Prediction of left ventricular thrombus after myocardial infarction: a cardiac magnetic resonance-based prospective

Carlos Bertolin-Boronat1, Víctor Marcos-Garcés2, Hector Merenciano-González2

  • 1Department of Cardiology, Hospital Clínico Universitario de Valencia, Valencia, Spain; INCLIVA Biomedical Research Institute, Valencia, Spain.

Insights

This study predicts left ventricular thrombus (LVTh) after ST-segment elevation myocardial infarction (STEMI) using readily available admission data. Clinical, echocardiographic, and ECG factors effectively identify high-risk patients for early detection and management.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Predictive Analytics

Background:

  • Left ventricular thrombus (LVTh) is a serious complication following ST-segment elevation myocardial infarction (STEMI).
  • Early identification of LVTh is crucial for preventing embolic events and improving patient outcomes.

Purpose of the Study:

  • To develop a predictive model for LVTh occurrence post-STEMI.
  • Utilize cardiac magnetic resonance (CMR) imaging alongside clinical, echocardiographic, and electrocardiographic (ECG) data available at admission.

Main Methods:

  • Included 590 STEMI patients undergoing CMR (1-week and/or 6-month follow-up).
  • Collected baseline clinical, echocardiographic (LVEF), and ECG (sum-STE, Q-STE) data.
  • Employed multivariate logistic regression and ROC curve analysis for LVTh prediction.

Main Results:

  • LVTh detected in 7.3% of patients.
  • Predictors included chronic coronary syndrome (CCS), anterior STEMI, LVEF, maximum sum-STE, and Q-STE.
  • A high-risk group (anterior STEMI, Q-STE, CCS, max sum-STE >10 mm, LVEF <50%) showed 19.6% LVTh risk within 6 months.
  • The predictive model demonstrated excellent discrimination (AUC=0.85).

Conclusions:

  • LVTh within 6 months post-STEMI is predictable using pre-discharge clinical, echocardiographic, and ECG data.
  • The findings aid in selecting STEMI patients for CMR screening to detect LVTh.
  • Simplified risk scores showed comparable predictive ability and external validation.
Abstract

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