The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.Aims
Methods
Matrix-assisted autologous chondrocyte transplantation (MACT)
has been developed and applied in the clinical practice in the last
decade to overcome most of the disadvantages of the first generation
procedures. The purpose of this systematic review is to document
and analyse the available literature on the results of MACT in the
treatment of chondral and osteochondral lesions of the knee. All studies published in English addressing MACT procedures were
identified, including those that fulfilled the following criteria:
1) level I-IV evidence, 2) measures of functional or clinical outcome,
3) outcome related to cartilage lesions of the knee cartilage.Objectives
Methods
