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Understanding Chinese Medicine Patterns of Rheumatoid Arthritis and Related Biomarkers

Background: A considerable number of Rheumatoid Arthritis (RA) patients only experience side effects from treatment, with little to no actual pain relief. The combination of disease diagnosis in biomedicine and multi-disciplinary integrative approaches such as Chinese Medicine (CM), can help to iden...

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Detalles Bibliográficos
Autores principales: Seca, Susana, Franconi, Giovanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874582/
https://www.ncbi.nlm.nih.gov/pubmed/29401671
http://dx.doi.org/10.3390/medicines5010017
Descripción
Sumario:Background: A considerable number of Rheumatoid Arthritis (RA) patients only experience side effects from treatment, with little to no actual pain relief. The combination of disease diagnosis in biomedicine and multi-disciplinary integrative approaches such as Chinese Medicine (CM), can help to identify different functional diagnosis of RA in the context of biomarker discovery. We aimed to analyse CM patterns in RA and their biomarker profiles. Methods: Four electronic databases (web of science, CINAHL, Scopus and PubMed) were searched. The reference list of all identified reports and articles were searched for additional studies. All study designs were included and no date limits were set. Studies were considered if they were published in English and explored the possible biomarkers profiles in RA patients, classified according to the American College of Rheumatology and categorized in CM as either cold, heat/hot or deficiency patterns. Methodological quality of included studies was assessed using checklists adapted from the ©Critical Appraisal Skills Programme by two independent reviewers. A narrative synthesis was conducted, using thematic analysis. Results: A total of 10 articles were included. The studies examined 77 healthy volunteers and 1150 RA patients categorized as cold, heat/hot or deficiency pattern and related biomarkers were identified individually or concomitantly. Conclusions: CM pattern differentiation based on clinical signs and symptoms showed a diverse range of biomolecules, proteins and genes from RA patients correlated well with cold, heat/hot or deficiency phenotype-based CM patterns and could be used as diagnostic biomarkers for early detection, disease monitoring and therapeutic targets.