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Gabbe BJ, Keeves J, McKimmie A, Gadowski AM, Holland AJ, Semple BD, Young JT, Crowe L, Ownsworth T, Bagg MK, Antonic-Baker A, Hicks AJ, Hill R, Curtis K, Romero L, Ponsford JL, Lannin NA, O'Brien TJ, Cameron PA, Cooper DJ, Rushworth N, Fitzgerald M. The Australian Traumatic Brain Injury Initiative: Systematic Review and Consensus Process to Determine the Predictive Value of Demographic, Injury Event, and Social Characteristics on Outcomes for People With Moderate-Severe Traumatic Brain Injury. J Neurotrauma 2024. [PMID: 38115598 DOI: 10.1089/neu.2023.0461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023] Open
Abstract
The objective of the Australian Traumatic Brain Injury (AUS-TBI) Initiative is to develop a data dictionary to inform data collection and facilitate prediction of outcomes of people who experience moderate-severe TBI in Australia. The aim of this systematic review was to summarize the evidence of the association between demographic, injury event, and social characteristics with outcomes, in people with moderate-severe TBI, to identify potentially predictive indicators. Standardized searches were implemented across bibliographic databases to March 31, 2022. English-language reports, excluding case series, which evaluated the association between demographic, injury event, and social characteristics, and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Abstracts and full text records were independently screened by at least two reviewers in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association. The review findings were discussed with an expert panel to determine the feasibility of incorporation of routine measurement into standard care. The search strategy retrieved 16,685 records; 867 full-length records were screened, and 111 studies included. Twenty-two predictors of 32 different outcomes were identified; 7 were classified as high-level (age, sex, ethnicity, employment, insurance, education, and living situation at the time of injury). After discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous predictors capable of enabling early identification of those at risk for poor outcomes and improved personalization of care through inclusion in routine data collection.
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Affiliation(s)
- Belinda J Gabbe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Health Data Research UK, Swansea University Medical School, Swansea University, Singleton Park, United Kingdom
| | - Jemma Keeves
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
| | - Ancelin McKimmie
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Adelle M Gadowski
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Andrew J Holland
- The Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health, University of Sydney School of Medicine, Westmead, Australia
| | - Bridgette D Semple
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Jesse T Young
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
- Clinical Sciences Murdoch Children's Research Institute, Parkville, VIC, Australia
- School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
- Justice Health Group, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Louise Crowe
- Clinical Sciences Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Tamara Ownsworth
- School of Applied Psychology and the Hopkins Centre, Griffith University, Brisbane, Australia
| | - Matthew K Bagg
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia
- School of Health Sciences, University of Notre Dame Australia, Fremantle, WA, Australia
| | - Ana Antonic-Baker
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Amelia J Hicks
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, VIC, Australia
- School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Regina Hill
- Regina Hill Effective Consulting Pty. Ltd., Melbourne, VIC, Australia
| | - Kate Curtis
- Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
- Illawarra Shoalhaven LHD, Wollongong, NSW, Australia
- George Institute for Global Health, Newtown, NSW, Australia
| | | | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, VIC, Australia
- School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Natasha A Lannin
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
- Alfred Health, Melbourne, VIC, Australia
| | - Terence J O'Brien
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Peter A Cameron
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- National Trauma Research Institute, Melbourne, VIC, Australia
- Emergency and Trauma Centre, The Alfred Hospital, Melbourne, VIC, Australia
| | - D Jamie Cooper
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Australian and New Zealand Intensive Care Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care and Hyperbaric Medicine, The Alfred, Melbourne, VIC, Australia
| | | | - Melinda Fitzgerald
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Bentley, WA, Australia
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Luo W, Yang Z, Zhang W, Zhou D, Guo X, Wang S, He F, Wang Y. Quantitative Proteomics Reveals the Dynamic Pathophysiology Across Different Stages in a Rat Model of Severe Traumatic Brain Injury. Front Mol Neurosci 2022; 14:785938. [PMID: 35145378 PMCID: PMC8821658 DOI: 10.3389/fnmol.2021.785938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/30/2021] [Indexed: 11/30/2022] Open
Abstract
Background Severe traumatic brain injury (TBI) has become a global health problem and causes a vast worldwide societal burden. However, distinct mechanisms between acute and subacute stages have not been systemically revealed. The present study aimed to identify differentially expressed proteins in severe TBI from the acute to subacute phase. Methods Sixty Sprague Dawley (SD) rats were randomly divided into sham surgery and model groups. The severe TBI models were induced by the controlled cortical impact (CCI) method. We evaluated the neurological deficits through the modified neurological severity score (NSS). Meanwhile, H&E staining and immunofluorescence were performed to assess the injured brain tissues. The protein expressions of the hippocampus on the wounded side of CCI groups and the same side of Sham groups were analyzed by the tandem mass tag-based (TMT) quantitative proteomics on the third and fourteenth days. Then, using the gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and protein–protein interaction (PPI), the shared and stage-specific differentially expressed proteins (DEPs) were screened, analyzed, and visualized. Eventually, target proteins were further verified by Western blotting (WB). Results In the severe TBI, the neurological deficits always exist from the acute stage to the subacute stage, and brain parenchyma was dramatically impaired in either period. Of the significant DEPs identified, 312 were unique to the acute phase, 76 were specific to the subacute phase, and 63 were shared in both. Of the 375 DEPs between Sham-a and CCI-a, 240 and 135 proteins were up-regulated and down-regulated, respectively. Of 139 DEPs, 84 proteins were upregulated, and 55 were downregulated in the Sham-s and CCI-s. Bioinformatics analysis revealed that the differential pathophysiology across both stages. One of the most critical shared pathways is the complement and coagulation cascades. Notably, three pathways associated with gastric acid secretion, insulin secretion, and thyroid hormone synthesis were only enriched in the acute phase. Amyotrophic lateral sclerosis (ALS) was significantly enriched in the subacute stage. WB experiments confirmed the reliability of the TMT quantitative proteomics results. Conclusion Our findings highlight the same and different pathological processes in the acute and subacute phases of severe TBI at the proteomic level. The results of potential protein biomarkers might facilitate the design of novel strategies to treat TBI.
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Affiliation(s)
- Weikang Luo
- Department of Integrated Chinese and Western Medicine, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Zhaoyu Yang
- Department of Integrated Chinese and Western Medicine, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Wei Zhang
- The College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, China
| | - Dan Zhou
- Periodical Office, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaohang Guo
- Medical School, Hunan University of Chinese Medicine, Changsha, China
| | - Shunshun Wang
- Postpartum Health Care Department, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, China
| | - Feng He
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Yang Wang
- Department of Integrated Chinese and Western Medicine, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Yang Wang,
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