Novel classification of knee osteoarthritis severity based on spatiotemporal gait analysis.
Objective: To describe a novel classification method for knee osteoarthritis (OA) based on spatiotemporal gait analysis.Methods: Gait analysis was initially performed on 2911 knee OA patients. Females and males were analyzed separately because of the influence of body height on spatiotemporal parame...
| Publicado en: | Osteoarthritis & Cartilage Vol. 22; no. 3; pp. 457 - 464 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Mar2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103812396&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103812396 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10634584 NZV jtl: Osteoarthritis & Cartilage issn: 10634584 maglogo: N pubinfo: dt: Mar2014 vid: 22 iid: 3 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 103812396 NLM24418677 2012496082 10.1016/j.joca.2013.12.015 NLM24418677 103812396 ppf: 457 ppct: 7 formats: tig: atl: Novel classification of knee osteoarthritis severity based on spatiotemporal gait analysis. aug: au: Elbaz, A Mor, A Segal, G Debi, R Shazar, N Herman, A affil: AposTherapy Research Group, Herzliya, Israel. Electronic address: avie@apostherapy.com. sug: subj: Algorithms Gait Physiology Osteoarthritis, Knee Classification Severity of Illness Indices Adult Aged Aged, 80 and Over Arthroplasty, Replacement, Knee Statistics and Numerical Data Clinical Assessment Tools Disability Evaluation Female Human Male Middle Age Osteoarthritis, Knee Surgery Questionnaires Standards Short Form-36 Health Survey (SF-36) Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Objective: To describe a novel classification method for knee osteoarthritis (OA) based on spatiotemporal gait analysis.Methods: Gait analysis was initially performed on 2911 knee OA patients. Females and males were analyzed separately because of the influence of body height on spatiotemporal parameters. The analysis included the three stages of clustering, classification and clinical validation. Clustering of gait analysis to four groups was applied using the kmeans method. Two-thirds of the patients were used to create a simplified classification tree algorithm, and the model's accuracy was validated by the remaining one-third. Clinical validation of the classification method was done by the short form 36 Health Survey (SF-36) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaires.Results: The clustering algorithm divided the data into four groups according to severity of gait difficulties. The classification tree algorithm used stride length and cadence as predicting variables for classification. The correct classification accuracy was 89.5%, and 90.8% for females and males, respectively. Clinical data and number of total joint replacements correlated well with severity group assignment. For example, the percentages of total knee replacement (TKR) within 1 year after gait analysis for females were 1.4%, 2.8%, 4.1% and 8.2% for knee OA gait grades 1-4, respectively. Radiographic grading by Kellgren and Lawrence was found to be associated with the gait analysis grading system.Conclusions: Spatiotemporal gait analysis objectively classifies patients with knee OA according to disease severity. That method correlates with radiographic evaluation, the level of pain, function, number of TKR. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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