Literature DB >> 20151250

Creation of a reflecting formula to determine a patient's indication for undergoing total knee arthroplasty.

Wing P Chan1, Shu-Mei Hsu, Guo-Shu Huang, Min-Szu Yao, Yue-Chune Chang, Wei-Pin Ho.   

Abstract

BACKGROUND: The aim of this study was to develop, from patients' characteristics and radiography, a formula reflecting the decision for total knee arthroplasty (TKA) in patients with a painful osteoarthritic knee.
METHODS: We reviewed medical records of 193 consecutive patients who had knee osteoarthritis and underwent primary TKA surgery and 133 consecutive patients with knee osteoarthritis who did not have surgery in one institution during the preceding 5 years. Two skeletal radiologists graded, from 0 to 3, radiographic joint space narrowing (JSN), osteophytes, subchondral sclerosis, and subchondral cysts. The association between the variables and outcome were calculated by the chi-squared test and multivariable logistic regression.
RESULTS: Women had more TKAs than men (P = 0.002), and the TKA and non-TKA groups differed in terms of self-care ability (P < 0.001). There were no significant differences in age or body mass index between the two groups. The relevant factors in the reflective formula were age, sex, self-care ability, JSN, and osteophytes in the medial compartment. The retrospective sensitivity and specificity for patients who underwent TKA surgery were 84% and 83%, respectively. The diagnostic efficacy in retrospect evaluated by a receiver operating characteristic curve was 0.92.
CONCLUSIONS: A formula reflecting the decision for TKA surgery in patients with a painful osteoarthritic knee has been developed with acceptable diagnostic efficacy obtained retrospectively. The formula should be validated by further study.

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Year:  2010        PMID: 20151250     DOI: 10.1007/s00776-009-1418-8

Source DB:  PubMed          Journal:  J Orthop Sci        ISSN: 0949-2658            Impact factor:   1.601


  4 in total

1.  Prediction models for the risk of total knee replacement: development and validation using data from multicentre cohort studies.

Authors:  Qiang Liu; Hongling Chu; Michael P LaValley; David J Hunter; Hua Zhang; Liyuan Tao; Siyan Zhan; Jianhao Lin; Yuqing Zhang
Journal:  Lancet Rheumatol       Date:  2022-01-05

2.  Prognostic models for knee osteoarthritis: a protocol for systematic review, critical appraisal, and meta-analysis.

Authors:  Jingyu Zhong; Liping Si; Guangcheng Zhang; Jiayu Huo; Yue Xing; Yangfan Hu; Huan Zhang; Weiwu Yao
Journal:  Syst Rev       Date:  2021-05-19

3.  Predicting Total Knee Replacement from Symptomology and Radiographic Structural Change Using Artificial Neural Networks-Data from the Osteoarthritis Initiative (OAI).

Authors:  Stephan Heisinger; Wolfgang Hitzl; Gerhard M Hobusch; Reinhard Windhager; Sebastian Cotofana
Journal:  J Clin Med       Date:  2020-05-01       Impact factor: 4.241

4.  Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink.

Authors:  Dahai Yu; Kelvin P Jordan; Kym I E Snell; Richard D Riley; John Bedson; John James Edwards; Christian D Mallen; Valerie Tan; Vincent Ukachukwu; Daniel Prieto-Alhambra; Christine Walker; George Peat
Journal:  Ann Rheum Dis       Date:  2018-10-18       Impact factor: 19.103

  4 in total

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