We aimed to examine the characteristics of deep venous flow in
the leg in a cast and the effects of a wearable neuromuscular stimulator
(geko; FirstKind Ltd) and also to explore the participants’ tolerance
of the stimulator. This is an open-label physiological study on ten healthy volunteers.
Duplex ultrasonography of the superficial femoral vein measured
normal flow and cross-sectional area in the standing and supine
positions (with the lower limb initially horizontal and then elevated).
Flow measurements were repeated during activation of the geko stimulator
placed over the peroneal nerve. The process was repeated after the
application of a below-knee cast. Participants evaluated discomfort
using a questionnaire (verbal rating score) and a scoring index
(visual analogue scale).Objectives
Methods
The aim of this study was to perform a comprehensive evaluation of the changes in function from pre- to post-surgery in total and unilateral knee arthroplasty (UKA/TKA) patients. Twenty healthy (age 62.4 ±5.9, 11 male), 14 UKA (age 60.9 ±10.1, 8 male) and 17 TKA (age 67.2 ±8.1, 9 male) patients were studied. KA patients were assessed four weeks pre- and six months post-operation. Measures of perceived pain and function were collected using Oxford Knee Score (OKS) questionnaire. Tests of objective function included joint range of motion (RoM), ultrasound imaging, and 3-D motion analysis/inverse modelling from gait and sit-stand. An optimal set of variables was used to classify KA function using the Cardiff DST method. Pre-KA and healthy individuals were accurately classified (96%). Post-operation questionnaire measures of function improved for both UKA and TKA groups. However, observed measures of RoM, muscle atrophy and gait had only limited gains. This resulted in 57% of UKA and only 27% of TKA patients being classified as healthy post-operation. The results of this study show that 6 months post-surgery UKA patients had higher function than TKA. Using statistical approaches to combine functional assessments has provided an accurate platform to classify function and estimate changes from pre- to post-surgery. The clinical application of this tool requires further investigation and comparison to commonly used clinical techniques.
The number of total knee joint replacements has increased dramatically, from 28,000 in 2004 to over 73,000 in 2008 in the UK. This increase in procedures means that there is a need to assess the performance of an implant design in the general population. For younger, more active patients, cementless tibial fixation is an attractive alternative means of fixation and has been used for over 30 years. However, the clinical results with cementless fixation have been variable, with reports of extensive radiolucent lines, rapid early migration and aseptic loosening [1]. This study investigates the inter-patient variability of bone strain at the implant-bone interface of 130 implanted tibias over a full gait cycle. A large scale FE study of a full gait cycle was performed on 130 tibias implanted with a cementless tibia tray (PFC Sigma, DePuy Inc, USA). A population of tibias was generated from a statistical shape and intensity (SSI) model [2]. The tibia tray was automatically positioned and implanted using ZIBAmira (Zuse Institute Berlin, Germany). Cutting and implanting were performed using Boolean operations on the meshed surfaces of the tibia and implant. After generation of a volume mesh from the resulting surface, the bone modulus was mapped onto the new mesh. The FE models were processed in Abaqus (SIMULIA, RI, USA). Associated force data (axial, anterior-posterior and medial-lateral forces and flexion-extension, varus-valgus and internal-external moments) was sampled from a statistical model of the gait cycle derived from musculoskeletal modelling of 20 elderly healthy subjects. Patient weight was estimated using the length of the tibia and a BMI sampled from NHANES data. Loads were applied to four groups of nodes on the tibia tray (anterior, posterior, medial and, lateral) for 51 steps in the gait cycle. The bone and implant were assumed to be bonded, simulating the osseointegrated condition.Introduction
Methods
