validating the performance characteristics of the model in a screening setting. The validation of this accessible ECG-based screening strategy, that can be directly used by clinicians using a smartphone or web-based application, can transform the early identification of LVSD before the development of symptoms, thereby allowing broader utilization of evidence-based therapies to prevent symptomatic heart failure and premature death.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Left Ventricular Systolic Dysfunction

7. Study Design

Primary Purpose
Device Feasibility
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Model Description
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.
Masking
None (Open Label)
Allocation
N/A
Enrollment
20 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
AI-ECG
Arm Type
Experimental
Arm Description
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.
Intervention Type
Device
Intervention Name(s)
AI-ECG
Intervention Description
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.
Primary Outcome Measure Information:
Title
Successful detection of asymptomatic LVSD by AI-ECG
Description
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.
Time Frame
During study visit approximately 50 minutes

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Provision of signed and dated informed consent form. Stated willingness to comply with all study procedures and availability for the duration of the study Exclusion Criteria: 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
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Lovedeep Dhingra, MBBS
Phone
(203) 747-4429
Email
lovedeep.dhingra@yale.edu
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Rohan Khera, MD, MS
Organizational Affiliation
Yale University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Yale New Haven Hospital
City
New Haven
State/Province
Connecticut
ZIP/Postal Code
06520
Country
United States
Individual Site Status
Recruiting

12. IPD Sharing Statement

Learn more about this trial

The SMART-LV Pilot Study

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