Predictors of timed “Up-and-Go” test in elderly with knee osteoarthritis

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Bibliographische Detailangaben
Deutscher übersetzter Titel:Prädiktoren des zeitlich festgelegten “Up-and-Go” Tests bei Älteren mit Kniearthrose
Autor:Marconcin, Priscila; Espanha, Margarida; Yazigi, Flávia; Teles, Júlia
Erschienen in:icSPORTS 2015 : proceedings of the 3rd International Congress on Sports Science Research and Technology Support ; November 15-17, 2015, in Lisbon, Portugal
Veröffentlicht:Cham: Science and Technology Publications (Verlag), 2015, S. 97-103, Lit.
Herausgeber:International Congress on Sports Science Research and Technology Support
Format: Literatur (SPOLIT)
Publikationstyp: Sammelwerksbeitrag
Medienart: Elektronische Ressource (online) Gedruckte Ressource
Dokumententyp: Tagungsband
Sprache:Englisch
DOI:10.5220/0005611300970103
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Erfassungsnummer:PU201609006354
Quelle:BISp

Abstract des Autors

Knee Osteoarthritis (KOA) and aging are conditions that can compromise physical function and quality of life of human being. Thus, performance-based tests and specific self-reported measures related with KOA and general health-related quality of life (QoL) should be used in clinical intervention with elderlies. The study aim was to investigate which factors best predict the performance of the Timed “up-and-go” test in the elderly people with KOA. Eligibility criteria were age ≥ 60 years and uni or bilateral KOA. Subject performed physical tests [Timed “up-and-go” (TUG), Six Minutes Waking Test (6MWT), Five Repetition Sit-to-Stand Test (FRSTST)], Handgrip, 6 meters gait speed, Standing Balance], and filled self-reported questionnaires [Knee Injury and Osteoarthritis Outcome Score (KOOS), health-related quality of life (EQ-5D-5F) and International Physical Activity Questionnaire (IPAQ)]. Pearson and Spearman coefficients were used for correlation analysis and multiple linear regression analysis to identify the significant predictors of Timed “up-and-go”. Results: Final sample included 67 patients, 69+/-6 years of age. Timed “up-and-go” can be explained by two models. The best model (explained 80.7% of variance) included FRSTST, 6MWT, Gait Speed, KOOS ADL and EQ-5D-5F Self-Care variables. Conclusion: Functional strength, mobility, gait speed, and perceived limitation in activities of daily living influenced the TUG performance.