Proteomic phenotyping with machine learning for cardiovascular outcomes in haemodialysis: insights from the AURORA trial.

Fiche publication

Date publication

avril 2026

Journal

European heart journal. Digital health

Auteurs

Membres identifiés du Cancéropôle Est :
Pr ROSSIGNOL Patrick

Tous les auteurs :
Salib M, Girerd S, Pinet F, März W, Scharnagl H, Massy ZA, Leroy C, Duarte K, Bresso E, Lacomblez C, Jardine AG, Schmieder RE, Fellstrom B, Lopez-Andres N, Rossignol P, Zannad F, Girerd N

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/41971741

Résumé

Cardiovascular (CV) trials have yielded neutral results in haemodialysis. A better understanding of patient profiles is needed to personalize treatment strategies in order to improve CV outcomes in this setting. This study sought to identify biological phenotypes based on proteomic data using machine learning approaches in patients undergoing haemodialysis.