Not provided
Not provided
Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| W81XWH-22-1-0956 | Other Grant/Funding Number | Congressionally Directed Medical Research Programs |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
The goal of this observational study is to learn about the impact of historic and current Traumatic Brain Injuries on a Marine Battalion. Its main objectives are:
Participants will wear wear smart watches and analyte sensors to track their real time physiological and sleep measures and complete subjective and psychological measures in a custom research app.
To prevent brain health degradation, it is necessary to understand the factors that contribute to brain insult and injury. The investigators aim to understand and identify pre-exposure risk, reversible and irreversible injury, and the impact of stressors. The investigators will research the real-time interaction between exposure and injury biomarkers and identify how the interaction affects long-term health and measures such as time to recovery.
The project will work with a newly formed Infantry Marine Battalion on Camp Pendleton. This group of Service Members will have many that are beginning their military careers, and thus will bring in only the components of brain health and emotional trauma they have accumulated during their civilian lives to this point.
Participants will be provided with a customized research mobile application that will obtain baseline information related to their military history and experience, and then continuously track activity, physiologic parameters, sleep, cognition and emotional state. Detailed dietary consumption and metabolic data, if indicated, will be tracked and displayed. The data will be collected continuously
During the study, participants will be provided with their data in real-time and this will be displayed along with their schedule and tasks. During and upon completion of the study investigators will provide a detailed summary and analysis of their health and human performance metrics, including insights on how diet and activity impacts their metabolic control or other biomarkers and how all of these factors impact sleep, cognition and behavioral state. The investigators will collaborate with the participants to identify the most useful data displays and information that will best help them achieve optimized physical, mental and cognitive training and recovery and gain understanding of how metabolic control or other biomarkers impact these metrics.
These insights will be used to develop insight dashboards on the holistic health metrics mentioned above, and help provide optimization insights. We will work with participants to create additional app content specific for them that relates to optimal diet and mental and physical training and recovery.
Not provided
Not provided
Not provided
Not provided
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Explanation of Outcomes | In a traditional clinical trial, we would have explicitly included measures, or measurement tool used to assess the measure, along with the measurement units that would be used to assess this outcome measure. However, in this novel prospective digital health trial, these outcomes are not predefined, but are part of discovery within the digital app. Therefore these data will be reported as digital biomarkers that will not necessarily conform with the typical single or multi-variable traditional clinical trial and will include many novel measurement parameters and blended measures. For instance, a novel measurement that will be used to assess the effect of engaging in this clinical trial will be app adherence, which is not a variable generally used in clinical trials. | 18 months |
| Establish individual mental and physical performance profile and brain health baseline in Infantry Marines. | Establish individual mental and physical performance profile and brain health baseline in Infantry Marines from physiological and psychological assessments. Assessments will be scored and recorded to contrast with scores during the study and at its conclusion for individuals as well as the group. Scores will be used to determine correlates and other connections between variables. This will include such connections as the connection between TBI history and current cognitive and psychological assessments, etc. | 1 month |
| Develop predictive models | Develop predictive models to identify early signs of mental and/or physical degradation that can help predict adverse brain health or behavioral events using continuous physiological data and ongoing cognitive and psychological measures. Using assessments on baseline cognitive, physiological and psychological states combined with continuous and periodic assessments of these states, changes in TBI status and cognitive status will be correlated with biomarkers such as sleep, heart rate, O2 measures, glucose measures, and others (as described elsewhere) in order to discover new indications for adverse brain health. | 18 months |
| Increase warfighter self-knowledge and personal awareness |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Healthy service members of the 1st Marine Division 1st Battalion out of Camp Pendleton, CA
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Camp Pendleton | Oceanside | California | 92058 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34346851 | Background | Beckner ME, Main L, Tait JL, Martin BJ, Conkright WR, Nindl BC. Circulating biomarkers associated with performance and resilience during military operational stress. Eur J Sport Sci. 2022 Jan;22(1):72-86. doi: 10.1080/17461391.2021.1962983. Epub 2021 Aug 17. | |
| 29888288 | Background | Bollyky JB, Bravata D, Yang J, Williamson M, Schneider J. Remote Lifestyle Coaching Plus a Connected Glucose Meter with Certified Diabetes Educator Support Improves Glucose and Weight Loss for People with Type 2 Diabetes. J Diabetes Res. 2018 May 16;2018:3961730. doi: 10.1155/2018/3961730. eCollection 2018. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D000070642 | Brain Injuries, Traumatic |
| ID | Term |
|---|---|
| D001930 | Brain Injuries |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
Determine warfighter self-knowledge and personal awareness by developing and measuring self-reported and recorded interaction with personalized educational and interventional portions of the research app. Because we are interested in individuals being invested in their own data in order to make behavioral changes, we will establish baseline assessment scores, and deliver them back to the user with explanations. Participants will also receive continuous biomarker data. This will allow participants to decide if they will make any changes in their behavior or seek help in order to improve their own health outcomes. These will be measured in the same ways as described earlier - changes in sleep patterns, changes in eating habits, changes in drinking habits, etc., as well as level of access by participants of insights and other tools in the research app. |
| 18 months |
| 15788110 | Background | Brynes AE, Adamson J, Dornhorst A, Frost GS. The beneficial effect of a diet with low glycaemic index on 24 h glucose profiles in healthy young people as assessed by continuous glucose monitoring. Br J Nutr. 2005 Feb;93(2):179-82. doi: 10.1079/bjn20041318. |
| 16313250 | Background | Cauza E, Hanusch-Enserer U, Strasser B, Kostner K, Dunky A, Haber P. Strength and endurance training lead to different post exercise glucose profiles in diabetic participants using a continuous subcutaneous glucose monitoring system. Eur J Clin Invest. 2005 Dec;35(12):745-51. doi: 10.1111/j.1365-2362.2005.01573.x. |
| 33006093 | Background | Eslam M, Sarin SK, Wong VW, Fan JG, Kawaguchi T, Ahn SH, Zheng MH, Shiha G, Yilmaz Y, Gani R, Alam S, Dan YY, Kao JH, Hamid S, Cua IH, Chan WK, Payawal D, Tan SS, Tanwandee T, Adams LA, Kumar M, Omata M, George J. The Asian Pacific Association for the Study of the Liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hepatol Int. 2020 Dec;14(6):889-919. doi: 10.1007/s12072-020-10094-2. Epub 2020 Oct 1. |
| 19885137 | Background | Freckmann G, Hagenlocher S, Baumstark A, Jendrike N, Gillen RC, Rossner K, Haug C. Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals. J Diabetes Sci Technol. 2007 Sep;1(5):695-703. doi: 10.1177/193229680700100513. |
| 34108250 | Background | Gambhir SS, Ge TJ, Vermesh O, Spitler R, Gold GE. Continuous health monitoring: An opportunity for precision health. Sci Transl Med. 2021 Jun 9;13(597):eabe5383. doi: 10.1126/scitranslmed.abe5383. |
| 23628170 | Background | Garcia-Compean D, Jaquez-Quintana JO, Gonzalez-Gonzalez JA, Lavalle-Gonzalez FJ, Villarreal-Perez JZ, Maldonado-Garza HJ. [Diabetes in liver cirrhosis]. Gastroenterol Hepatol. 2013 Aug-Sep;36(7):473-82. doi: 10.1016/j.gastrohep.2013.01.012. Epub 2013 Apr 28. Spanish. |
| 27010052 | Background | FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); 2016-. Available from http://www.ncbi.nlm.nih.gov/books/NBK326791/ |
| 30040822 | Background | Hall H, Perelman D, Breschi A, Limcaoco P, Kellogg R, McLaughlin T, Snyder M. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 2018 Jul 24;16(7):e2005143. doi: 10.1371/journal.pbio.2005143. eCollection 2018 Jul. |
| 19880582 | Background | Hamaguchi E, Takamura T, Sakurai M, Mizukoshi E, Zen Y, Takeshita Y, Kurita S, Arai K, Yamashita T, Sasaki M, Nakanuma Y, Kaneko S. Histological course of nonalcoholic fatty liver disease in Japanese patients: tight glycemic control, rather than weight reduction, ameliorates liver fibrosis. Diabetes Care. 2010 Feb;33(2):284-6. doi: 10.2337/dc09-0148. Epub 2009 Oct 30. |
| 26721721 | Background | Hazell TJ, Islam H, Townsend LK, Schmale MS, Copeland JL. Effects of exercise intensity on plasma concentrations of appetite-regulating hormones: Potential mechanisms. Appetite. 2016 Mar 1;98:80-8. doi: 10.1016/j.appet.2015.12.016. Epub 2015 Dec 22. |
| 35271177 | Background | Holzer R, Bloch W, Brinkmann C. Continuous Glucose Monitoring in Healthy Adults-Possible Applications in Health Care, Wellness, and Sports. Sensors (Basel). 2022 Mar 5;22(5):2030. doi: 10.3390/s22052030. |
| 2868515 | Background | Jacobs I. Blood lactate. Implications for training and sports performance. Sports Med. 1986 Jan-Feb;3(1):10-25. doi: 10.2165/00007256-198603010-00003. |
| 18939388 | Background | Kim CH, Younossi ZM. Nonalcoholic fatty liver disease: a manifestation of the metabolic syndrome. Cleve Clin J Med. 2008 Oct;75(10):721-8. doi: 10.3949/ccjm.75.10.721. |
| Background | 15. Karney BR, Crown JS. Families Under Stress: An Assessment of Data, Theory, and Research on ... - Benjamin R. Karney, John S. Crown - Google Books.; 2007. |
| 14964502 | Background | Knapik JJ, Reynolds KL, Harman E. Soldier load carriage: historical, physiological, biomechanical, and medical aspects. Mil Med. 2004 Jan;169(1):45-56. doi: 10.7205/milmed.169.1.45. |
| 31260026 | Background | Koutoukidis DA, Astbury NM, Tudor KE, Morris E, Henry JA, Noreik M, Jebb SA, Aveyard P. Association of Weight Loss Interventions With Changes in Biomarkers of Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis. JAMA Intern Med. 2019 Sep 1;179(9):1262-1271. doi: 10.1001/jamainternmed.2019.2248. |
| Background | Kulawiec, D.G., Zhou, T., Knopp, J.L. and Chase, J.G., 2021. Continuous glucose monitoring to measure metabolic impact and recovery in sub-elite endurance athletes. Biomedical Signal Processing and Control, 70, p.103059. |
| 30877806 | Background | LaFountain RA, Miller VJ, Barnhart EC, Hyde PN, Crabtree CD, McSwiney FT, Beeler MK, Buga A, Sapper TN, Short JA, Bowling ML, Kraemer WJ, Simonetti OP, Maresh CM, Volek JS. Extended Ketogenic Diet and Physical Training Intervention in Military Personnel. Mil Med. 2019 Oct 1;184(9-10):e538-e547. doi: 10.1093/milmed/usz046. |
| 28737585 | Background | Lee EC, Fragala MS, Kavouras SA, Queen RM, Pryor JL, Casa DJ. Biomarkers in Sports and Exercise: Tracking Health, Performance, and Recovery in Athletes. J Strength Cond Res. 2017 Oct;31(10):2920-2937. doi: 10.1519/JSC.0000000000002122. |
| Background | Leung, M.Y., Chan, Y.S. and Yuen, K.W., 2010. Impacts of stressors and stress on the injury incidents of construction workers in Hong Kong. Journal of Construction Engineering and Management, 136(10), pp.1093-1103. |
| 17614026 | Background | Lippi G, Montagnana M, Salvagno GL, Franchini M, Guidi GC. Glycaemic control in athletes. Int J Sports Med. 2008 Jan;29(1):7-10. doi: 10.1055/s-2007-964898. Epub 2007 Jul 5. |
| 33618024 | Background | Liu J, Ayada I, Zhang X, Wang L, Li Y, Wen T, Ma Z, Bruno MJ, de Knegt RJ, Cao W, Peppelenbosch MP, Ghanbari M, Li Z, Pan Q. Estimating Global Prevalence of Metabolic Dysfunction-Associated Fatty Liver Disease in Overweight or Obese Adults. Clin Gastroenterol Hepatol. 2022 Mar;20(3):e573-e582. doi: 10.1016/j.cgh.2021.02.030. Epub 2021 Feb 20. |
| Background | Mitra-Sarkar, S. and Andreas, M., 2009. Driving behaviors, risk perceptions, and stress: An examination of military personnel during wartime deployment. Transportation research record, 2138(1), pp.42-45. |
| Background | Murray, M., Fitzpatrick, D., and O'Connell, C. (1997). "Fishermen's blues: Factors related to accidents and safety among Newfoundland fishermen." Work Stress, 11(3), 292-297.10.1080/02678379708256842 |
| 20665427 | Background | Nowotny B, Cavka M, Herder C, Loffler H, Poschen U, Joksimovic L, Kempf K, Krug AW, Koenig W, Martin S, Kruse J. Effects of acute psychological stress on glucose metabolism and subclinical inflammation in patients with post-traumatic stress disorder. Horm Metab Res. 2010 Sep;42(10):746-53. doi: 10.1055/s-0030-1261924. Epub 2010 Jul 27. |
| 8038905 | Background | Opstad K. Circadian rhythm of hormones is extinguished during prolonged physical stress, sleep and energy deficiency in young men. Eur J Endocrinol. 1994 Jul;131(1):56-66. doi: 10.1530/eje.0.1310056. |
| 24219323 | Background | Russell WR, Baka A, Bjorck I, Delzenne N, Gao D, Griffiths HR, Hadjilucas E, Juvonen K, Lahtinen S, Lansink M, Loon LV, Mykkanen H, Ostman E, Riccardi G, Vinoy S, Weickert MO. Impact of Diet Composition on Blood Glucose Regulation. Crit Rev Food Sci Nutr. 2016;56(4):541-90. doi: 10.1080/10408398.2013.792772. |
| 28344895 | Background | Saeb S, Lattie EG, Schueller SM, Kording KP, Mohr DC. The relationship between mobile phone location sensor data and depressive symptom severity. PeerJ. 2016 Sep 29;4:e2537. doi: 10.7717/peerj.2537. eCollection 2016. |
| Background | Sevil, M., Rashid, M., Hajizadeh, I., Maloney, Z., Samadi, S., Askari, M.R., Brandt, R., Hobbs, N., Park, M., Quinn, L. and Cinar, A., 2019, May. Assessing the effects of stress response on glucose variations. In 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (pp. 1-4). IEEE. |
| 26506195 | Background | Szivak TK, Kraemer WJ. Physiological Readiness and Resilience: Pillars of Military Preparedness. J Strength Cond Res. 2015 Nov;29 Suppl 11:S34-9. doi: 10.1519/JSC.0000000000001073. |
| Background | Tison GH, Kaiyu Hsu, Johnson T. Hsieh, et al. Abstract 21029: Achieving High Retention in Mobile Health Research Using Design Principles Adopted from Widely Popular Consumer Mobile Apps | Circulation. Circulation. 2018;136(No. suppl_1). https://www.ahajournals.org/doi/10.1161/circ.136.suppl_1.21029. Accessed May 1, 2020 |
| 23422934 | Background | Wu G, Feder A, Cohen H, Kim JJ, Calderon S, Charney DS, Mathe AA. Understanding resilience. Front Behav Neurosci. 2013 Feb 15;7:10. doi: 10.3389/fnbeh.2013.00010. eCollection 2013. |
| D006259 |
| Craniocerebral Trauma |
| D020196 | Trauma, Nervous System |
| D014947 | Wounds and Injuries |