Predictors of postprocedural troponin increase in patients undergoing elective percutaneous coronary intervention

Sean Gilhooley1, Mauro Gitto1,2, Alessandro Spirito1

  • 1Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

PubMed

Insights

Post-PCI troponin increase (pTI) after elective percutaneous coronary intervention (PCI) is linked to higher mortality. This study identified key clinical and angiographic risk factors to predict pTI, aiding personalized risk assessment.

Area of Science:

  • Cardiology
  • Interventional Cardiology
  • Biomarkers

Background:

  • Elevation in serum troponin after elective percutaneous coronary intervention (PCI) indicates post-PCI troponin increase (pTI).
  • pTI is associated with increased mortality rates.
  • Identifying risk factors for pTI is crucial for patient management.

Purpose of the Study:

  • To identify clinical and angiographic risk factors associated with post-PCI troponin increase (pTI).
  • To improve risk stratification for patients undergoing elective PCI.

Main Methods:

  • Retrospective analysis of 10,592 patients undergoing elective PCI with drug-eluting stent implantation.
  • pTI defined by Fourth Universal Definition of Myocardial Infarction (UDMI) and Academic Research Consortium 2 (ARC-2) criteria.
  • Multivariable logistic regression used to evaluate predictors of pTI.

Main Results:

  • 16.3% of patients experienced pTI by UDMI criteria and 4.4% by ARC-2 criteria.
  • Predictors of pTI included low-density lipoprotein cholesterol, lesion length, and maximum stent diameter.
  • Higher left ventricular ejection fraction, prior PCI, and intravascular imaging use were protective; female sex, anemia, and P2Y12 inhibitor loading predicted UDMI-defined pTI, while chronic kidney disease predicted ARC-2-defined pTI.

Conclusions:

  • Patient-specific angiographic and clinical factors can predict pTI.
  • These identified risk factors can inform individualized risk assessment for patients undergoing elective PCI.
  • Further research may refine prediction models for pTI.
Abstract

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