Simple risk stratification for a complex coronary phenotype: association of the ACEF score with coronary slow flow

Bihter Senturk1, Mehmet Kıs1, Huseyin Dursun1

  • 1Department of Cardiology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey.

Insights

The ACEF score effectively predicts coronary slow flow (CSF), showing superior accuracy compared to HbA1c. This score is a valuable tool for identifying patients with CSF, independent of its individual components.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Predictive Analytics

Background:

  • Coronary slow flow (CSF) is a condition lacking robust predictive markers.
  • The association between the ACEF score and CSF prediction requires further investigation.

Purpose of the Study:

  • To evaluate the predictive accuracy of the ACEF score for coronary slow flow (CSF).
  • To compare the predictive performance of the ACEF score against HbA1c and LDL-C for CSF.

Main Methods:

  • Retrospective analysis of 257 patients undergoing coronary angiography.
  • Stratification into CSF (n=121) and normal coronary flow (NCF) (n=136) groups.
  • Receiver operating characteristic (ROC) curve analysis and logistic regression to assess predictive values.

Main Results:

  • The ACEF score demonstrated an Area Under the Curve (AUC) of 0.763 for CSF prediction, outperforming HbA1c (AUC=0.610).
  • A 0.1-unit increase in the ACEF score correlated with a 28% increased risk of CSF.
  • The ACEF score provided significant incremental predictive value over its individual components.

Conclusions:

  • The ACEF score is a strong independent predictor of coronary slow flow (CSF).
  • The ACEF score offers superior discriminatory ability for CSF compared to HbA1c.
Abstract

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