Application of machine learning algorithms to predict 30-day hospital readmission following cement augmentation for osteoporotic vertebral compression fractures

Application of machine learning algorithms to predict 30-day hospital readmission following cement augmentation for osteoporotic vertebral compression fractures

Objective: Osteoporosis is a common skeletal disease that greatly increases the risk of pathologic fractures and accounts for approximately 700,000 vertebral compression fractures (VCFs) annually in the United States. Cement augmentation procedures such as balloon kyphoplasty (KP) and percutaneous v...

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Bibliographic Details
Main Authors: Andrew Cabrera, Alexander Bouterse, Michael Nelson, Luke Thomas, Omar Ramos, Wayne Cheng, Olumide Danisa
Format: Article
Language:English
Published: Elsevier 2024-07-01
Series:World Neurosurgery: X
Subjects:
Cement augmentation
Kyphoplasty
Machine learning
Readmission
Vertebroplasty
Online Access:http://www.sciencedirect.com/science/article/pii/S2590139724000693

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http://www.sciencedirect.com/science/article/pii/S2590139724000693

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