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AI-enabled ECG index for predicting left ventricular dysfunction in patients with ST-segment elevation myocardial

Ki-Hyun Jeon1, Hak Seung Lee2,3, Sora Kang4,5

  • 1Department of Internal Medicine, Seoul National University College of Medicine and Department of Cardiology, Seoul National University Bundang Hospital, Seongnam, South Korea. imcardio@gmail.com.

Scientific Reports
|July 17, 2024
PubMed

Insights

Artificial intelligence (AI) analyzing electrocardiogram (ECG) changes after ST-segment elevation myocardial infarction (STEMI) treatment can predict left ventricular (LV) dysfunction. This AI-enabled ECG index identifies high-risk patients for timely interventions.

Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Electrocardiogram (ECG) changes post-primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) correlate with patient prognosis.
  • Predicting left ventricular (LV) dysfunction early is crucial for managing STEMI patients.

Purpose of the Study:

  • To assess the feasibility of an AI-enabled ECG algorithm in predicting LV dysfunction in STEMI patients.
  • To evaluate the AI algorithm's ability to quantify ECG changes after PCI and correlate them with clinical outcomes.

Main Methods:

  • Serial ECGs from 637 STEMI patients were analyzed using an AI algorithm at multiple time points (pre-PCI, post-PCI, 6h, 24h, discharge, 1-month).
  • The AI algorithm quantified STEMI probability and generated an index.
  • Statistical analysis correlated the AI-derived probability index with the prevalence of LV dysfunction and clinical outcomes.

Main Results:

  • The AI-derived probability index showed a significant association with the prevalence of LV dysfunction.
  • A higher AI probability index independently predicted LV dysfunction.
  • Elevated indices were linked to increased rates of cardiac death and heart failure hospitalizations.

Conclusions:

  • AI-enabled ECG analysis effectively quantifies post-PCI ECG changes in STEMI patients.
  • The AI-derived ECG index serves as a digital biomarker for predicting post-STEMI LV dysfunction, heart failure, and mortality.
  • This AI tool aids in early identification of high-risk STEMI patients, facilitating timely interventions and improved outcomes.

Keywords:
Artificial intelligenceElectrocardiogramHeart failureST-segment elevation myocardial infarction

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