Ignite Creation Date:
2025-12-25 @ 1:22 AM
Ignite Modification Date:
2026-01-06 @ 12:37 PM
Study NCT ID:
NCT06637293
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-09-19
First Post:
2024-10-09
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Deployment and Evaluation of Artificial Intelligence Software for Electrocardiogram Analysis and Management in Primary Care
Sponsor:
Montreal Heart Institute
Organization:
Study Overview
Official Title:
Deployment and Evaluation of Artificial Intelligence Software for Electrocardiogram Analysis and Management in Primary Care
Status:
NOT_YET_RECRUITING
Status Verified Date:
2025-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
DAISEA-ECG
Brief Summary:
The DAISEA-ECG project aims to improve the diagnosis of heart diseases in primary care through the DeepECG platform, which combines ECG-AI and ECHONeXT algorithms. This study uses a stepped wedge design, where each Family Medicine Group acts as its own control. The FMGs will gradually transition from the control period (without AI recommendations) to the intervention period (with AI recommendations activated) in a randomized sequence.
The primary objective is to compare the sensitivity of family physicians in detecting cardiac pathologies, with and without the assistance of the DeepECG platform. Sensitivity is defined as the proportion of patients correctly referred to cardiology or for transthoracic echocardiography (TTE) among those who indeed required cardiovascular evaluation, as confirmed by an independent adjudication committee.
The primary objective is to compare the sensitivity of family physicians in detecting cardiac pathologies, with and without the assistance of the DeepECG platform. Sensitivity is defined as the proportion of patients correctly referred to cardiology or for transthoracic echocardiography (TTE) among those who indeed required cardiovascular evaluation, as confirmed by an independent adjudication committee.
Detailed Description:
Mathematically, sensitivity is calculated as True Positive / (True Positive + False Negative), where True Positive represents correctly referred patients and false negatives represents patients who should have been referred but were not.
The secondary objectives include determining the rate of cardiovascular evaluation referrals before and after the intervention (implementation of the DeepECG platform), the individual characteristics of the intervention (PPV, NPV, and specificity), as well as evaluating the feasibility of implementing AI-based automatic ECG interpretation in primary care through surveys of family physicians and cardiologists.
PPV: Positive predictive value NPV: Negative predictive value
The secondary objectives include determining the rate of cardiovascular evaluation referrals before and after the intervention (implementation of the DeepECG platform), the individual characteristics of the intervention (PPV, NPV, and specificity), as well as evaluating the feasibility of implementing AI-based automatic ECG interpretation in primary care through surveys of family physicians and cardiologists.
PPV: Positive predictive value NPV: Negative predictive value
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: