Tso Samantha, Saha Ashirbani, Cusimano Michael D
Division of Neurosurgery, St. Michael's Hospital, Toronto, Ontario, Canada.
Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.
Neurotrauma Rep. 2021 Mar 12;2(1):149-164. doi: 10.1089/neur.2020.0047. eCollection 2021.
The Traumatic Brain Injury Model Systems (TBIMS) is the largest longitudinal TBI data set in the world. Our study reviews the works using TBIMS data for analysis in the last 5 years. A search (2015-2020) was conducted across PubMed, EMBASE, and Google Scholar for studies that used the National Institute on Disability, Independent Living and Rehabilitation Research NIDILRR/VA-TBIMS data. Search terms were as follows: ["TBIMS" national database] within PubMed and Google Scholar, and ["TBIMS" AND national AND database] on EMBASE. Data sources, study foci (in terms of data processing and outcomes), study outcomes, and follow-up information usage were collected to categorize the studies included in this review. Variable usage in terms of TBIMS' form-based variable groups and limitations from each study were also noted. Assessment was made on how TBIMS' objectives were met by the studies. Of the 74 articles reviewed, 23 used TBIMS along with other data sets. Fifty-four studies focused on specific outcome measures only, 6 assessed data aspects as a major focus, and 13 explored both. Sample sizes of the included studies ranged from 11 to 15,835. Forty-two of the 60 longitudinal studies assessed follow-up from 1 to 5 years, and 15 studies used 10 to 25 years of the same. Prominent variable groups as outcome measures were "Employment," "FIM," "DRS," "PART-O," "Satisfaction with Life," "PHQ-9," and "GOS-E." Limited numbers of studies were published regarding tobacco consumption, the Brief Test of Adult Cognition by Telephone (BTACT), the Supervision Rating Scale (SRS), general health, and comorbidities as variables of interest. Generalizability was the most significant limitation mentioned by the studies. The TBIMS is a rich resource for large-sample longitudinal analyses of various TBI outcomes. Future efforts should focus on under-utilized variables and improving generalizability by validation of results across large-scale TBI data sets to better understand the heterogeneity of TBI.
创伤性脑损伤模型系统(TBIMS)是世界上最大的创伤性脑损伤纵向数据集。我们的研究回顾了过去5年中使用TBIMS数据进行分析的研究。在PubMed、EMBASE和谷歌学术上进行了搜索(2015 - 2020年),以查找使用美国国家残疾、独立生活和康复研究所在职军人医疗管理局创伤性脑损伤模型系统(NIDILRR/VA - TBIMS)数据的研究。搜索词如下:在PubMed和谷歌学术中为["TBIMS"国家数据库],在EMBASE上为["TBIMS" AND国家AND数据库]。收集了数据来源、研究重点(在数据处理和结果方面)、研究结果以及随访信息的使用情况,以便对本综述中纳入的研究进行分类。还记录了各研究在TBIMS基于表单的变量组方面的变量使用情况和局限性。评估了这些研究在多大程度上实现了TBIMS的目标。在所审查的74篇文章中,23篇将TBIMS与其他数据集一起使用。54项研究仅关注特定的结果指标,6项研究将数据方面作为主要重点进行评估,13项研究对两者都进行了探索。纳入研究的样本量从11到15835不等。60项纵向研究中的42项评估了1至5年的随访情况,15项研究使用了相同的10至25年随访数据。作为结果指标的突出变量组有“就业”、“功能独立性测量(FIM)”、“残疾评定量表(DRS)”、“PART - O”、“生活满意度”、“患者健康问卷 - 9(PHQ - 9)”和“扩展格拉斯哥预后量表(GOS - E)”。关于烟草消费、成人电话认知简短测试(BTACT)、监督评定量表(SRS)、一般健康状况和共病作为感兴趣变量的研究发表数量有限。普遍性是这些研究提到的最显著局限性。TBIMS是对各种创伤性脑损伤结果进行大样本纵向分析的丰富资源。未来的工作应集中在未充分利用的变量上,并通过跨大规模创伤性脑损伤数据集验证结果来提高普遍性,以便更好地理解创伤性脑损伤的异质性。