The usefulness of arylesterase in predicting contrast-induced nephropathy in ST-segment elevation myocardial infarction patients undergoing percutaneous coronary intervention

Year 2023, Volume: 6 Issue: 2, 244 - 249, 27.03.2023

Süleyman Kalaycı , Ayse Ceylan Hamamcıoglu , Belma Kalaycı

https://doi.org/10.32322/jhsm.1221793

Abstract

Aim: Oxidative stress is one of the causes of contrast-induced nephropathy (CIN). Paraoxonase1 (PON1), is one of the oxidative stress markers. The most sensitive method that has been in use to measure PON1 enzyme activity is the measurement of arylesterase (AREase) activity. To explore relationship between AREase activity and CIN development.
Material and Method: A total of 58 STEMI patients were included in our study. The patients were divided into two groups as CIN (+) and CIN (-). The success of AREase activity level in predicting the development of CIN was also examined by using ROC analysis.
Results: Out of the study patients, 13 were CIN (+) and 45 were CIN (-). AREase activity was found to be statistically significantly lower in the CIN (+) group (875 U/L vs 819 U/L, p= 0.004). In the regression analysis, diabetes mellitus, contrast volume and AREase activity were determined as independent risk factors in the development of CIN. As a result of the ROC analysis, we concluded that the AREase activity level <824.1 U/L predicted the development of CIN with 61.5% sensitivity and 86.7% specificity (AUC= 0.768, 95% CI= 0.638-0.868, p=0.001).
Conclusion: AREase level is an independent risk factor for the development of CIN and can be used for the prediction of CIN development.

Keywords

Acute myocardial infarction/STEMI, angiography, coronary, coronary artery disease, percutaneous coronary Intervention (PCI), renal disease, acute

Supporting Institution

This study was supported by Scientific Research Project Unit of Zonguldak Bulent Ecevit University (BAP 2019-21664500-01) in Turkey.

Project Number

This study was supported by Scientific Research Project Unit of Zonguldak Bulent Ecevit University (BAP 2019-21664500-01) in Turkey.

Thanks

We would like to thank Asisstant Professor Dr Fürüzan Köktürk (PhD) for the statistical analyses.

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