Article 2024 · 1 citations

Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients

Saylik, Faysal, Cinar, Tufan, Selcuk, Murat, Tanboga, Ibrahim Halil

Abstract

Aim: Inflammatory prognostic index (IPI), has been shown to be related with poor outcomes in cancer patients. We aimed to investigate the predictive role of IPI for contrast-induced nephropathy (CIN) development in non-ST segment elevation myocardial infarction patients using a nomogram and performing machine learning (ML) algorithms.Materials & methods: A total of 178 patients with CIN (+) and 1511 with CIN (-) were included.Results: CIN (+) patients had higher IPI levels, and IPI was independently associated with CIN. A risk prediction nomogram including IPI had a higher predictive ability and good calibration. Naive Bayes and k-nearest neighbors were the best ML algorithms for the prediction of CIN patients.Conclusion: IPI might be used as an easily obtainable marker for CIN prediction using ML algorithms.

Keywords

contrast-induced nephropathy inflammatory prognostic index machine learning nomogram non-ST segment elevation myocardial infarction ACUTE KIDNEY INJURY ACUTE CORONARY SYNDROME EPIDEMIOLOGY ASSOCIATION RATIO

WoS Categories

Medicine, Research & Experimental

Sustainable Development Goals

Good Health and Well-being

Citation

Journal: BIOMARKERS IN MEDICINE
Year: 2024
Volume: 18
Issue: 23
Pages: 1007-1015
ISSN: 1752-0363
eISSN: 1752-0371
DOI: 10.1080/17520363.2024.2422810
WoS UID: WOS:001355043100001

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