Targeted computational probabilistic corroboration of experimental knee wear simulator: the importance of accounting for variability.

Experimental testing is widely used to predict wear of total knee replacement (TKR) devices. Computational models cannot replace this essential in vitro testing, but they do have complementary strengths and capabilities, which make in silico models a valuable support tool for experimental wear investigations. For effective exploitation, these two separate domains should be closely corroborated together; this requires extensive data-sharing and cross-checking at every stage of simulation and testing. However, isolated deterministic corroborations provide only a partial perspective; in vitro testing is inherently variable, and relatively small changes in the environmental and kinematic conditions at the articulating interface can account for considerable variation in the reported wear rates. Understanding these variations will be key to managing uncertainty in the tests, resulting in a 'cleaner' investigation environment for further refining current theories of wear. This study demonstrates the value of probabilistic in silico methods by describing a specific, targeted corroboration of the AMTI knee wear simulator, using rigid body dynamics software models. A deterministic model of the simulator under displacement-control was created for investigation. Firstly, a large sample of experimental data (N>100) was collated, and a probabilistic computational study (N>1000 trials) was used to compare the kinetic performance envelopes for in vitro and in silico models, to more fully corroborate the mechanical model. Secondly, corresponding theoretical wear-rate predictions were compared to the experimentally reported wear data, to assess the robustness of current wear theories to uncertainty (as distinct from the mechanical variability). The results reveal a good corroboration for the physical mechanics of the wear test rig; however they demonstrate that the distributions for wear are not currently well-predicted. The probabilistic domain is found to be far more sensitive at distinguishing between different wear theories. As such we recommend that in future, researchers move towards probabilistic studies as a preferred framework for investigations into implant wear.

A multi-platform comparison of efficient probabilistic methods in the prediction of total knee replacement mechanics.

Explicit finite element (FE) and multi-body dynamics (MBD) models have been developed to evaluate total knee replacement (TKR) mechanics as a complement to experimental methods. In conjunction with these models, probabilistic methods have been implemented to predict performance bounds and identify important parameters, subject to uncertainty in component alignment and experimental conditions. Probabilistic methods, such as advanced mean value (AMV) and response surface method (RSM), provide an efficient alternative to the gold standard Monte Carlo simulation technique(MCST). The objective of the current study was to benchmark models from three platforms (two FE and one MBD) using various probabilistic methods by predicting the influence of alignment variability and experimental parameters on TKR mechanics in simulated gait. Predicted kinematics envelopes were on average about 2.6mm for tibial anterior-posterior translation, 2.98 for tibial internal­external rotation and 1.9 MPa for tibial peak contact pressure for the various platforms and methods. Based on this good agreement with the MCST, the efficient probabilistic techniques may prove useful in the fast evaluation of new implant designs, including considerations of uncertainty, e.g. misalignment.

In-silico wear prediction for knee replacements--methodology and corroboration.

The capability to predict in-vivo wear of knee replacements is a valuable pre-clinical analysis tool for implant designers. Traditionally, time-consuming experimental tests provided the principal means of investigating wear. Today, computational models offer an alternative. However, the validity of these models has not been demonstrated across a range of designs and test conditions, and several different formulas are in contention for estimating wear rates, limiting confidence in the predictive power of these in-silico models. This study collates and retrospectively simulates a wide range of experimental wear tests using fast rigid-body computational models with extant wear prediction algorithms, to assess the performance of current in-silico wear prediction tools. The number of tests corroborated gives a broader, more general assessment of the performance of these wear-prediction tools, and provides better estimates of the wear 'constants' used in computational models. High-speed rigid-body modelling allows a range of alternative algorithms to be evaluated. Whilst most cross-shear (CS)-based models perform comparably, the 'A/A+B' wear model appears to offer the best predictive power amongst existing wear algorithms. However, the range and variability of experimental data leaves considerable uncertainty in the results. More experimental data with reduced variability and more detailed reporting of studies will be necessary to corroborate these models with greater confidence. With simulation times reduced to only a few minutes, these models are ideally suited to large-volume 'design of experiment' or probabilistic studies (which are essential if pre-clinical assessment tools are to begin addressing the degree of variation observed clinically and in explanted components).

Epidemiological typing of Enterobacter aerogenes.

The applicability of Enterobacter cloacae and Klebsiella typing reagents for classifying clinical strains of Enterobacter aerogenes was evaluated. Of 75 strains, none were agglutinated by E. cloacae O antisera or were sensitive to E. cloacae bacteriophages. In contrast, 70 strains reacted with Klebsiella capsular antisera. Two-thirds of the strains were lysed by Klebsiella typing phages. A set of five E. aerogenes bacteriocin producers classified 92% of strains into 15 sensitivity types. In conclusion, E. aerogenes may be typed with Klebsiella reagents, and the simple bacteriocin test provides further discrimination between strains. The limited number of capsular antigens in the species and their apparent similarity to Klebsiella capsular antigens warrant further investigation.

Comparison of polyclonal rabbit antisera with monoclonal antibodies for serological typing of Pseudomonas aeruginosa.

A panel of 219 distinct strains of Pseudomonas aeruginosa were serotyped with a set of monoclonal antibodies prepared against the serotype strains of the Homma scheme (J. Y. Homma, Jpn. J. Exp. Med. 46:329-336, 1976). A total of 87.6% were typable, and there was very good agreement with the corresponding polyclonal serotype. A high proportion of strains that were polyagglutinating or nontypable with polyclonal antisera were agglutinated by antibody towards Homma group M.

Sylvatic trichinosis in Ontario, Canada.

Samples of muscle from 4,773 specimens of 18 species of wild mammals from Ontario were examined for Trichinella. One of 12 mink (Mustela vison), 83 of 1,821 fisher (Martes pennanti) and 68 of 1,980 marten (Martes americana) had T. spiralis. Prevalences of infections by Trichinella were determined for fisher and marten from the Algonquin region, over a 10-yr period. Prevalences ranged from 0.9-9.2% in fisher and 1.3-8.7% in marten indicating that the parasite is well-established in the region. Prevalences of Trichinella increased with age of both fisher and marten. Intensities determined for the 1981-1982 sample ranged from 0.4-15.8 larvae/g for fisher and 22.4-159.7 larvae/g for marten. Higher intensities were not correlated with older hosts. Fisher and marten appeared to be the key hosts maintaining Trichinella in the Algonquin region, but transmission dynamics were unclear. Transmission may include an unidentified small rodent or other host and natural carrion-feeding.

Amniotic fluid embolism: prophylaxis with heparin and aspirin.

The thromboplastic activity of amniotic fluid (AF) from women in labor may be a significant factor in amniotic fluid embolism (AFE) and obstetric disseminated intravascular coagulation (DIC). Infusion of AF from women in labor into laboratory animals was found to depress the platelet count, as seen in DIC. In this study we also investigated the ability of heparin and aspirin to block the thromboplastic activity and thrombocytopenia subsequent to AF infusion. In animals, heparin prophylaxis before infusion of AF prevented thrombocytopenia, whereas aspirin prophylaxis did not. Heparin prophylaxis may be useful in the management of coagulation defects associated with AFE and labor.