Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients
Biomarkers in Medicine, cilt.18, sa.23, ss.1007-1015, 2024 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 18 Sayı: 23
- Basım Tarihi: 2024
- Doi Numarası: 10.1080/17520363.2024.2422810
- Dergi Adı: Biomarkers in Medicine
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.1007-1015
- Anahtar Kelimeler: contrast-induced nephropathy, inflammatory prognostic index, machine learning, nomogram, non-ST segment elevation myocardial infarction
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
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.