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Nomogram for predicting acute kidney injury after primary PCI in STEMI patients: development and validation study

Ximin Li1, Juzhen Yan1, Yingji Chen1

  • 1Department of Nephrology and Rheumatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.

Renal Failure
|October 15, 2025
PubMed

Insights

This study identified risk factors for acute kidney injury (AKI) after percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI) patients. A new nomogram model accurately predicts AKI risk, aiding early intervention strategies.

Area of Science:

  • Cardiology
  • Nephrology
  • Medical Informatics

Background:

  • Acute kidney injury (AKI) is a significant complication following percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI) patients.
  • Early identification of patients at high risk for AKI is crucial for implementing timely preventive measures.

Purpose of the Study:

  • To identify independent risk factors for AKI after primary PCI in STEMI patients.
  • To develop and validate a predictive nomogram model for post-PCI AKI.

Main Methods:

  • Retrospective analysis of 227 STEMI patients undergoing primary PCI.
  • Logistic regression for risk factor identification.
  • Nomogram construction and evaluation using ROC, calibration curves, and DCA.

Main Results:

  • 18.1% of patients developed AKI.
  • Independent risk factors identified: NSAID use, female sex, elevated blood glucose, serum creatinine, and uric acid.
  • The nomogram demonstrated superior predictive performance (AUC: 0.793) compared to the Mehran score (AUC: 0.626).

Conclusions:

  • The developed nomogram is a valuable tool for accurately predicting AKI risk in STEMI patients post-PCI.
  • The model facilitates early identification of high-risk individuals and supports stratified preventive strategies.
  • High-risk patients experienced significantly longer hospital stays.
Abstract

Keywords:
Acute kidney injuryST-elevation myocardial infarctionhyperglycemianomogram modelpercutaneous coronary interventionrisk factoruric acid

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