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Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI
Joint Authors
Celaya-Padilla, José
Treviño, Victor
Tamez-Peña, José
Galván-Tejada, Jorge I.
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented.
Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented.
The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects.
Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2).
Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool.
Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios.
Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively.
The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively.
Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively.
Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain.
American Psychological Association (APA)
Galván-Tejada, Jorge I.& Celaya-Padilla, José& Treviño, Victor& Tamez-Peña, José. 2015. Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057998
Modern Language Association (MLA)
Galván-Tejada, Jorge I.…[et al.]. Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1057998
American Medical Association (AMA)
Galván-Tejada, Jorge I.& Celaya-Padilla, José& Treviño, Victor& Tamez-Peña, José. Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057998
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057998