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The CatLet score and outcome prediction in acute myocardial infarction for patients undergoing primary percutaneous intervention: A proof-of-concept study

  • Ming Xing Xu
  • , Terrence D. Ruddy
  • , Paul Schoenhagen
  • , Thomas Bartel
  • , Roberto Di Bartolomeo
  • , Yskert von Kodolitsch
  • , Javier Escaned
  • , Chengxing Shen
  • , Yong Ming He
  • Soochow University
  • University of Ottawa
  • Cleveland Clinic Foundation
  • Sant'Orsola Malpighi Hospital
  • University of Hamburg
  • Hospital Clínico San Carlos de Madrid
  • Shanghai Jiao Tong University

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Background: The Coronary Artery Tree description and Lesion EvaluaTion (CatLet) score accommodating the variability in coronary anatomy is a recently developed and comprehensive angiographic scoring system aimed at assisting in risk-stratification of patients with coronary artery disease. However, a validation of this angiographic scoring system is lacking. Methods: The CatLet score was calculated retrospectively in 308 consecutively enrolled patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention. The primary endpoint, major adverse cardiac or cerebrovascular events (MACCEs), was stratified according to CatLet tertiles: CatLetlow ≤14 (n = 124), CatLetmid 15–21 (n = 82) and CatLettop ≥22 (n = 102). Results: The CatLet score alone or after adjusting for a broad spectrum of risk factors, significantly predicted clinical outcomes at a median 4.3-year follow-up. Multivariable-adjusted hazard ratios (95%CI)/unit higher score were 1.05 (1.04–1.07) for MACCE, 1.06 (1.04–1.07) for cardiac death, and 1.05 (1.04–1.07) for all-cause death. When compared to the SYNTAX score, improved discrimination and better calibration of this CatLet score resulted in a significantly refined risk stratification. The overall category-free net reclassification improvement afforded by this CatLet score was as follows: 37.2% (p =.008) for MACCEs, 35.5% (p =.0249) for cardiac death, and 31.8% (p =.0316) for all-cause death. Conclusions: The ability to integrate the variability in coronary anatomy into angiographic scoring makes the CatLet score a more specific tool for outcome predictions in AMI. (http://www.chictr.org.cn. Unique identifiers: ChiCTR-POC-17013536).

Original languageEnglish
Pages (from-to)E220-E229
JournalCatheterization and Cardiovascular Interventions
Volume96
Issue number3
DOIs
StatePublished - 1 Sep 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • acute myocardial infarction
  • angiographic scoring
  • coronary artery disease
  • outcome prediction

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