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Articles Published Processes
8/4/2025 12:11:32 PM | Browse: 13 | Download: 41
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Received |
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2025-01-24 06:57 |
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Peer-Review Started |
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2025-01-24 06:57 |
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To Make the First Decision |
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Return for Revision |
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2025-03-16 12:13 |
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Revised |
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2025-03-29 12:17 |
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Second Decision |
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2025-05-06 02:51 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-05-07 10:27 |
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Articles in Press |
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2025-05-07 10:27 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-07-07 05:39 |
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Publish the Manuscript Online |
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2025-08-04 12:11 |
| ISSN |
2222-0682 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Orthopedics |
| Manuscript Type |
Retrospective Study |
| Article Title |
Machine learning for patient selection in corticosteroid decision making in knee osteoarthritis: A feasibility model
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Omar Musbahi, Kyriacos Pouris, Savvas Hadjixenophontos, Ahmed Al-Saadawi, Iris Soteriou, Justin Peter Cobb and Gareth G Jones |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Institute For Health and Care Research |
No. NIHR302632 |
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| Corresponding Author |
Omar Musbahi, Senior Researcher, Department of Surgery and Cancer - Faculty of Medicine, Imperial College London, 86 Wood Ln, London W12 0BZ, United Kingdom. om112@ic.ac.uk |
| Key Words |
Knee osteoarthritis; Machine learning; Predictive modelling; Corticosteroid injection; Patient selection |
| Core Tip |
Historically, the efficacy of corticosteroid injections in knee osteoarthritis has been heavily debated, as patient responses can vary significantly. This study evaluates the feasibility of a machine learning model to identify which patients with knee osteoarthritis will benefit from corticosteroid injections. Data from two cohort studies were combined for analysis. The model generated an accuracy of 67.8% (95% confidence interval: 64.6%-70.9%), F1 score of 30.8%, and an area under the curve score of 0.60. These metrics demonstrate feasibility to assist clinicians with decision-making in patient selection for corticosteroid injections. Further research is required to improve the model prior to testing in clinical settings. |
| Publish Date |
2025-08-04 12:11 |
| Citation |
<p>Musbahi O, Pouris K, Hadjixenophontos S, Al-Saadawi A, Soteriou I, Cobb JP, Jones GG. Machine learning for patient selection in corticosteroid decision making in knee osteoarthritis: A feasibility model. <i>World J Methodol</i> 2025; 15(4): 105493</p> |
| URL |
https://www.wjgnet.com/2222-0682/full/v15/i4/105493.htm |
| DOI |
https://dx.doi.org/10.5662/wjm.v15.i4.105493 |
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