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

knee osteoarthritis pain physical function quality of life rehabilitation sf-36

Journal

Cureus
ISSN: 2168-8184
Titre abrégé: Cureus
Pays: United States
ID NLM: 101596737

Informations de publication

Date de publication:
Jul 2022
Historique:
accepted: 27 07 2022
entrez: 31 8 2022
pubmed: 1 9 2022
medline: 1 9 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 36042993
doi: 10.7759/cureus.27339
pmc: PMC9415726
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e27339

Informations de copyright

Copyright © 2022, Pinto Barbosa et al.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Sara Pinto Barbosa (S)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Lucas Marques (L)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Andre Sugawara (A)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Fernanda Toledo (F)

Hospital das Clínicas, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Marta Imamura (M)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, BRA.

Linamara Battistella (L)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Marcel Simis (M)

Clinical Research Center of the Institute of Physical Medicine and Rehabilitation of Hospital das Clínicas - FMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, São Paulo, BRA.

Felipe Fregni (F)

Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, USA.

Classifications MeSH