The goal of total hip arthroplasty (THA) is to reduce pain, restore function but also activity levels for general health benefits or social participation. Thus evaluating THA patient activity can be important for diagnosis, indication, outcome assessment or biofeedback. Physical activity (PA) of n=100 primary THA patients (age at surgery 63 ±8yrs; 49M/51F; 170 ±8cm, 79.8 ±14.0kg) was measured at 8 ±3yrs follow-up. A small 3D accelerometer was worn for 4 successive days during waking hours at the non-affected lateral upper leg. Data was analyzed using validated algorithms (Matlab) producing quantitative (e.g. #steps, #transfers, #walking bouts) and qualitative (e.g. cadence, temporal distribution of events) activity parameters. An age matched healthy control group (n=40, 69 ±8yrs, 22M/18F) served as reference.Introduction
Methods
Patient satisfaction becomes an important aspect in clinical practice causing a shift from clinician-administered scales (CAS) towards patient-administered measurement outcomes (PROMs). Besides, clinical outcome can objectively be evaluated using inertia-based motion analysis (IMA). This study evaluates different outcome measures by investigating the 1) effect of replacing CAS by PROMS on outcome assessment, 2) redundancy between scales, 3) additional value of IMA in outcome scoring. This cross-sectional study included 27 primary unilateral total knee arthroplasty patients (m/f=12/19; age=66.2 yrs), 6 weeks (n=12) and 6 months (n=15) postoperative, who covered a wide range of the scores. One CAS (Knee Society Score (KSS; knee and function subscore), two PROMs (Knee Injury and Osteoarthritis Outcome Score Physical Shortform (KOOS-PS), Visual Analogue Scale satisfaction (VAS)) and a functional test (IMA block step test) were completed. For IMA, patients stepped up and down a 20cm block starting with the affected and followed by the non-affected leg, while wearing an inertia-sensor (3D accelero- and gyrometer) at the lower back (fig. 1). IMA-parameters like performance time (s), bending angle (°), pelvic-obliquity angle (°), were calculated using self-designed algorithms. Differences between legs were determined by ratios (affected/non-affected leg). Pearson's correlations were done, considering r<0.4 poor, 0.4<r<0.7 moderate, r>0.7 strong.Introduction
Methods
