Scientific Reports · 2018 · 94 citations · 43 references
MedicineOrthopaedic SurgeryOrthopedic SurgeryJoint Replacement SurgeryOrthopedicsPain ManagementKnee ArthroplastyLower Extremity Function AssessmentOutcome AssessmentPain AssessmentPain MeasurementPain OutcomesClinical Phenotype PredictionClinical Prediction RulesClinical Risk PredictionKnee Function AssessmentLinear RegressionLow Body Mass IndexPatient PainPrimary Knee Arthroplasty
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.
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