IDEAS home Printed from https://ideas.repec.org/a/taf/gcmbxx/v26y2023i4p450-459.html
   My bibliography  Save this article

Multimodal data analysis of knee osteoarthritis assessment: factors selection for conservative care decision making

Author

Listed:
  • F. Bensalma
  • N. Mezghani
  • A. Cagnin
  • A. Fuente
  • L. Lenoir
  • N. Hagemeister

Abstract

When assessing a patient with knee osteoarthritis (OA), a number of factors are considered to guide treatment plan, namely, demographic, radiographic, clinical, musculoskeletal, and biomechanical factors. The aim of this study is to identify which of these factors are the most related to each other to potentially better prioritize the modifiable factors to be addressed as they may influence treatment outcomes. We investigated a multimodal canonical correlation analysis to evaluate associations between these factors. The analysis was performed on 415 OA patients who were not candidates for knee arthroplasty, to identify factors that are associated to the patients’ clinical conditions.

Suggested Citation

  • F. Bensalma & N. Mezghani & A. Cagnin & A. Fuente & L. Lenoir & N. Hagemeister, 2023. "Multimodal data analysis of knee osteoarthritis assessment: factors selection for conservative care decision making," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 26(4), pages 450-459, March.
  • Handle: RePEc:taf:gcmbxx:v:26:y:2023:i:4:p:450-459
    DOI: 10.1080/10255842.2022.2066973
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10255842.2022.2066973
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10255842.2022.2066973?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:gcmbxx:v:26:y:2023:i:4:p:450-459. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/gcmb .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.