Quantifying the effect of cerebral atrophy on head injury risk in elderly individuals: Insights from computational biomechanics and experimental analysis of bridging veins

Mortality in Moderate to Severe Traumatic Brain Injury in Elderly Polytrauma Patients at a European Level 1 Trauma Centre-A Retrospective Cohort Study

Introduction: Traumatic brain injury (TBI) remains a significant challenge in older polytrauma patients, with age being a major determinant of outcomes. While mortality predictors have been studied in general polytrauma populations, less is known about specific risk factors in older adults with TBI. Methods: This retrospective study analysed data from 304 polytrauma patients over 18 years of age treated at a Level 1 trauma centre between 2013 and 2023. Patients were divided into three age categories: 18-64 years (n = 189), 65-84 years (n = 92), and ≥85 years (n = 23). The analysis included demographics, injury patterns, clinical indicators, surgical treatments, and in-hospital mortality to identify key mortality predictors. Results: The mean age was 54.5 years (SD 22.2); 72% of patients were male. In-hospital mortality was 36.3% overall, increasing to 60.8% in patients aged ≥85. TBI severity was moderate in 25% and severe in 75% of cases. Older patients were less frequently admitted to the ICU and more often managed conservatively. ICU admission was significantly lower in patients aged 65-84 (24.5%) and ≥85 (19.4%) compared to the 18-64 group (70.0%). Multivariate analysis identified age, male sex, and severe TBI as significant predictors of 30-day mortality. Conclusions: TBI management in older polytrauma patients requires distinct approaches due to higher mortality and poorer outcomes. Age is a critical risk factor, highlighting the need for tailored triage systems and ICU strategies to improve care and prognosis in this vulnerable population.

Statistical mechanics of bone damage: a constitutive model

After the elastic regime is surpassed, cortical bone exhibits significant microcracking in its post-elastic mechanical behavior. This work develops a thermodynamically consistent, nonlinear constitutive model based on statistical mechanics, designed to predict the stress-strain relationship and the progression of inter-osteon microcracking. To assess the model's sufficiency, precise tensile and bending tests were performed in comparison to empirical curves that illustrated theoretical predictions of constitutive relationships. Moreover, entropy increases were quantitatively assessed using model parameters refined through experimental data. A large-size sample was utilized, comprising 51 dog-bone-shaped cortical bone specimens from the 4th ribs of various subjects for uniaxial tensile tests, and 15 complete fourth ribs for bending tests. Displacement and strain fields were meticulously recorded using digital image correlation and video analysis. The model demonstrated robustness, accurately fitting the data from all experimental specimens and revealing correlations between constitutive parameters and anthropometric variables. Entropy calculations provide insights into the behavior of the bone under varying strains: microcracking is minimal at low strains with stress nearly proportional to strain, escalating significantly beyond a critical threshold, thus challenging the linear relationship between stress and strain.

Biomechanical perspectives on traumatic brain injury in the elderly: a comprehensive review

Traumatic brain injuries (TBIs) pose a significant health concern among the elderly population, influenced by age-related physiological changes and the prevalence of neurodegenerative diseases. Understanding the biomechanical dimensions of TBIs in this demographic is vital for developing effective preventive strategies and optimizing clinical management. This comprehensive review explores the intricate biomechanics of TBIs in the elderly, integrating medical and aging studies, experimental biomechanics of head tissues, and numerical simulations. Research reveals that global brain atrophy in normal aging occurs at annual rates of -0.2% to -0.5%. In contrast, neurodegenerative diseases such as Alzheimer's, Parkinson's, and multiple sclerosis are associated with significantly higher rates of brain atrophy. These variations in atrophy rates underscore the importance of considering differing brain atrophy patterns when evaluating TBIs among the elderly. Experimental studies further demonstrate that age-related changes in the mechanical properties of critical head tissues increase vulnerability to head injuries. Numerical simulations provide insights into the biomechanical response of the aging brain to traumatic events, aiding in injury prediction and preventive strategy development tailored to the elderly. Biomechanical analysis is essential for understanding injury mechanisms and forms the basis for developing effective preventive strategies. By incorporating local atrophy and age-specific impact characteristics into biomechanical models, researchers can create targeted interventions to reduce the risk of head injuries in vulnerable populations. Future research should focus on refining these models and integrating clinical data to better predict outcomes and enhance preventive care. Advancements in this field promise to improve health outcomes and reduce injury risks for the aging population.

Numerical investigation of knee prosthesis stresses in daily activities: Insight into knee rehabilitation and Creation of a new optimal model

Total knee arthroplasty (TKA) is a cornerstone in addressing knee joint disorders, significantly enhancing patients' quality of life. However, despite technological advancements, a comprehensive understanding of the dynamic stresses experienced by knee prostheses during daily activities, particularly under rehabilitation interventions, remains elusive. This study aims to bridge this gap by employing numerical simulations and finite element analysis to elucidate these dynamic stresses and their interaction with rehabilitation protocols. A real-life knee replacement prosthesis model was meticulously constructed through coordinate measuring and 3D scanning, facilitating detailed finite element analysis in ANSYS Workbench version 17.1. Two distinct boundary conditions and loading scenarios were applied, with comparisons made between linear and nonlinear material assumptions. The simulation results using these different boundary condition methods revealed minimal differences. Specifically, at a knee angle of 0°, the relative stress error rate between the two boundary condition types was approximately 1 % (1.11 MPa and 1.099 MPa, respectively). At 15° and 90°, the error rates were 1.9 % and 0.56 %, respectively (10.275 MPa and 10.078 MPa at 15°; 10.275 MPa and 10.078 MPa at 90°). Given these minimal differences, the first type of boundary condition was adopted for the subsequent scenarios to enhance convergence efficiency in the analysis. Moreover, comparative analyses between linear and nonlinear material behaviors demonstrated acceptable agreement, offering insights into potential efficiency gains in simulation methodologies. Building on this foundation, an optimized tibial model was proposed, incorporating geometric alterations to the tray. Quantitative assessments revealed significant reductions, with von Mises stress decreasing by 23.35 % and equivalent strain by 17 % at a knee angle of 140°. Further evaluations at varying angles, including 60°, consistently showed positive influences on stress and strain. These quantitative findings not only contribute valuable insights into the mechanical behavior of knee prostheses but also provide tangible evidence for the efficacy of linear material behavior assumptions. The proposed optimized model exhibits promising potential for enhancing the design and performance of knee prostheses, particularly under critical loading conditions. In conclusion, these results underscore the importance of a nuanced understanding of knee prosthesis behavior during rehabilitation, offering a quantitative foundation for refining existing designs and informing the development of next-generation prostheses.

Quantitative assessment of traumatic brain injury risk in diverse age groups of females: Insights from computational biomechanics

Traumatic Brain Injury (TBI) stands as a multifaceted health concern, exhibiting varying influences across human population. This study delves into the biomechanical complexities of TBI within gender-specific contexts, focusing on females. Our primary objective is to investigate distinctive injury mechanisms and risks associated with females, emphasizing the imperative for tailored investigations within this cohort. By employing Fluid-Structure Interaction (FSI) Analysis, we conducted simulations to quantify biomechanical responses to traumatic forces across diverse age groups of females. The study utilized a scaling technique to create finite element models (FEMs). The young female FEM, based on anthropometric data, showcased a 15 % smaller head geometry compared to the young male FEM. Moreover, while the elderly female FEM closely mirrored the young female FEM in most structural aspects, it showed distinctive features such as brain atrophy and increased cerebrospinal fluid (CSF) layer thickness. Notably, the child female FEM (ages 7-11 years) replicated around 95 % of the young female FEM's geometry. These structural distinctions meticulously captured age-specific variations across our modeled female age groups. It's noteworthy that identical conditions, encompassing impact intensity, loading type, and boundary conditions, were maintained across all FEMs in this biomechanical finite element analysis, ensuring comparative results. The findings unveiled significant variations in frontal and occipital pressures among diverse age groups, highlighting potential age-related discrepancies in TBI susceptibility among females. These variations were primarily linked to differences in anatomical features, including brain volume, CSF thickness, and brain condition, as the same material properties were used in the FEMs. These results were approximately 4.70, 6.33 and 6.43 % in frontal area of brain in diverse age groups of females (young, elderly, and child) respectively compared to young male FEM. Comparing the FEM results between the young female and the elderly female, we observed a decrease in occipital brain pressure at the same point, reducing from 171,993 to 167,793 Pa, marking an approximate 2.5 % decrease. While typically the elderly exhibit greater brain vulnerability compared to the young, our findings showcase a reduction in brain pressure. Notably, upon assessing the relative movement between the brain and the skull at the point located in occipital area, we observed greater relative movement in the elderly (1.8 mm) compared to the young female (1.04 mm). Therefore, brain atrophy increases the range of motion of the brain within the cranial space. The study underscores the critical necessity for nuanced TBI risk assessment tailored to age and gender, emphasizing the importance of age-specific protective strategies in managing TBIs across diverse demographics. Future research employing individual modeling techniques and exploring a wider age spectrum holds promise in refining our understanding of TBI mechanisms and adopting targeted approaches to mitigate TBI in diverse groups.

Revealing the role of material properties in impact-related injuries: Investigating the influence of brain and skull density variations on head injury severity

Traumatic brain injuries (TBI) resulting from head impacts are a major public health concern, which prompted our research to investigate the complex relationship between the material properties of brain tissue and the severity of TBI. The goal of this research is to investigate how variations in brain and skull density influence the vulnerability of brain tissue to traumatic injury, thereby enhancing our understanding of injury mechanism. To achieve this goal, we employed a well-validated finite element head model (FEHM). The current investigation was divided into two phases: in the first one, three distinct brain viscoelastic materials that had been utilized in prior studies were analyzed. The review of the properties of these three materials has been meticulous, encompassing both the spectrum of mechanical properties and the behaviors that are relevant to the way in which brain tissue reacts to traumatic loading conditions. In the second phase, the material properties of both the brain and skull tissue, alongside the impact conditions, were held constant. After this step, the focus was directed towards the variation of density in the brain and skull, which was consistent with the results obtained from previous experimental investigations, in order to determine the precise impact of these variations in density. This approach allowed a more profound comprehension of the impacts that density had on the simulation results. In the first phase, Material No. 2 exhibited the highest maximum first principal strain value in the frontal region (ε max = 15.41 % ), indicating lower stiffness to instantaneous deformation. This characteristic suggests that Material No. 2 may deform more extensively upon impact, potentially increasing the risk of injury due to its viscoelastic behavior. In contrast, Material No. 1, with a lower maximum first principal strain in the frontal region (ε max = 7.87 % ), displayed greater stiffness to instantaneous deformation, potentially reducing the risk of brain injury upon head impact. The second phase provided quantitative findings revealing a proportional relationship between brain tissue density and the pressures experienced by the brain. A 2 % increase in brain tissue density corresponded to approximately a 1 % increase in pressure on the brain tissue. Similarly, changes in skull density exhibited a similar quantitative relationship, with a 6 % increase in skull density leading to a 2.5 % increase in brain pressure. This preliminary approximate ratio of 2 to 1 between brain and skull density variations provides an initial quantitative framework for assessing the impact of density changes on brain vulnerability. These findings have several implications for the development of protective measures and injury prevention strategies, particularly in contexts where head trauma is a major issue.

Risk of using smartphones while walking for digital natives in realistic environments: Effects of cognitive-motor interference

The effect of using smartphones while walking on the cognitive and physical abilities of the "digital native" generation, i.e., individuals who have grown up in a digital media-centric environment, remains poorly understood. This study evaluated the effects of cognitive-motor interference on the use of smartphones while walking in children and young adults. The study involved 50 individuals from the digital age generation, including 24 children and 26 young adults. The study encompassed three experimental conditions, in which participants were instructed to traverse a distance of 60 m. The initial condition functioned as a control, wherein the participants walked without supplementary stimuli. In the second condition, the participants were provided with explicit instructions to grasp the smartphone device and position it in front of their chest by using both hands. This manipulation introduced a postural component into the experimental setup. The third condition required participants to be ambulatory while concurrently engaging in a cognitive task, namely, participating in a game that necessitated focused attention. Gait parameters were obtained by using inertial measurement unit sensors. Subsequently, the acquired gait characteristics were converted into dual-task costs (DTC). In the cognitive condition, children exhibited significantly greater DTC values for gait speed (76%), stride length (79%), stride time (102%), and stride length coefficient of variation (CV) than the young adults (p < 0.025). Moreover, as shown by the increased CV, a significant association exists between poor performance in smartphone games among children and increased variability in stride length. In children, the DTC of stride time CV decreased as smartphone game scores increased (R2 = 16.5%), and the DTC of stride length CV decreased more markedly as smartphone game scores increased (R2 = 28.2%). In conclusion, children are at a higher risk of pedestrian accidents when using smartphones while walking compared to young adults.