Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Department of Aerospace Engineering, University of Cincinnati, Cincinnati, OH, USA.
Methods Mol Biol. 2022;2393:877-903. doi: 10.1007/978-1-0716-1803-5_47.
The best predictor of future injury is previous injury and this has not changed in a quarter century despite the introduction of evidence-based medicine and associated revisions to post-injury treatment and care. Nearly nine million sports-related injuries occur annually, and the majority of these require medical intervention prior to clearance for the athlete to return to play (RTP). Regardless of formal care, these athletes remain two to four times more likely to suffer a second injury for several years after RTP. In the case of children and young adults, this sets them up for a lifetime of negative health outcomes. Thus, the initial injury is the tipping point for a post-injury cascade of negative sequelae exposing athletes to more physical and psychological pain, higher medical costs, and greater risk of severe long-term negative health throughout their life. This chapter details the technologies and method that make up the automated Intelligent Phenotypic Plasticity Platform (IP)-a revolutionary new approach to the current standard of post-injury care that identifies and targets deficits that underly second injury risk in sport. IP capitalizes on the biological concept of phenotypic plasticity (PP) to quantify an athlete's functional adaptability across different performance environments, and it is implemented in two distinct steps: (1) phenomic profiling and (2) precision treatment. Phenomic profiling indexes the fitness and subsequent phenotypic plasticity of an individual athlete, which drives the personalization of the precision treatment step. IP leverages mixed-reality technologies to present true-to-life environments that test the athlete's ability to adapt to dynamic stressors. The athlete's phenotypic plasticity profile is then used to drive a precision treatment that systematically stresses the athlete, via a combination of behavioral-based and genetic fuzzy system models, to optimally enhance the athlete's functional adaptability. IP is computationally light-weight and, through the integration with mixed-reality technologies, promotes real-time prediction, responsiveness, and adaptation. It is also the first ever phenotypic plasticity-based precision medicine platform, and the first precision sports medicine platform of any kind.
未来受伤的最佳预测因素是之前的受伤，尽管引入了循证医学以及相关的受伤后治疗和护理修订，但这一点在四分之一个世纪以来并未改变。每年发生近 900 万例与运动相关的损伤，其中大多数在运动员重返运动（RTP）之前需要医疗干预。无论是否进行正式护理，这些运动员在 RTP 后几年内再次受伤的可能性仍高出两到四倍。对于儿童和年轻人来说，这使他们一生都面临负面健康后果的风险。因此，最初的受伤是受伤后一系列负面后果的转折点，使运动员遭受更多的身体和心理痛苦、更高的医疗费用，并增加整个生命周期内发生严重长期负面健康的风险。本章详细介绍了构成自动化智能表型可塑性平台（IP）的技术和方法，这是一种针对当前受伤后护理标准的革命性新方法，可识别和针对运动中再次受伤风险的潜在缺陷。IP 利用表型可塑性（PP）的生物学概念来量化运动员在不同表现环境中的功能适应性，它通过两个不同的步骤实现：（1）表型谱分析和（2）精准治疗。表型谱分析指标是个体运动员的适应性和随后的表型可塑性，这推动了精准治疗步骤的个性化。IP 利用混合现实技术呈现逼真的环境，以测试运动员适应动态应激源的能力。然后，运动员的表型可塑性谱用于驱动精准治疗，通过行为基于和遗传模糊系统模型的组合，系统地对运动员施加压力，以最佳地增强运动员的功能适应性。IP 计算量轻，并且通过与混合现实技术的集成，可促进实时预测、响应性和适应性。它也是第一个基于表型可塑性的精准医学平台，也是第一个任何类型的精准运动医学平台。
