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澳大利亚中重度创伤性脑损伤后预测预后及监测干预效果的健康信息学方法

AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury.

作者信息

Fitzgerald Melinda, Ponsford Jennie, Lannin Natasha A, O'Brien Terence J, Cameron Peter, Cooper D James, Rushworth Nick, Gabbe Belinda

机构信息

Curtin Health Innovation Research Institute, Curtin University, Nedlands, Western Australia, Australia.

Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia.

出版信息

Neurotrauma Rep. 2022 Jun 7;3(1):217-223. doi: 10.1089/neur.2022.0002. eCollection 2022.

Abstract

Predicting and optimizing outcomes after traumatic brain injury (TBI) remains a major challenge because of the breadth of injury characteristics and complexity of brain responses. AUS-TBI is a new Australian Government-funded initiative that aims to improve personalized care and treatment for children and adults who have sustained a TBI. The AUS-TBI team aims to address a number of key knowledge gaps, by designing an approach to bring together data describing psychosocial modulators, social determinants, clinical parameters, imaging data, biomarker profiles, and rehabilitation outcomes in order to assess the influence that they have on long-term outcome. Data management systems will be designed to track a broad range of suitable potential indicators and outcomes, which will be organized to facilitate secure data collection, linkage, storage, curation, management, and analysis. It is believed that these objectives are achievable because of our consortium of highly committed national and international leaders, expert committees, and partner organizations in TBI and health informatics. It is anticipated that the resulting large-scale data resource will facilitate personalization, prediction, and improvement of outcomes post-TBI.

摘要

由于创伤性脑损伤(TBI)的损伤特征广泛且脑反应复杂,预测和优化其预后仍然是一项重大挑战。澳大利亚创伤性脑损伤研究计划(AUS-TBI)是澳大利亚政府资助的一项新倡议,旨在改善对遭受创伤性脑损伤的儿童和成人的个性化护理和治疗。AUS-TBI团队旨在通过设计一种方法来汇集描述心理社会调节因素、社会决定因素、临床参数、成像数据、生物标志物谱和康复结果的数据,以评估它们对长期预后的影响,从而解决一些关键的知识空白。数据管理系统将被设计用于跟踪广泛的合适潜在指标和结果,这些指标和结果将被组织起来以促进安全的数据收集、关联、存储、管理、管理和分析。相信由于我们由致力于TBI和健康信息学的国内外顶尖领导者、专家委员会及合作伙伴组织组成的联盟,这些目标是可以实现的。预计由此产生的大规模数据资源将促进TBI后预后的个性化、预测和改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90f3/9279124/b80eea9fccff/neur.2022.0002_figure1.jpg

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