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

Şaylık F., Çınar T., Selçuk M., Tanboğa İ. H.

Biomarkers in Medicine, cilt.18, sa.23, ss.1007-1015, 2024 (SCI-Expanded) identifier identifier

  • 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, Chemical Abstracts Core, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.1007-1015
  • Anahtar Kelimeler: contrast-induced nephropathy, inflammatory prognostic index, machine learning, nomogram, non-ST segment elevation myocardial infarction
  • Atatürk 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.