Preoperative Prediction and Risk Factor Identification of Hospital Length of Stay for Total Joint Arthroplasty Patients Using Machine Learning

BACKGROUND: The aim of this study was to improve understanding of hospital length of stay (LOS) in patients undergoing total joint arthroplasty (TJA) in a high-efficiency, hospital-based pathway. METHODS: We retrospectively reviewed 1401 consecutive primary and revision TJA patients across 67 patien...

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Detalles Bibliográficos
Autores principales: Park, Jaeyoung, Zhong, Xiang, Miley, Emilie N., Gray, Chancellor F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10372176/
https://www.ncbi.nlm.nih.gov/pubmed/37521739
http://dx.doi.org/10.1016/j.artd.2023.101166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10372176/
https://www.ncbi.nlm.nih.gov/pubmed/37521739
http://dx.doi.org/10.1016/j.artd.2023.101166

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