Dataset Information

OPS_KM_01_hSerum: A Comprehensive Proteomics Analysis of Blood Sera from Patients of Osteoarthritis-Comparative Study before and after Total Joint Replacement Surgery

ABSTRACT: A Comprehensive Proteomics Analysis of Blood Sera from Patients of Osteoarthritis-Comparative Study before and after Total Joint Replacement Surgery

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Harumoto Yamada

PROVIDER: PXD008712 | JPOST Repository | Wed Jun 03 00:00:00 GMT+01:00 2020

REPOSITORIES: jPOST

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			Action	DRS
	20160602_33_KM2_BO_10uL.raw	Raw
	20160602_36_KM2_A3_10uL.raw	Raw
	20160602_40_KM3_BO_10uL.raw	Raw
	20160602_43_KM3_A3_10uL.raw	Raw
	20160608_71_KM4_BO_10uL.raw	Raw

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Project description:BackgroundUnderstanding the gait pattern of patients eligible for total hip arthroplasty (THA) due to hip osteoarthritis (OA) offers valuable information for improving locomotive syndrome (LS). This study aims to measure the gait patterns of THA-eligible patients using an optical motion capture system and to analyze these patterns using principal component analysis (PCA). Additionally, this study examines the relationship between THA-induced gait patterns and LS.MethodsThis before-after study included 237 patients who underwent unilateral primary THA due to hip OA. The primary outcome measures were spatiotemporal gait parameters. Secondary outcome measures included three LS risk tests: a stand-up test, a two-step test, a 25-question Geriatric Locomotive Function Scale (GLFS-25), and total clinical decision limits stages. PCA was performed using 16 spatiotemporal gait parameters collected before and three months after THA. Principal components (PC) were selected to achieve a cumulative contribution rate of 90% (0.9) or higher. Each summarized PC was compared using a paired t-test before and three months after THA. Furthermore, multiple regression analysis was conducted to determine how changes in each PC between before and three months after THA related to changes in the four LS evaluation items.ResultsPCA identified three principal components (PC1, PC2, PC3) that accounted for a cumulative contribution rate of 0.910 using 16 spatiotemporal gait parameters. When comparing before and three months after THA for all three PCs, significant differences were observed in each PC (p < 0.001), with overall walking ability and stance phase being higher three months after THA than before THA, while the asymmetry of support time was lower three months after THA. The results of multiple regression analysis revealed that PC1, PC2, and PC3 were the most influential factors in total clinical decision limits stage. For each LS risk test, the factors related to the stand-up test were identified as PC1, PC2, and PC3, while the factors related to the two-step test were identified as PC1 and PC2. The factors related to the GLFS-25 were also identified as PC1 and PC2.ConclusionsThe most important findings of this study indicate that the three PCs represent over 90% of the 16 spatiotemporal gait parameters, which are associated with total clinical decision limits stage and LS risk tests. The present results suggest that PC1 represents overall walking ability, PC2 represents the stance phase, and PC3 represents asymmetry of support time. Gait pattern characteristics, such as overall walking ability, stance phase, and asymmetry of support time, were clearly defined by these PCs. Regarding the relationship between PC and LS, all three PCs are related to total clinical decision limits stage. In addition, PC1 and PC2 related to all three LS risk tests, and PC3 related only to the stand-up test.

Dataset Information

OPS_KM_01_hSerum: A Comprehensive Proteomics Analysis of Blood Sera from Patients of Osteoarthritis-Comparative Study before and after Total Joint Replacement Surgery

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