287 resultados para medical implants


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This study reports the physicochemical and drug diffusion properties of rifampicin containing poly(epsilon-caprolactone) (PCL)/polyethylene glycol (PEG) networks, designed as bioactive biomaterials. Uniquely, the effects of the states of both rifampicin and PEG and the interplay between these components on these properties are described. PCL matrices containing rifampicin (1-5%, w/w) and PEG 200 (0-15%, w/w) were prepared by casting from an organic solvent (dichloromethane). The films were subsequently characterized in terms of their thermal/thermorheological, surface and tensile properties, biodegradation and drug diffusion/release properties. Incorporation of PEG and/or rifampicin significantly affected the tensile and surface properties of PCL, lowering the ultimate tensile strength, % elongation at break, Young modulus and storage and loss moduli. Both in the absence and presence of PEG, solubilisation of rifampicin within the crystalline domains of PCL was observed. PEG was present as a dispersed liquid phase. The release of rifampicin (3% loading) was unaffected by the presence of PEG. Similarly the release of rifampicin (5%) was unaffected by low concentrations of PEG (5-10%) however, at higher loadings, the release rate of rifampicin was enhanced by the presence of PEG. Rifampicin release (10% loading) was enhanced by the presence of PEG in a concentration dependent fashion. These observations were accredited to enhanced porosity of the matrix. In all cases, diffusion-controlled release of rifampicin occurred which was unaffected by polymer degradation. This study has uniquely illustrated the effect of hydrophilic pore formers on the physicochemical properties of PCL. Interestingly, enhanced diffusion controlled release was only observed from biomaterials containing high loadings of PEG and rifampicin (5, 10%), concentrations that were shown to affect the mechanical properties of the biomaterials. Care should therefore be shown when adopting this strategy to enhance release of bioactive agents from biomaterials. (C) 2011 Elsevier B.V. All rights reserved.

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This study describes the thermorheological, mechanical and drug release properties of novel, light-activated antimicrobial implants. Hydrogels, based on N-isopropylacrylamide (NIPAA) and hydroxyethyl methacryl ate (HEMA) and either devoid of or containing zinc tetraphenylporphyrin, were prepared by free radical polymerisation and characterised using oscillatory rheometry and texture profile analysis. Drug release was studied at both 20 and 37 degrees C. Hydrogels containing NIPAA exhibited a sol-gel temperature (Tin), which increased as the proportion of HEMA increased and was

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Reliable prediction of long-term medical device performance using computer simulation requires consideration of variability in surgical procedure, as well as patient-specific factors. However, even deterministic simulation of long-term failure processes for such devices is time and resource consuming so that including variability can lead to excessive time to achieve useful predictions. This study investigates the use of an accelerated probabilistic framework for predicting the likely performance envelope of a device and applies it to femoral prosthesis loosening in cemented hip arthroplasty.
A creep and fatigue damage failure model for bone cement, in conjunction with an interfacial fatigue model for the implant–cement interface, was used to simulate loosening of a prosthesis within a cement mantle. A deterministic set of trial simulations was used to account for variability of a set of surgical and patient factors, and a response surface method was used to perform and accelerate a Monte Carlo simulation to achieve an estimate of the likely range of prosthesis loosening. The proposed framework was used to conceptually investigate the influence of prosthesis selection and surgical placement on prosthesis migration.
Results demonstrate that the response surface method is capable of dramatically reducing the time to achieve convergence in mean and variance of predicted response variables. A critical requirement for realistic predictions is the size and quality of the initial training dataset used to generate the response surface and further work is required to determine the recommendations for a minimum number of initial trials. Results of this conceptual application predicted that loosening was sensitive to the implant size and femoral width. Furthermore, different rankings of implant performance were predicted when only individual simulations (e.g. an average condition) were used to rank implants, compared with when stochastic simulations were used. In conclusion, the proposed framework provides a viable approach to predicting realistic ranges of loosening behaviour for orthopaedic implants in reduced timeframes compared with conventional Monte Carlo simulations.