ArticleArthritis & rheumatology (Hoboken, N.J.)2024
Using Two Predictive Models to Capture Two Types of Poor Outcomes in Knee Arthroplasty: A Multisite Longitudinal Cohort Study.
Article in Arthritis & rheumatology (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
2 citing papers in PubMed.
- Letter to the Editor: Analytic approaches for prognostic studies of persistent pain following knee arthroplasty.Acta orthopaedica · 2026Article
- Response to Letter: Analytic approaches for prognostic studies of persistent pain following knee arthroplasty.Acta orthopaedica · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
objectivePoor outcome after knee arthroplasty (KA), a common major surgery worldwide, reportedly occurs in approximately 20% of patients. These patients demonstrate minimal improvement, at least moderate knee pain, and difficulty performing many routine daily activities. The purposes of our study were to comprehensively determine poor outcome risk after KA and to identify predictors of poor outcome.
methodsData from 565 participants with KA in the Osteoarthritis Initiative and the Multicenter Osteoarthritis studies were used. Previously validated latent class analyses (LCAs) of good versus poor outcome trajectories of Western Ontario and McMaster Universities Arthritis Index (WOMAC) Pain and Disability were generated to describe minimal improvement and poor final outcome. The modified Escobar RAND appropriateness system was used to generate classifications of appropriate, inconclusive, and rarely appropriate. Multivariable prediction models included LCA-based good versus poor outcome, modified Escobar classifications, and evidence-driven preoperative prognostic variables.
resultsModified Escobar appropriateness classifications were nonsignificant predictors of WOMAC Pain good versus poor outcomes, indicating the methods provide independent outcome estimates. For WOMAC Pain and WOMAC Disability, approximately 34% and 45% of participants, respectively, had a high probability of either minimal improvement via "rarely appropriate" classifications or poor outcome via LCA. In multivariable prediction models, greater contralateral knee pain consistently predicted poor outcome (eg, odds ratio 1.21, 95% confidence interval 1.10-1.33).
conclusionAppropriateness criteria and LCA estimates provided combined poor outcome estimates that were approximately double the commonly reported poor outcome of 20%. Rates of poor outcome could be reduced if clinicians screened patients using appropriateness criteria and LCA predictors before surgery to optimize outcome.
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