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Iyanna N, Donohue JK, Lorence JM, Guyette FX, Gimbel E, Brown JB, Daley BJ, Eastridge BJ, Miller RS, Nirula R, Harbrecht BG, Claridge JA, Phelan HA, Vercruysse GA, O'Keefe T, Joseph B, Shutter LA, Sperry JL. Early Glasgow Coma Scale Score and Prediction of Traumatic Brain Injury: A Secondary Analysis of Three Harmonized Prehospital Randomized Clinical Trials. PREHOSP EMERG CARE 2024:1-9. [PMID: 39042825 DOI: 10.1080/10903127.2024.2381048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/11/2024] [Accepted: 07/03/2024] [Indexed: 07/25/2024]
Abstract
OBJECTIVES The prehospital prediction of the radiographic diagnosis of traumatic brain injury (TBI) in hemorrhagic shock patients has the potential to promote early therapeutic interventions. However, the identification of TBI is often challenging and prehospital tools remain limited. While the Glasgow Coma Scale (GCS) score is frequently used to assess the extent of impaired consciousness after injury, the utility of the GCS scores in the early prehospital phase of care to predict TBI in patients with severe injury and concomitant shock is poorly understood. METHODS We performed a post-hoc, secondary analysis utilizing data derived from three randomized prehospital clinical trials: the Prehospital Air Medical Plasma trial (PAMPER), the Study of Tranexamic Acid During Air Medical and Ground Prehospital Transport trial (STAAMP), and the Pragmatic Prehospital Type O Whole Blood Early Resuscitation (PPOWER) trial. Patients were dichotomized into two cohorts based on the presence of TBI and then further stratified into three groups based on prehospital GCS score: GCS 3, GCS 4-12, and GCS 13-15. The association between prehospital GCS score and clinical documentation of TBI was assessed. RESULTS A total of 1,490 enrolled patients were included in this analysis. The percentage of patients with documented TBI in those with a GCS 3 was 59.5, 42.4% in those with a GCS 4-12, and 11.8% in those with a GCS 13-15. The positive predictive value (PPV) of the prehospital GCS score for the diagnosis of TBI is low, with a GCS of 3 having only a 60% PPV. Hypotension and prehospital intubation are independent predictors of a low prehospital GCS. Decreasing prehospital GCS is strongly associated with higher incidence or mortality over time, irrespective of the diagnosis of TBI. CONCLUSIONS The ability to accurately predict the presence of TBI in the prehospital phase of care is essential. The utility of the GCS scores in the early prehospital phase of care to predict TBI in patients with severe injury and concomitant shock is limited. The use of novel scoring systems and improved technology are needed to promote the accurate early diagnosis of TBI.
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Affiliation(s)
- Nidhi Iyanna
- Department of Surgery, Division of Trauma and General Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jack K Donohue
- Department of Surgery, Division of Trauma and General Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - John M Lorence
- Department of Surgery, Division of Trauma and General Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Francis X Guyette
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Elizabeth Gimbel
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joshua B Brown
- Department of Surgery, Division of Trauma and General Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Brian J Daley
- Department of Surgery, University of Tennessee Health Science Center, Knoxville, Tennessee
| | - Brian J Eastridge
- Department of Surgery, University of Texas Health San Antonio, San Antonio, Texas
| | | | - Raminder Nirula
- Department of Surgery, University of Utah, Salt Lake City, Utah
| | - Brian G Harbrecht
- Department of Surgery, University of Louisville, Louisville, Kentucky
| | - Jeffrey A Claridge
- Department of Surgery, Metro Health Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - Herb A Phelan
- Department of Surgery, University of Texas Southwestern, Dallas, Texas
| | | | - Terence O'Keefe
- Department of Surgery, University of Arizona, Tucson, Arizona
| | - Bellal Joseph
- Department of Surgery, University of Arizona, Tucson, Arizona
| | - Lori A Shutter
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jason L Sperry
- Department of Surgery, Division of Trauma and General Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania
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Bagg MK, Hellewell SC, Keeves J, Antonic-Baker A, McKimmie A, Hicks AJ, Gadowski A, Newcombe VFJ, Barlow KM, Balogh ZJ, Ross JP, Law M, Caeyenberghs K, Parizel PM, Thorne J, Papini M, Gill G, Jefferson A, Ponsford JL, Lannin NA, O'Brien TJ, Cameron PA, Cooper DJ, Rushworth N, Gabbe BJ, Fitzgerald M. The Australian Traumatic Brain Injury Initiative: Systematic Review of Predictive Value of Biological Markers for People With Moderate-Severe Traumatic Brain Injury. J Neurotrauma 2024. [PMID: 38115587 DOI: 10.1089/neu.2023.0464] [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 Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to co-design a data resource to predict outcomes for people with moderate-severe traumatic brain injury (TBI) across Australia. Fundamental to this resource is the data dictionary, which is an ontology of data items. Here, we report the systematic review and consensus process for inclusion of biological markers in the data dictionary. Standardized database searches were implemented from inception through April 2022. English-language studies evaluating association between a fluid, tissue, or imaging marker and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Records were screened using a prioritization algorithm and saturation threshold in Research Screener. Full-length records were then screened in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association, and high-value predictors were discussed in a consensus process. Searches retrieved 106,593 records; 1,417 full-length records were screened, resulting in 546 included records. Two hundred thirty-nine individual markers were extracted, evaluated against 101 outcomes. Forty-one markers were judged to be high-value predictors of 15 outcomes. Fluid markers retained following the consensus process included ubiquitin C-terminal hydrolase L1 (UCH-L1), S100, and glial fibrillary acidic protein (GFAP). Imaging markers included computed tomography (CT) scores (e.g., Marshall scores), pathological observations (e.g., hemorrhage, midline shift), and magnetic resonance imaging (MRI) classification (e.g., diffuse axonal injury). Clinical context and time of sampling of potential predictive indicators are important considerations for utility. This systematic review and consensus process has identified fluid and imaging biomarkers with high predictive value of clinical and long-term outcomes following moderate-severe TBI.
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Affiliation(s)
- Matthew K Bagg
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia
- School of Health Sciences, University of Notre Dame Australia, Fremantle, WA, Australia
| | - Sarah C Hellewell
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- School of Medicine, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
| | - Jemma Keeves
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Ana Antonic-Baker
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Ancelin McKimmie
- School of Public Health and Preventive 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
| | - Adelle Gadowski
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Virginia F J Newcombe
- PACE Section, Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Karen M Barlow
- Acquired Brain Injury in Children Research Program, Queensland Children's Hospital, Brisbane, QLD, Australia
- Centre for Children's Health Research, University of Queensland, Brisbane, QLD, Australia
| | - Zsolt J Balogh
- Department of Traumatology, John Hunter Hospital and University of Newcastle, Newcastle, NSW, Australia
| | - Jason P Ross
- Molecular Diagnostic Solutions, Health and Biosecurity, CSIRO, Australia
| | - Meng Law
- Alzheimer's Disease Research Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Neuroscience and Radiology, Monash University, Alfred Health, Melbourne, VIC, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Paul M Parizel
- University of Antwerp, Edegem, Belgium
- Department of Radiology, Royal Perth Hospital and University of Western Australia, Perth, WA, Australia
- West Australian National Imaging Facility Node, Nedlands, WA, Australia
| | - Jacinta Thorne
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Melissa Papini
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Geena Gill
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Amanda Jefferson
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, 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, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Alfred Health, Melbourne, VIC, Australia
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, 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
- 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
| | | | - 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
| | - Melinda Fitzgerald
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
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Chattopadhyay I, Ramamoorthy L, Kumari M, Harichandrakumar K, Lalthanthuami H, Subramaniyan R. Comparison of the Prognostic Accuracy of Full Outline of Unresponsiveness (FOUR) Score with Glasgow Coma Scale (GCS) Score among Patients with Traumatic Brain Injury in a Tertiary Care Center. Asian J Neurosurg 2024; 19:1-7. [PMID: 38751395 PMCID: PMC11093641 DOI: 10.1055/s-0044-1779515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024] Open
Abstract
Objectives The Glasgow Coma Scale (GCS) is widely used and considered the gold standard in assessing the consciousness of patients with traumatic brain injury. However, some significant limitations, like the considerable variations in interobserver reliability and predictive validity, were the reason for developing the Full Outline of Unresponsiveness (FOUR) score. The current study aims to compare the prognostic accuracy of the FOUR score with the GCS score for in-hospital mortality and morbidity among patients with traumatic brain injury. Materials and Methods A prospective cohort study was conducted, where 237 participants were selected by consecutive sampling from a tertiary care center. These patients were assessed with the help of GCS and FOUR scores within 6 hours of admission, and other clinical parameters were also noted. The level of consciousness was checked every day with the help of GCS and FOUR scores until their last hospitalization day. Glasgow Outcome Scale was used to assess their outcome on the last day of hospitalization. The GCS and FOUR scores were compared, and data were analyzed by descriptive and inferential statistics. The chi-square test, independent Student's t -test, and receiver operating characteristic analysis were used for inferential analysis. Results The area under the curve (AUC) for the GCS score at the 6th hour for predicting mortality was 0.865 with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 64%. The AUC for FOUR scores at the 6th hour for predicting the mortality was 0.893, with a cutoff value of 5.5, and it yields a sensitivity of 87% and a specificity of 73%. Conclusion The current study shows that, as per the AUC of GCS and FOUR scores, their sensitivity was equal, but specificity was higher in the FOUR score. So, the FOUR score has higher accuracy than the GCS score in the prediction of mortality among traumatic brain injury patients.
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Affiliation(s)
- Indrani Chattopadhyay
- Department of Medical Surgical Nursing, College of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - Lakshmi Ramamoorthy
- Department of Medical Surgical Nursing, College of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - Manoranjitha Kumari
- Department of Neurosurgery, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - K.T. Harichandrakumar
- Department of Biostatistics, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - H.T. Lalthanthuami
- Department of Medical Surgical Nursing, College of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
| | - Rani Subramaniyan
- Department of Medical Surgical Nursing, College of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India
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O'Reilly GM, Curtis K, Mitra B, Kim Y, Afroz A, Hunter K, Ryder C, Hendrie DV, Rushworth N, Tee J, D'Angelo S, Solly E, Bhattacharya O, Fitzgerald MC. Hospitalisations and in-hospital deaths following moderate to severe traumatic brain injury in Australia, 2015-20: a registry data analysis for the Australian Traumatic Brain Injury National Data (ATBIND) project. Med J Aust 2023; 219:316-324. [PMID: 37524539 DOI: 10.5694/mja2.52055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/26/2023] [Accepted: 06/29/2023] [Indexed: 08/02/2023]
Abstract
OBJECTIVE To describe the frequency of hospitalisation and in-hospital death following moderate to severe traumatic brain injury (TBI) in Australia, both overall and by patient demographic characteristics and the nature and severity of the injury. DESIGN, SETTING Cross-sectional study; analysis of Australia New Zealand Trauma Registry data. PARTICIPANTS People with moderate to severe TBI (Abbreviated Injury Score [head] greater than 2) who were admitted to or died in one of the twenty-three major Australian trauma services that contributed data to the ATR throughout the study period, 1 July 2015 - 30 June 2020. MAJOR OUTCOME MEASURES Primary outcome: number of hospitalisations with moderate to severe TBI; secondary outcome: number of deaths in hospital following moderate to severe TBI. RESULTS During 2015-20, 16 350 people were hospitalised with moderate to severe TBI (mean, 3270 per year), of whom 2437 died in hospital (14.9%; mean, 487 per year). The mean age at admission was 50.5 years (standard deviation [SD], 26.1 years), and 11 644 patients were male (71.2%); the mean age of people who died in hospital was 60.4 years (SD, 25.2 years), and 1686 deaths were of male patients (69.2%). The overall number of hospitalisations did not change during 2015-20 (per year: incidence rate ratio [IRR], 1.00; 95% confidence interval [CI], 0.99-1.02) and death (IRR, 1.00; 95% CI, 0.97-1.03). CONCLUSION Injury prevention and trauma care interventions for people with moderate to severe TBI in Australia reduced neither the incidence of the condition nor the associated in-hospital mortality during 2015-20. More effective care strategies are required to reduce the burden of TBI, particularly among younger men.
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Affiliation(s)
- Gerard M O'Reilly
- Alfred Hospital, Melbourne, VIC
- National Trauma Research Institute, Alfred Hospital, Melbourne, VIC
| | - Kate Curtis
- Sydney Nursing School, University of Sydney, Sydney, NSW
| | | | - Yesul Kim
- National Trauma Research Institute, Alfred Hospital, Melbourne, VIC
- Central Clinical School, Monash University, Melbourne, VIC
| | | | - Kate Hunter
- The George Institute for Global Health, Sydney, NSW
- The University of New South Wales, Sydney, NSW
| | - Courtney Ryder
- College of Medicine and Public Health, Flinders University, Adelaide, SA
| | | | | | - Jin Tee
- National Trauma Research Institute, Alfred Hospital, Melbourne, VIC
| | - Shane D'Angelo
- College of Medicine and Public Health, Flinders University, Adelaide, SA
| | - Emma Solly
- National Trauma Research Institute, Alfred Hospital, Melbourne, VIC
| | | | - Mark C Fitzgerald
- Alfred Hospital, Melbourne, VIC
- National Trauma Research Institute, Alfred Hospital, Melbourne, VIC
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