Clinical utility of PTSD, resilience, sleep, and blast as risk factors to predict poor neurobehavioral functioning following traumatic brain injury: A longitudinal study in US military service members

被引:7
|
作者
Lange, Rael T. [1 ,2 ,3 ,4 ,11 ]
French, Louis M. [1 ,2 ,3 ,5 ]
Bailie, Jason M. [1 ,6 ,11 ]
Merritt, Victoria C. [7 ,8 ]
Pattinson, Cassandra L. [9 ]
Hungerford, Lars D. [1 ,10 ,11 ]
Lippa, Sara M. [2 ,3 ]
Brickell, Tracey A. [1 ,2 ,3 ,5 ,11 ]
机构
[1] Traumat Brain Injury Ctr Excellence, Silver Spring, MD 20910 USA
[2] Walter Reed Natl Mil Med Ctr, Bethesda, MD 20814 USA
[3] Natl Intrepid Ctr Excellence, Bethesda, MD 20814 USA
[4] Univ British Columbia, Vancouver, BC, Canada
[5] Uniformed Serv Univ Hlth Sci, Bethesda, MD 20814 USA
[6] Naval Hosp Camp Pendleton, Oceanside, CA USA
[7] VA San Diego Healthcare Syst, San Diego, CA USA
[8] Univ Calif San Diego, La Jolla, CA 92093 USA
[9] Univ Queensland, Brisbane, Qld, Australia
[10] Naval Med Ctr San Diego, San Diego, CA USA
[11] Gen Dynam Informat Technol, Falls Church, VA 22042 USA
关键词
Traumatic brain injury; Posttraumatic stress; Sleep disturbance; Resilience; Military; POSTTRAUMATIC-STRESS-DISORDER; DETECT SYMPTOM EXAGGERATION; QUALITY-OF-LIFE; VALIDITY-10; SCALE; HEALTH; DISTURBANCES; VETERANS; TBI; AFGHANISTAN; POPULATION;
D O I
10.1007/s11136-022-03092-4
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Purpose This study examined the clinical utility of post-traumatic stress disorder (PTSD), low resilience, poor sleep, and lifetime blast exposure as risk factors for predicting future neurobehavioral outcome following traumatic brain injury (TBI). Methods Participants were 591 U.S. military service members and veterans who had sustained a TBI (n = 419) or orthopedic injury without TBI (n = 172). Participants completed the Neurobehavioral Symptom Inventory, PTSD Checklist, and the TBI-Quality of Life (TBI-QOL) scale at baseline and follow-up. Results Using the four risk factors at baseline, 15 risk factor combinations were examined by calculating odds ratios to predict poor neurobehavioral outcome at follow-up (i.e., number of abnormal scores across five TBI-QOL scales [e.g., Fatigue, Depression]). The vast majority of risk factor combinations resulted in odds ratios that were considered to be clinically meaningful (i.e., >= 2.5) for predicting poor outcome. The risk factor combinations with the highest odds ratios included PTSD singularly, or in combination with poor sleep and/or low resilience (odds ratios = 4.3-72.4). However, poor sleep and low resilience were also strong predictors in the absence of PTSD (odds ratios = 3.1-29.8). Conclusion PTSD, poor sleep, and low resilience, singularly or in combination, may be valuable risk factors that can be used clinically for targeted early interventions.
引用
收藏
页码:2411 / 2422
页数:12
相关论文
共 49 条
  • [21] Influence of Bodily Injuries on Symptom Reporting Following Uncomplicated Mild Traumatic Brain Injury in US Military Service Members
    French, Louis M.
    Lange, Rael T.
    Iverson, Grant L.
    Ivins, Brian
    Marshall, Katherine
    Schwab, Karen
    JOURNAL OF HEAD TRAUMA REHABILITATION, 2012, 27 (01) : 63 - 74
  • [22] An examination of the clinical utility of "Cogniform Disorder'' within a sample of military service members with mild traumatic brain injury (TBI)
    Parmer, N. M.
    Law, W. A.
    Pancholi, S.
    French, L. M.
    CLINICAL NEUROPSYCHOLOGIST, 2008, 22 (03) : 423 - 423
  • [23] Outcomes Associated With Blast Versus Nonblast-Related Traumatic Brain Injury in US Military Service Members and Veterans: A Systematic Review
    Greer, Nancy
    Sayer, Nina
    Koeller, Eva
    Velasquez, Tina
    Wilt, Timothy J.
    JOURNAL OF HEAD TRAUMA REHABILITATION, 2018, 33 (02) : E16 - E29
  • [24] Resilience in Active Duty US Military Service Members: Factor Analysis and Prediction of Psychological Symptoms in a Mild Traumatic Brain Injury Sample
    Hershaw, Jamie
    Tra, John
    ARCHIVES OF CLINICAL NEUROPSYCHOLOGY, 2024, 39 (07) : 1131 - 1131
  • [25] Risk Factors Associated with Sleep Disturbance following Traumatic Brain Injury: Clinical Findings and Questionnaire Based Study
    Hou, Lijun
    Han, Xi
    Sheng, Ping
    Tong, Wusong
    Li, Zhiqiang
    Xu, Dayuan
    Yu, Mingkun
    Huang, Liuqing
    Zhao, Zhongxin
    Lu, Yicheng
    Dong, Yan
    PLOS ONE, 2013, 8 (10):
  • [26] Apolipoprotein E e4 is associated with worse self-reported neurobehavioral symptoms following uncomplicated mild traumatic brain injury in US military service members
    Lange, Rael T.
    Merritt, Victoria C.
    Brickell, Tracey A.
    Dalgard, Clifton L.
    Soltis, Anthony R.
    Hershaw, Jamie
    Lippa, Sara M.
    Gill, Jessica
    French, Louis M.
    BEHAVIOURAL BRAIN RESEARCH, 2021, 415
  • [27] The relationship between PTSD symptoms and tau and amyloid levels in US military service members with and without mild-moderate traumatic brain injury
    Lippa, Sara
    Gill, Jessica
    Lange, Rael
    Brickell, Tracey
    French, Louis
    BRAIN INJURY, 2017, 31 (6-7) : 865 - 865
  • [28] Diffusion Tensor Imaging and Postconcussion Symptom Reporting in US Military Service Members Following Mild to Moderate Traumatic Brain Injury
    Lange, R.
    Yeh, P.
    Oakes, T.
    Riedy, G.
    Ollinger, J.
    French, L.
    ARCHIVES OF CLINICAL NEUROPSYCHOLOGY, 2015, 30 (06) : 509 - 509
  • [29] Combat Exposure, PTSD Symptoms, and Cognition Following Blast-Related Traumatic Brain Injury in OEF/OIF/OND Service Members and Veterans
    Troyanskaya, Maya
    Pastorek, Nicholas J.
    Scheibel, Randall S.
    Petersen, Nancy J.
    McCulloch, Katie
    Wilde, Elisabeth A.
    Henson, Helene K.
    Levin, Harvey S.
    MILITARY MEDICINE, 2015, 180 (03) : 285 - 289
  • [30] Assessing the Clinical Utility of a Wearable Device for Physiological Monitoring of Heart Rate Variability in Military Service Members with Traumatic Brain Injury
    Uomoto, Jay M.
    Skopp, Nancy
    Jenkins-Guarnieri, Michael
    Reini, Josh
    Thomas, Drew
    Adams, Robert J.
    Tsui, Megan
    Miller, Shaun R.
    Scott, Beverly R.
    Pasquina, Paul F.
    TELEMEDICINE AND E-HEALTH, 2022, 28 (10) : 1496 - 1504