Predictors of the Health-Related Quality of Life (HRQOL) in SF-36 in Knee Osteoarthritis Patients: A Multimodal Model With Moderators and Mediators

膝骨关节炎患者 SF-36 中的健康相关生活质量 (HRQOL) 预测因素:具有调节因素和介质的多模态模型

阅读:10
作者:Sara Pinto Barbosa, Lucas Marques, Andre Sugawara, Fernanda Toledo, Marta Imamura, Linamara Battistella, Marcel Simis, Felipe Fregni

Abstract

Purpose The study aimed to examine associations between the 36-item short form health survey (SF-36) in clinical and neurophysiological measures to identify its predictors in patients with knee osteoarthritis (KOA) in a rehabilitation program. Methods We analyzed data from our cohort study (DEFINE cohort). We analyzed data from our KOA arm, with 107 patients, including clinical assessments, demographic data, pain scales, motor function (Timed Up and Go Test (TUG), 10 meters walk test, and 6-minute walk), balance (BBS), sleepiness (ESS), and Transcranial Magnetic Stimulation (TMS) and Electroencephalography (EEG). Results Our results showed 83.19% of patients were female with an average age of 68.6 years and an average number of days of pain was 96 days; around 31.86% were using more than five medications per day. Regarding the multimodal model to explain SF-36, the main variables relevant to the quality of life (QoL) were related to emotional aspects, such as anxiety and depression. Moreover, our study added findings with polymorphism (OPRM1/rs1799971) predicting mental aspects. Cognitive variables were important in predicting the mental health, emotional, and social support dimensions of the SF-36. In the physical domain, pain-related variables predominantly predicted QoL in these relationships. The domain of vitality significantly predicted all dimensions studied, except for mental and general health. Conclusion The results help in understanding the aspects that contribute to QoL and are discussed considering the general literature on physical rehabilitation and specific to this clinical group. Furthermore, the statistical methods allowed us to explore and effectively understand the dimensions related to QoL.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。