Personalized Preoperative Prediction of the Length of Hospital Stay after TAVI Using a Dedicated Decision Tree Algorithm

Background: The aim of this study was to identify pre-operative parameters able to predict length of stay (LoS) based on clinical data and patient-reported outcome measures (PROMs) from a scorecard database in patients with significant aortic stenosis who underwent TAVI (transfemoral aortic valve im...

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Detalles Bibliográficos
Autores principales: Zisiopoulou, Maria, Berkowitsch, Alexander, Neuber, Ralf, Gouveris, Haralampos, Fichtlscherer, Stephan, Walther, Thomas, Vasa-Nicotera, Mariuca, Seppelt, Philipp
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950279/
https://www.ncbi.nlm.nih.gov/pubmed/35330346
http://dx.doi.org/10.3390/jpm12030346

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8950279/
https://www.ncbi.nlm.nih.gov/pubmed/35330346
http://dx.doi.org/10.3390/jpm12030346

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