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A Predictive Model for Contrast-Induced Acute Kidney Injury After Percutaneous Coronary Intervention in Elderly

Hang Qiu1, Yinghua Zhu1, Guoqi Shen1

  • 1Institute of Cardiovascular Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, People's Republic of China.

Clinical Interventions in Aging
|March 29, 2023
PubMed

Insights

A new nomogram model accurately predicts Contrast-Induced Acute Kidney Injury (CI-AKI) risk in elderly patients with ST-segment elevation myocardial infarction (STEMI) undergoing emergency percutaneous coronary intervention (PCI). This tool aids in identifying high-risk individuals for better patient outcomes.

Area of Science:

  • Cardiology
  • Nephrology
  • Medical Informatics

Background:

  • Contrast-Induced Acute Kidney Injury (CI-AKI) is a significant complication following percutaneous coronary intervention (PCI).
  • Elderly patients with ST-segment elevation myocardial infarction (STEMI) are particularly vulnerable to CI-AKI.
  • Accurate risk prediction is crucial for timely intervention and improved patient management.

Purpose of the Study:

  • To develop and validate a nomogram model for predicting CI-AKI risk in elderly STEMI patients undergoing emergency PCI.
  • To identify key independent risk factors contributing to CI-AKI in this specific patient population.

Main Methods:

  • Retrospective analysis of 542 elderly STEMI patients undergoing emergency PCI.
  • Utilized univariate, LASSO, and multivariate logistic regression to identify risk factors.
  • Developed a nomogram using R software and validated its predictive performance against the Mehran score 2.

Main Results:

  • The nomogram incorporated five variables: diabetes mellitus, LVEF, SII, NT-proBNP, and hsCRP.
  • Achieved high predictive accuracy with AUCs of 0.84 (training) and 0.844 (validation).
  • Demonstrated superior predictive ability and good clinical utility compared to the Mehran score 2.

Conclusions:

  • The developed nomogram model effectively and accurately identifies high-risk elderly STEMI patients for CI-AKI post-PCI.
  • The model offers a valuable tool for clinical decision-making and targeted preventive strategies.
Abstract

Keywords:
ST-segment elevation myocardial infarctioncontrast-induced acute kidney injuryelderlynomogrampercutaneous coronary interventionrisk prediction model

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