Development and validation of a clinical prediction model for patient-reported pain and function after primary total knee replacement surgery View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

M. T. Sanchez-Santos, C. Garriga, A. Judge, R. N. Batra, A. J. Price, A. D. Liddle, M. K. Javaid, C. Cooper, D. W. Murray, N. K. Arden

ABSTRACT

To develop and validate a clinical prediction model of patient-reported pain and function after undergoing total knee replacement (TKR). We used data of 1,649 patients from the Knee Arthroplasty Trial who received primary TKR across 34 centres in the UK. The external validation included 595 patients from Southampton University Hospital, and Nuffield Orthopaedic Centre (Oxford). The outcome was the Oxford Knee Score (OKS) 12-month after TKR. Pre-operative predictors including patient characteristics and clinical factors were considered. Bootstrap backward linear regression analysis was used. Low pre-operative OKS, living in poor areas, high body mass index, and patient-reported anxiety or depression were associated with worse outcome. The clinical factors associated with worse outcome were worse pre-operative physical status, presence of other conditions affecting mobility and previous knee arthroscopy. Presence of fixed flexion deformity and an absent or damaged pre-operative anterior cruciate ligament (compared with intact) were associated with better outcome. Discrimination and calibration statistics were satisfactory. External validation predicted 21.1% of the variance of outcome. This is the first clinical prediction model for predicting self-reported pain and function 12 months after TKR to be externally validated. It will help to inform to patients regarding expectations of the outcome after knee replacement surgery. More... »

PAGES

3381

Journal

TITLE

Scientific Reports

ISSUE

1

VOLUME

8

Author Affiliations

From Grant

  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-018-21714-1

    DOI

    http://dx.doi.org/10.1038/s41598-018-21714-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1101059624

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/29467465


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