绘制康复之路:通过图表理论探索创伤性脑损伤并发症--探索益处与挑战

Shyam Kumar Sudhakar, Kaustav Mehta
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引用次数: 0

摘要

创伤性脑损伤(TBIs)的特点是具有广泛的并发症,会对受影响者的福祉造成削弱性影响。从长远来看,创伤性脑损伤与多种精神和医疗并发症有关。此外,没有任何药物可以预防与原发性损伤相关的继发性损伤。在这篇透视文章中,我们建议通过构建疾病合并症网络来应用图论,以识别高风险患者群体,为受影响人群提供预防性护理,并减轻疾病负担。我们描述了与监测创伤性脑损伤受试者合并症发展相关的挑战,并解释了疾病合并症网络如何通过预防疾病相关并发症来减轻疾病负担。我们进一步讨论了用于构建疾病并发症网络的各种方法,并解释了从网络中得出的特征如何帮助识别可能有患创伤后并发症风险的受试者。最后,我们探讨了利用图论成功管理创伤后并发症可能面临的挑战。
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Charting paths to recovery: Navigating traumatic brain injury comorbidities through graph theory–exploring benefits and challenges

Traumatic brain injuries (TBIs) are characterized by widespread complications that exert a debilitating effect on the well-being of the affected individual. TBIs are associated with a multitude of psychiatric and medical comorbidities over the long term. Furthermore, no medications prevent secondary injuries associated with a primary insult. In this perspective article, we propose applying graph theory via the construction of disease comorbidity networks to identify high-risk patient groups, offer preventive care to affected populations, and reduce the disease burden. We describe the challenges associated with monitoring the development of comorbidities in TBI subjects and explain how disease comorbidity networks can reduce disease burden by preventing disease-related complications. We further discuss the various methods used to construct disease comorbidity networks and explain how features derived from a network can help identify subjects who might be at risk of developing post-traumatic comorbidities. Lastly, we address the potential challenges of using graph theory to successfully manage comorbidities following a TBI.

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