Osteoarthritis (OA) is a growing societal burden, due to the ageing population. Less invasive, less damaging, and cheaper methods for diagnosis are needed, and sound technology is an emerging tool in this field. The aim of the current research was to: 1) investigate the potential of visual scalogram analysis of Acoustic Emission (AE) frequencies within the human audible range (20–20000 Hz) to diagnose knee OA, 2) correlate the qualitative visual scalogram analysis of the AE with OA symptoms, and 3) to do this based on information gathered during gait.INTRODUCTION
AIMS
Osteoarthritis (OA) is a growing societal burden, due to the ageing population. Less invasive, less damaging, and cheaper methods for diagnosis are needed, and sound technology is an emerging tool in this field. Some studies investigate ultrasound signals, while others look at acoustic signals in the audible range. The aim of the current research was to: 1) investigate the potential of visual scalogram analysis of Acoustic Emission (AE) frequencies within the human audible range (20–20000 Hz) to diagnose knee OA, 2) correlate the qualitative visual scalogram analysis of the AE with OA symptoms, and 3) to do this based on information gathered during gait.INTRODUCTION
AIMS
The diagnosis of periprosthetic joint infection (PJI) remains a serious challenge. Based on previous work, we believe that biomarkers will become the mainstay of diagnosing PJI in the future. We report on completion of our 8 year comprehensive biomarker program, evaluating the diagnostic profile of the 15 most promising synovial fluid biomarkers. Synovial fluid was prospectively collected from 99 patients being evaluated for infection in the setting of revision hip or knee arthroplasty. All synovial fluid samples were tested by immunoassay for 15 putative biomarkers that were developed and optimized specifically for use in synovial fluid. Sensitivity, specificity and receiver operating Characteristic (ROC) curve analysis were performed for all biomarkers.INTRODUCTION:
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