Clinical outcomes associated with robotic and computer-navigated total knee arthroplasty: a machine learning-augmented systematic review.

Buchlak, QD; Clair, J; Esmaili, N; Barmare, A; Chandrasekaran, S

Clinical outcomes associated with robotic and computer-navigated total knee arthroplasty: a machine learning-augmented systematic review.

Buchlak, QD Clair, J Esmaili, N Barmare, A Chandrasekaran, S

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: European Journal of Orthopaedic Surgery and Traumatology, 2022, 32, (5), pp. 915-931
Issue Date:: 2022-06-25

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Field	Value	Language
dc.contributor.author	Buchlak, QD
dc.contributor.author	Clair, J
dc.contributor.author	Esmaili, N
dc.contributor.author	Barmare, A
dc.contributor.author	Chandrasekaran, S
dc.date.accessioned	2023-03-21T00:19:12Z
dc.date.available	2021-06-14
dc.date.available	2023-03-21T00:19:12Z
dc.date.issued	2022-06-25
dc.identifier.citation	European Journal of Orthopaedic Surgery and Traumatology, 2022, 32, (5), pp. 915-931
dc.identifier.issn	1633-8065
dc.identifier.issn	1432-1068
dc.identifier.uri	http://hdl.handle.net/10453/167841
dc.description.abstract	BACKGROUND: Robotic (RTKA) and computer-navigated total knee arthroplasty (CNTKA) are increasingly replacing manual techniques in orthopaedic surgery. This systematic review compared clinical outcomes associated with RTKA and CNTKA and investigated the utility of natural language processing (NLP) for the literature synthesis. METHODS: A comprehensive search strategy was implemented. Results of included studies were combined and analysed. A transfer learning approach was applied to train deep NLP classifiers (BERT, RoBERTa and XLNet), with cross-validation, to partially automate the systematic review process. RESULTS: 52 studies were included, comprising 5,067 RTKA and 2,108 CNTKA. Complication rates were 0-22% and 0-16% and surgical time was 70-116 and 77-102 min for RTKA and CNTKA, respectively. Technical failures were more commonly associated with RTKA (8%) than CNTKA (2-4%). Patient satisfaction was equivalent (94%). RTKA was associated with a higher likelihood of achieving target alignment, less femoral notching, shorter operative time and shorter length of stay. NLP models demonstrated moderate performance (AUC = 0.65-0.68). CONCLUSIONS: RTKA and CNTKA appear to be associated with similarly positive clinical outcomes. Further work is required to determine whether the two techniques differ significantly with regard to specific outcome measures. NLP shows promise for facilitating the systematic review process.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Springer
dc.relation.ispartof	European Journal of Orthopaedic Surgery and Traumatology
dc.relation.isbasedon	10.1007/s00590-021-03059-0
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Orthopedics
dc.subject.mesh	Arthroplasty, Replacement, Knee
dc.subject.mesh	Computers
dc.subject.mesh	Humans
dc.subject.mesh	Machine Learning
dc.subject.mesh	Operative Time
dc.subject.mesh	Robotic Surgical Procedures
dc.subject.mesh	Humans
dc.subject.mesh	Arthroplasty, Replacement, Knee
dc.subject.mesh	Computers
dc.subject.mesh	Operative Time
dc.subject.mesh	Robotic Surgical Procedures
dc.subject.mesh	Machine Learning
dc.subject.mesh	Arthroplasty, Replacement, Knee
dc.subject.mesh	Computers
dc.subject.mesh	Humans
dc.subject.mesh	Machine Learning
dc.subject.mesh	Operative Time
dc.subject.mesh	Robotic Surgical Procedures
dc.title	Clinical outcomes associated with robotic and computer-navigated total knee arthroplasty: a machine learning-augmented systematic review.
dc.type	Journal Article
utslib.citation.volume	32
utslib.location.activity	France
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-03-21T00:19:11Z
pubs.issue	5
pubs.publication-status	Published online
pubs.volume	32
utslib.citation.issue	5

Abstract:

BACKGROUND: Robotic (RTKA) and computer-navigated total knee arthroplasty (CNTKA) are increasingly replacing manual techniques in orthopaedic surgery. This systematic review compared clinical outcomes associated with RTKA and CNTKA and investigated the utility of natural language processing (NLP) for the literature synthesis. METHODS: A comprehensive search strategy was implemented. Results of included studies were combined and analysed. A transfer learning approach was applied to train deep NLP classifiers (BERT, RoBERTa and XLNet), with cross-validation, to partially automate the systematic review process. RESULTS: 52 studies were included, comprising 5,067 RTKA and 2,108 CNTKA. Complication rates were 0-22% and 0-16% and surgical time was 70-116 and 77-102 min for RTKA and CNTKA, respectively. Technical failures were more commonly associated with RTKA (8%) than CNTKA (2-4%). Patient satisfaction was equivalent (94%). RTKA was associated with a higher likelihood of achieving target alignment, less femoral notching, shorter operative time and shorter length of stay. NLP models demonstrated moderate performance (AUC = 0.65-0.68). CONCLUSIONS: RTKA and CNTKA appear to be associated with similarly positive clinical outcomes. Further work is required to determine whether the two techniques differ significantly with regard to specific outcome measures. NLP shows promise for facilitating the systematic review process.

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http://hdl.handle.net/10453/167841