CORR Insights®: Machine-learning Models Predict 30-day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty
- PMID: 35849057
- PMCID: PMC9556019
- DOI: 10.1097/CORR.0000000000002325
CORR Insights®: Machine-learning Models Predict 30-day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty
Conflict of interest statement
The author certifies that there are no funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article related to the author or any immediate family members. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research ® editors and board members are on file with the publication and can be viewed on request.
Comment on
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Machine-learning Models Predict 30-Day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty.Clin Orthop Relat Res. 2022 Nov 1;480(11):2137-2145. doi: 10.1097/CORR.0000000000002276. Epub 2022 Jun 20. Clin Orthop Relat Res. 2022. PMID: 35767804 Free PMC article.
References
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- Bellamy JL, Runner RP, Vu CCL, Schenker ML, Bradbury TL, Roberson JR. Modified Frailty Index is an effective risk assessment tool in primary total hip arthroplasty. J Arthroplasty. 2017;32:2963-2968. - PubMed
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- Jamshidi A, Pelletier J, Labbe A, Abram F, Martel‐Pelletier J, Droit A. Machine learning-based individualized survival prediction model for total knee replacement in osteoarthritis: data from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken). 2021;73:1518-1527. - PubMed
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