A Prospective Analysis To Assess The Potential Use Of ECGio In Clinical Practice

Overview

The goal of this observational study is to learn if an ai-assistive algorithm would be useful in patients who are under suspicion of coronary disease. The main question it aims to answer: What proportion of patients would clinicians see fit to order an ai-assistive algorithm if available for clinical use? Participants will be asked to use clinical judgement as to whether a patient fits a predetermined criteria for use and select them for ai-assistive analysis.

An anonymous and de-identified database to be created over the next 9 months at the Cardiology Consultants of Philadelphia. Clinicians will be given the opportunity to select patients who would be appropriate for the analysis, then the study database will be able to be collected retrospectively after the fact. The second database will be a survey response database collected anonymously and de-identified of a simple random sample of clinicians (see 6.2) who "ordered" ECGio. The EMR will be scraped by CCP after the fact to identify which patients (whether ECGio was "ordered" or not) would be appropriate for ECGio usage based on the criteria defined in section 3.1. Digital (or PDF), anonymous, and de-identified ECG tracings for the cohort will be collected from the MUSE system. We will be provided an example of the ECG tracing as an XML export (or other format acceptable to the study sponsor), lasting 10 seconds with 500 Hz sampling. Within the digital tracing a total of 5000 data points exist for each of 12 standard leads (aVL, I, -aVR, II, aVF, III, V1, V2, V3, V4, V5, and V6).

Conditions

Interventions

Eligibility

Locations (4)

Outcomes

Central Contacts