Network analysis and relationship of symptom factors to functional outcomes and quality of life following mild traumatic brain injury: a TRACK-TBI study.
Network analysis and relationship of symptom factors to functional outcomes and quality of life following mild traumatic brain injury: a TRACK-TBI study.
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DOI：
10.3389/fneur.2023.1308540
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发表时间：
2023
影响因子：
3.4
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中科院分区：
文献类型：
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轻度创伤性脑损伤(MTBI)是一种异质性损伤，很难定性和处理。使用横断面网络分析(NA)来概念化mTBI症状，为确定mTBI症状之间的关系提供了一种创新的解决方案。网络理论的中心性假设假设，网络中的某些症状对网络的其余部分具有更相关的(中心)或高于平均水平的影响。然而，还没有研究使用NA来表征在美国一级创伤中心急诊科就诊的一组患者中的症状之间的相互关系，以及亚急性中枢症状与长期结果的关系。2013年至2019年在18个 美国一级创伤中心接受评估的mTBI(格拉斯哥昏迷评分13-15)患者在伤后2 周(W2)(n = 1,593)、伤后3个 月(M3)、6个 月(M6)和12个 月(M12)完成了里弗米德震荡后症状问卷(RPQ)。根据每个时间点的RPQ分量表分数绘制网络图。W2的RPQ评分与M6和M12的功能和生活质量结果相关。网络结构在不同的时间点上没有不同，表明症状/因素在不同时间对整个症状网络的影响没有差异。认知因素在W2(1.761)、M3(1.245)和M6(1.349)的预期影响最大。疲劳对M12的预期影响最大(1.275)。情绪因素是唯一一个在任何时间点都具有预期影响的节点>；1，表明情绪症状对总体症状负担的影响不成比例(M3 = 1.011；M6 = 1.076)。与先前验证的人口统计学和临床协变量相比，损伤后2周的几个症状因素与损伤后6个月和12个 月时的不完全恢复和/或较差的损伤相关生活质量有更强的相关性。网络分析表明，情绪、认知和疲劳症状可能是这一人群有用的治疗目标，因为整个症状网络的高度中心性和激活潜力。
Mild traumatic brain injury (mTBI) is a heterogenous injury which can be difficult to characterize and manage. Using cross-sectional network analysis (NA) to conceptualize mTBI symptoms offers an innovative solution to identify how mTBI symptoms relate to each other. The centrality hypothesis of network theory posits that certain symptoms in a network are more relevant (central) or have above average influence over the rest of the network. However, no studies have used NA to characterize the interrelationships between symptoms in a cohort of patients who presented with mTBI to a U.S. Level 1 trauma center emergency department and how subacute central symptoms relate to long-term outcomes. Patients with mTBI (Glasgow Coma Scale = 13–15) evaluated across 18 U.S. Level 1 trauma centers from 2013 to 2019 completed the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) at 2 weeks (W2) post-injury (n = 1,593) and at 3 months (M3), 6 months (M6), and 12 months (M12) post-injury. Network maps were developed from RPQ subscale scores at each timepoint. RPQ scores at W2 were associated with M6 and M12 functional and quality of life outcomes. Network structure did not differ across timepoints, indicating no difference in symptoms/factors influence on the overall symptom network across time. The cognitive factor had the highest expected influence at W2 (1.761), M3 (1.245), and M6 (1.349). Fatigue had the highest expected influence at M12 (1.275). The emotional factor was the only other node with expected influence >1 at any timepoint, indicating disproportionate influence of emotional symptoms on overall symptom burden (M3 = 1.011; M6 = 1.076). Several symptom factors at 2-weeks post-injury were more strongly associated with incomplete recovery and/or poorer injury-related quality of life at 6 and 12 months post-injury than previously validated demographic and clinical covariates. The network analysis suggests that emotional, cognitive, and fatigue symptoms may be useful treatment targets in this population due to high centrality and activating potential of the overall symptom network.
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