In this study, computational simulations and experiments were performed to investigate the mechanical behavior of the aorta wall because of the increasing occurrences of aorta-related diseases. The study focused on the deformation and strength of porcine and healthy human abdominal aortic tissues under uniaxial tensile loading. The experiments for the mechanical behavior of the arterial tissue were conducted using a uniaxial tensile test apparatus to validate the simulation results. In addition, the strength and stretching of the tissues in the abdominal aorta of a healthy human as a function of age were investigated based on the uniaxial tensile tests. Moreover, computational simulations using the ABAQUS finite element analysis program were conducted on the experimental scenarios based on age, and the Holzapfel-Gasser-Ogden (HGO) model was applied during the simulation. The material parameters and formulae to be used in the HGO model were proposed to identify the failure stress and stretch correlation with age.abdominal aorta specimens were investigated and analyzed based on age, and the material constants associated with the elastic modulus, stress, and strain in the numerical model were estimated from the numerical simulations according to age. From these results, the correlation between age and material constants was examined, and the formulae for estimating material constants based on age were proposed.

(1) Background: Metallic materials are predominantly used for spinal implants, and they can damage adjacent bones and intervertebral discs (IVDs) owing to their high elastic moduli. Consequently, there is a possibility that serious complications, such as kyphosis, may occur as the sequelae progresses. In this study, the behavior of the lumbar spine and implant system was evaluated using the finite element (FE) method, by applying the porous structure to the spinal implants to resolve the problem of metal spinal implants. (2) Methods: An FE model was developed for lumbar 3–5, and it was assumed that, owing to disease occurrence, spinal implants were placed in lumbar 3–4. Currently, Ti–6Al–4V is the most commonly used material for spinal implants. The shape of the porous structure was set in the form of a diamond, and porosity was varied over nine values ranging from 0 to 81%. Finally, equivalent material properties of the porous structure were derived using the Ramberg–Osgood formula, with reference to experimental study. (3) Results: The range of motion was increased, and the equivalent stress of adjacent IVD, and adjacent bone stress of the pedicle screw and spinal cage, decreased with increasing porosity of the spinal implants. As the porosity decreased, the safety factor exhibited a tendency to decrease rapidly. (4) Conclusion: Motor capacity of the spine was improved, and the equivalent stress of the spinal tissues decreased with the increasing porosity of the spinal implants. Therefore, in the future, porous structures can significantly contribute to the improvement of implants through continuous complementary research.

ObjectiveThis study aimed to assess whether rotational thermoelectrometry (ROTEM) data could improve the massive transfusion (MT) prediction model.MethodThis was a single-center, retrospective study. Patients who presented to the trauma center and underwent ROTEM between 2016 and 2020 were included. The primary and secondary outcomes were massive transfusion and in-hospital mortality, respectively. We constructed two models using multivariate logistic regression with backward conditional stepwise elimination (Model 1: without ROTEM parameter and Model 2: with ROTEM parameters). The area under the receiver operating characteristic curve (AUROC) was calculated to assess the predictive ability of the models.ResultIn total, 969 patients were included; 196 (20.2%) received MT. The in-hospital mortality rate was 14.1%. For MT, the AUROC was 0.854 (95% confidence interval [CI], 0.825-0.883) and 0.860 (95% CI, 0.832-0.888) for Model 1 and 2, respectively. For in-hospital mortality, the AUROC was 0.886 (95% CI, 0.857-0.915) and 0.889 (95% CI, 0.861-0.918) for Model 1 and 2, respectively. The AUROC values for Models 1 and 2 were not statistically different for either MT or in-hospital mortality.ConclusionWe found that addition of the ROTEM parameter did not significantly improve the predictive power of MT and in-hospital mortality in trauma patients.

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