Literature DB >> 28888903

Appropriateness and total knee arthroplasty: an examination of the American Academy of Orthopaedic Surgeons appropriateness rating system.

D L Riddle1, R A Perera2.   

Abstract

OBJECTIVE: The American Academy of Orthopaedic Surgeons (AAOS) recently published appropriateness criteria for patients with knee osteoarthritis (OA) who are being considered for total knee arthroplasty (TKA). We evaluated the extent to which predictor variables used by the AAOS contribute to final classification, rated as "appropriate," "may be appropriate" or "rarely appropriate."
METHODS: The RAND/UCLA Appropriateness method was used by AAOS to develop 864 clinical vignettes, each incorporating eight evidence-based variables associated with TKA outcome or need. Variables included function-limiting pain severity, knee OA severity, knee motion and age among others. The contribution of each variable to the overall classification was determined using multinomial regression. A classification tree method was applied to determine the combinations of variables that contributed to final classification for each vignette.
RESULTS: Multinomial regression indicated that patient age, knee motion, OA severity and location were the four most powerful predictors of final classification. Function limiting pain, knee instability and lower limb alignment contributed little to the final classification. The classification tree had an accuracy of 86.7% and the most important contributors to classification were age, knee OA severity and pattern.
CONCLUSION: Function limiting pain, the most frequent reason endorsed by patients seeking TKA does not meaningfully contribute to the newly developed AAOS appropriateness criteria. The system is highly dependent on traditional variables that surgeons consider when evaluating patients for TKA: patient age, knee OA severity, knee OA pattern and knee motion.
Copyright © 2017 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Appropriateness; Arthroplasty; Criteria; Knee

Mesh:

Year:  2017        PMID: 28888903     DOI: 10.1016/j.joca.2017.08.018

Source DB:  PubMed          Journal:  Osteoarthritis Cartilage        ISSN: 1063-4584            Impact factor:   6.576


  5 in total

1.  Prevalence of similar or worse symptom and osteoarthritis severity of index and contralateral knees prior to knee arthroplasty: A cross-sectional multicenter cohort study.

Authors:  Daniel L Riddle
Journal:  Knee       Date:  2019-12-23       Impact factor: 2.199

2.  Comparison of an Artificial Intelligence-Enabled Patient Decision Aid vs Educational Material on Decision Quality, Shared Decision-Making, Patient Experience, and Functional Outcomes in Adults With Knee Osteoarthritis: A Randomized Clinical Trial.

Authors:  Prakash Jayakumar; Meredith G Moore; Kenneth A Furlough; Lauren M Uhler; John P Andrawis; Karl M Koenig; Nazan Aksan; Paul J Rathouz; Kevin J Bozic
Journal:  JAMA Netw Open       Date:  2021-02-01

3.  Protocol for systematic review: patient decision aids for total hip and knee arthroplasty decision-making.

Authors:  Lissa Pacheco-Brousseau; Marylène Charette; Dawn Stacey; Stéphane Poitras
Journal:  Syst Rev       Date:  2021-01-04

Review 4.  Artificial intelligence in knee arthroplasty: current concept of the available clinical applications.

Authors:  Cécile Batailler; Jobe Shatrov; Elliot Sappey-Marinier; Elvire Servien; Sébastien Parratte; Sébastien Lustig
Journal:  Arthroplasty       Date:  2022-05-02

5.  The course of pain and function in osteoarthritis and timing of arthroplasty: the CHECK cohort.

Authors:  Maaike G J Gademan; Hein Putter; Wilbert B Van Den Hout; Margreet Kloppenburg; Stefanie N Hofstede; Suzanne C Cannegieter; Rob G H H Nelissen; Perla J Marang-Van De Mheen
Journal:  Acta Orthop       Date:  2018-10       Impact factor: 3.717

  5 in total

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