ArticleRheumatology advances in practice2018
Development of a clinical risk score for pain and function following total knee arthroplasty: results from the TRIO study.
Article in Rheumatology advances in practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 3 syntheses or guidelines pooled it, 36 citations in OpenAlex.
- Evaluating methodological quality of prognostic prediction models on patient-reported outcome measurements after total hip and total knee arthroplasty : a systematic review.Bone & joint open · 2026Pooled it
- Risk factors of chronic postoperative pain after total knee arthroplasty: a systematic review.Journal of orthopaedic surgery and research · 2024Pooled it
- Pooled it
- Comparative responsiveness of the PROMIS-10 Global Health and EQ-5D questionnaires in patients undergoing total knee arthroplasty.The bone & joint journal · 2019Trial
- Influencing factors on the quality of recovery after total knee arthroplasty: development of a predictive model.Frontiers in medicine · 2024Article
- Evaluating methodological quality of prognostic prediction models on patient reported outcome measurements after total hip replacement and total knee replacement surgery: a systematic review protocol.Systematic reviews · 2022Article
- Artificial intelligence in knee arthroplasty: current concept of the available clinical applications.Arthroplasty (London, England) · 2022Review
- Prognostic models for knee osteoarthritis: a protocol for systematic review, critical appraisal, and meta-analysis.Systematic reviews · 2021Article
- Achieving Validated Thresholds for Clinically Meaningful Change on the Knee Injury and Osteoarthritis Outcome Score After Total Knee Arthroplasty: Findings From a University-based Orthopaedic Tertiary Care Safety Net Practice.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2019Article
- [Predictors for persistent pain and dissatisfaction after total knee arthroplasty].Schmerz (Berlin, Germany) · 2019Review
- Classification using ensemble learning under weighted misclassification loss.Statistics in medicine · 2019Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesThe aim was to develop and validate a simple clinical prediction model, based on easily collected preoperative information, to identify patients at high risk of pain and functional disability 6 months after total knee arthroplasty (TKA).
methodsThis was a multicentre cohort study of patients from nine centres across the UK, who were undergoing a primary TKA for OA. Information on sociodemographic, psychosocial, clinical and quality-of-life measures were collected at recruitment. The primary outcome measure for this analysis was the Oxford knee score (OKS), measured 6 months postoperatively by postal questionnaire. Multivariable logistic regression was used to develop the model. Model performance (discrimination and calibration) and internal validity were assessed, and a simple clinical risk score was developed.
resultsSeven hundred and twenty-one participants (mean age 68.3 years; 53% female) provided data for the present analysis, and 14% had a poor outcome at 6 months. Key predictors were poor clinical status, widespread body pain, high expectation of postoperative pain and lack of active coping. The developed model based on these variables demonstrated good discrimination. At the optimal cut-off, the final model had a sensitivity of 83%, specificity of 61% and positive likelihood ratio of 2.11. Excellent agreement was found between observed and predicted outcomes, and there was no evidence of overfitting in the model.
conclusionWe have developed and validated a clinical prediction model that can be used to identify patients at high risk of a poor outcome after TKA. This clinical risk score may be an aid to shared decision-making between patient and clinician.
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