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

创伤性脑损伤 物理医学与康复 医学 背景(考古学) 脑老化 萎缩 头部受伤 人口 神经科学 心理学 认知 病理 精神科 环境卫生 生物 古生物学
作者
Hamed Abdi,David Sánchez‐Molina,Silvia García‐Vilana,Vafa Rahimi-Movaghar
出处
期刊:Progress in Biomedical Engineering 卷期号:7 (2): 022001-022001
标识
DOI:10.1088/2516-1091/ada654
摘要

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.
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