VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Phenotypes of Persistent Comorbidity in Post‐9/11 Era Veterans with mTBI
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:后 9/11 时代患有 mTBI 的退伍军人持续合并症的表型
基本信息
- 批准号:10001099
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:AcuteAlgorithmsAreaBehaviorBrain InjuriesCaringCharacteristicsChronicChronic CareDataData SourcesEpidemiologyFunctional disorderHealth systemIndividualInjuryInpatientsLearningMental HealthMethodsMilitary PersonnelModelingNerve DegenerationNervous System TraumaNeurodegenerative DisordersNeurosecretory SystemsOutcomeOutpatientsPainPathway interactionsPharmacy facilityPhenotypePrevalenceProcessPsychological reinforcementRegistriesRiskScienceSelf-Injurious BehaviorSeveritiesSleepSourceSubstance Use DisorderSupport SystemTextTraumaVeteransWorkcohortcomorbiditydeep learningeconomic outcomehealth dataimprovedinterestlongitudinal analysismild traumatic brain injuryneurosensorypsychologicscreening
项目摘要
The Chronic Effects of Neurotrauma Warfighter Epidemiology Cohort was developed to identify
phenotypes of comorbidity among deployed Post-9/11 Veterans in order to compare emergence
of neurosensory, neurodegenerative, pain, and mental health comorbidity in Veterans TBI. The
LIMBIC extension of the Warfighter Epidemiology Cohort will extend the work begun by CENC
in which we identified a cohort of Post-9/11 Veterans and identified comorbidity phenotypes. We
also obtained DoD trauma registry (DODTR) data, where available, and Military Health System
(MHS) inpatient, outpatient, and pharmacy data that was included in the DoD Mental Health
Data Cube. We now propose to expand upon this important data source for over 600,000
deployed SM’s to include a broader cohort of Post-9/11 era (deployed and nondeployed
Veterans and additional data sources that provide unique opportunities to examine long-term
comorbidity phenotypes and develop risk models for comorbidities of interest such as
neurodegenerative disease, SUD, psychological comorbidities, and self-harm behaviors.
These data will allow us to accomplish the following specific aims:
Aim 1: Using “all sources” TBI severity algorithm and NLP/text embedding methods, identify
phenotypes of mTBI in DoD and DoD+VA data that incorporate acute injury, mechanism of
injury, and blast exposure.
Aim 2: Identify prevalence of key comorbidities and outcomes at baseline, before and after
mTBI exposure, and in VA (where relevant) and compare those rates by TBI severity and
study group.
Aim 3: Use deep learning models that incorporate mTBI phenotype, acute and chronic
treatment approaches, and emergence of diverse comorbidities to develop risk scores for
poor military outcomes and developing key comorbidities.
Aim 4: Use deep learning models to identify optimal processes of care for mTBI.
We will use data in DaVINCI to identify a cohort of Veterans who receive longitudinal VA care
(at least once a year for three or more years between FY2002 and FY19 (at least one of which is
after 2007 when TBI screening was mandated. We will also identify individuals who did not
receive VA care. We will then categorize those with and without VA care as deployed and not
deployed, creating four study groups: a) deployed with VA care; b) deployed without VA care; c)
not deployed with VA care; d) not deployed without VA care. We will compile VA and DoD data
sources and identify key comorbidities (Neuroendocrine dysfunction, substance use disorder,
mental health conditions, pain conditions, sleep conditions, self-harm behaviors) and TBI
characteristics. Those data will be used for machine/deep learning models that will develop TBI
phenotypes, comorbidity phenotypes, and model risk scores for developing key comorbidities,
and optimal processes of care for mTBI.
Conducting these analyses for these four study groups will inform TBI pathways of care and
illuminate specific target areas to improve acute TBI care and subsequent support systems for
chronic care following TBI.
对神经创伤战士的慢性影响进行流行病学队列研究
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mary Jo Pugh其他文献
Mary Jo Pugh的其他文献
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{{ truncateString('Mary Jo Pugh', 18)}}的其他基金
VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Phenotypes of Persistent Comorbidity in Postâ9/11 Era Veterans with mTBI
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:后 9/11 时代患有 mTBI 退伍军人持续合并症的表型
- 批准号:
10269013 - 财政年份:2019
- 资助金额:
-- - 项目类别:
VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Phenotypes of Persistent Comorbidity in Postâ9/11 Era Veterans with mTBI
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:后 9/11 时代患有 mTBI 退伍军人持续合并症的表型
- 批准号:
10534112 - 财政年份:2019
- 资助金额:
-- - 项目类别:
VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Data and Biostatistics Core
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:数据和生物统计学核心
- 批准号:
10269014 - 财政年份:2019
- 资助金额:
-- - 项目类别:
VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Data and Biostatistics Core
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:数据和生物统计学核心
- 批准号:
10534111 - 财政年份:2019
- 资助金额:
-- - 项目类别:
VA-DoD Long-Term Impact of Military-Relevant Brain Injury Consortium (LIMBIC): Data and Biostatistics Core
VA-DoD 军事相关脑损伤联盟 (LIMBIC) 的长期影响:数据和生物统计学核心
- 批准号:
10000608 - 财政年份:2019
- 资助金额:
-- - 项目类别:
Secondary Analysis of Existing Databases in Traumatic Brain Injury to Explore Outcomes Relevant to Medical Rehabilitation
对现有的创伤性脑损伤数据库进行二次分析,探索与医疗康复相关的结果
- 批准号:
9173126 - 财政年份:2016
- 资助金额:
-- - 项目类别:
Validating Cases of Dementia and Mild Cognitive Impairment in OEF/OIF Veterans
验证 OEF/OIF 退伍军人的痴呆症和轻度认知障碍病例
- 批准号:
9033326 - 财政年份:2016
- 资助金额:
-- - 项目类别:
Validating Cases of Dementia and Mild Cognitive Impairment in OEF/OIF Veterans
验证 OEF/OIF 退伍军人的痴呆症和轻度认知障碍病例
- 批准号:
9198736 - 财政年份:2016
- 资助金额:
-- - 项目类别:
Secondary Analysis of Existing Databases in Traumatic Brain Injury to Explore Outcomes Relevant to Medical Rehabilitation
对现有的创伤性脑损伤数据库进行二次分析,探索与医疗康复相关的结果
- 批准号:
9650254 - 财政年份:2016
- 资助金额:
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VA Vascular Injury Study (VAVIS): VA-DoD extremity injury outcomes collaboration
VA 血管损伤研究 (VAVIS):VA-DoD 肢体损伤结果合作
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9145503 - 财政年份:2015
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