title: Prediction of time dependent survival in HF patients after VAD implantation using pre- and post-operative data.
abstract: Heart failure is one of the most common diseases worldwide. In recent years, Ventricular Assist Devices (VADs) have become a valuable option for patients with advanced HF. Although it has been shown that VADs improve patient survival rates, several complications persist during left VAD (LVAD) support. The stratification scores currently employed are mostly generic, i.e. not specifically built for LVAD patients, and are based on pre-implantation patient data. In this work we apply data mining approaches for the prediction of time dependent survival in patients after LVAD implantation. Moreover, the predictions acquired with the use of pre-implantation data are enriched by employing post-implantation data, i.e. follow-up data. Different clinical scenarios have been depicted and the subsequent conditions are tested in order to identify the optimal set of pre- and post-implant features, as well as the most suitable algorithms for feature selection and prediction. The proposed approach is applied to a real dataset of 71 patients, reporting an accuracy of 84.5%, sensitivity of 87% and specificity of 82%. Based on the reported results, expert cardio-surgeons can be supported in planning the treatment of VAD patients.
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Dept of Materials Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece; Dept of Biological Applications and Technologies, University of Ioannina, GR 45110 Ioannina, Greece.
authors.forename: Konstantina
authors.initials: K
authors.lastname: Kourou
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Dept of Materials Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece.
authors.forename: George
authors.initials: G
authors.lastname: Rigas
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Dept of Materials Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece.
authors.forename: Konstantinos P
authors.initials: KP
authors.lastname: Exarchos
authors.affiliation: Dept of Economics, University of Ioannina, GR 45110 Ioannina, Greece.
authors.forename: Yorgos
authors.initials: Y
authors.lastname: Goletsis
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Dept of Materials Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece.
authors.forename: Themis P
authors.initials: TP
authors.lastname: Exarchos
authors.affiliation: Dept of Cardiac Surgery, University Hospital Leuven, Belgium.
authors.forename: Steven
authors.initials: S
authors.lastname: Jacobs
authors.affiliation: Dept of Cardiac Surgery, University Hospital Leuven, Belgium.
authors.forename: Bart
authors.initials: B
authors.lastname: Meyns
authors.affiliation: Institute of Clinical Physiology, National Research Council, Pisa, Italy.
authors.forename: Maria-Giovanna
authors.initials: MG
authors.lastname: Trivella
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Dept of Materials Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece. Electronic address: fotiadis@cc.uoi.gr.
authors.forename: Dimitrios I
authors.initials: DI
authors.lastname: Fotiadis
mesh_terms: D000328:Adult; D016208:Databases, Factual; D018572:Disease-Free Survival; D005260:Female; D005500:Follow-Up Studies; D006333:Heart Failure / Q000401:mortality / Q000503:physiopathology / Q000601:surgery; D006353:Heart-Assist Devices; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011237:Predictive Value of Tests; D015996:Survival Rate
keywords: Classification; Data mining; Feature selection; Heart failure disease; Survival prediction; Ventricular assist device