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Svedung Wettervik T, Beqiri E, Hånell A, Yu Bögli S, Placek M, Donnelly J, Guilfoyle MR, Helmy A, Lavinio A, Hutchinson PJ, Smielewski P. Visualization of Cerebral Pressure Autoregulatory Insults in Traumatic Brain Injury. Crit Care Med 2024:00003246-990000000-00324. [PMID: 38587420 DOI: 10.1097/ccm.0000000000006287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
OBJECTIVES The first aim was to investigate the combined effect of insult intensity and duration of the pressure reactivity index (PRx) and deviation from the autoregulatory cerebral perfusion pressure target (∆CPPopt = actual CPP - optimal CPP [CPPopt]) on outcome in traumatic brain injury. The second aim was to determine if PRx influenced the association between intracranial pressure (ICP), CPP, and ∆CPPopt with outcome. DESIGN Observational cohort study. SETTING Neurocritical care unit, Cambridge, United Kingdom. PATIENTS Five hundred fifty-three traumatic brain injury patients with ICP and arterial blood pressure monitoring and 6-month outcome data (Glasgow Outcome Scale [GOS]). INTERVENTION None. MEASUREMENTS AND MAIN RESULTS The insult intensity (mm Hg or PRx coefficient) and duration (minutes) of ICP, PRx, CPP, and ∆CPPopt were correlated with GOS and visualized in heatmaps. In these plots, there was a transition from favorable to unfavorable outcome when PRx remained positive for 30 minutes and this was also the case for shorter durations when the intensity was higher. In a similar plot of ∆CPPopt, there was a gradual transition from favorable to unfavorable outcome when ∆CPPopt went below -5 mm Hg for 30-minute episodes of time and for shorter durations for more negative ∆CPPopt. Furthermore, the percentage of monitoring time with certain combinations of PRx with ICP, CPP, and ∆CPPopt were correlated with GOS and visualized in heatmaps. In the combined PRx/ICP heatmap, ICP above 20 mm Hg together with PRx above 0 correlated with unfavorable outcome. In a PRx/CPP heatmap, CPP below 70 mm Hg together with PRx above 0.2-0.4 correlated with unfavorable outcome. In the PRx-/∆CPPopt heatmap, ∆CPPopt below 0 together with PRx above 0.2-0.4 correlated with unfavorable outcome. CONCLUSIONS Higher intensities for longer durations of positive PRx and negative ∆CPPopt correlated with worse outcome. Elevated ICP, low CPP, and negative ∆CPPopt were particularly associated with worse outcomes when the cerebral pressure autoregulation was concurrently impaired.
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Affiliation(s)
- Teodor Svedung Wettervik
- Department of Medical Sciences, Section of Neurosurgery, Uppsala University, Uppsala, Sweden
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Erta Beqiri
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Anders Hånell
- Department of Medical Sciences, Section of Neurosurgery, Uppsala University, Uppsala, Sweden
| | - Stefan Yu Bögli
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Michal Placek
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Joseph Donnelly
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
- Department of Neurology, Auckland City Hospital, Auckland, New Zealand
| | - Mathew R Guilfoyle
- Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Adel Helmy
- Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Andrea Lavinio
- Division of Anaesthesia, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Peter J Hutchinson
- Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Peter Smielewski
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
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Stein KY, Froese L, Sekhon M, Griesdale D, Thelin EP, Raj R, Tas J, Aries M, Gallagher C, Bernard F, Gomez A, Kramer AH, Zeiler FA. Intracranial Pressure-Derived Cerebrovascular Reactivity Indices and Their Critical Thresholds: A Canadian High Resolution-Traumatic Brain Injury Validation Study. J Neurotrauma 2024; 41:910-923. [PMID: 37861325 DOI: 10.1089/neu.2023.0374] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023] Open
Abstract
Current neurointensive care guidelines recommend intracranial pressure (ICP) and cerebral perfusion pressure (CPP) centered management for moderate-severe traumatic brain injury (TBI) because of their demonstrated associations with patient outcome. Cerebrovascular reactivity metrics, such as the pressure reactivity index (PRx), pulse amplitude index (PAx), and RAC index, have also demonstrated significant prognostic capabilities with regard to outcome. However, critical thresholds for cerebrovascular reactivity indices have only been identified in two studies conducted at the same center. In this study, we aim to determine the critical thresholds of these metrics by leveraging a unique multi-center database. The study included a total of 354 patients from the CAnadian High-Resolution TBI (CAHR-TBI) Research Collaborative. Based on 6-month Glasgow Outcome Scores, patients were dichotomized into alive versus dead and favorable versus unfavorable. Chi-square values were then computed for incrementally increasing values of each physiological parameter of interest against outcome. The values that generated the greatest chi-squares for each parameter were considered to be the thresholds with the greatest outcome discriminatory capacity. To confirm that the identified thresholds provide prognostic utility, univariate and multivariable logistical regression analyses were performed adjusting for the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) variables. Through the chi-square analysis, a lower limit CPP threshold of 60 mm Hg and ICP thresholds of 18 mm Hg and 22 mm Hg were identified for both survival and favorable outcome predictions. For the cerebrovascular reactivity metrics, different thresholds were identified for the two outcome dichotomizations. For survival prediction, thresholds of 0.35, 0.25, and 0 were identified for PRx, PAx, and RAC, respectively. For favorable outcome prediction, thresholds of 0.325, 0.20, and 0.05 were found. Univariate logistical regression analysis demonstrated that the time spent above/below thresholds were associated with outcome. Further, multivariable logistical regression analysis found that percent time above/below the identified thresholds added additional variance to the IMPACT core model for predicting both survival and favorable outcome. In this study, we were able to validate the results of the previous two works as well as to reaffirm the ICP and CPP guidelines from the Brain Trauma Foundation (BTF) and the Seattle International Severe Traumatic Brain Injury Consensus Conference (SIBICC).
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Affiliation(s)
- Kevin Y Stein
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Mypinder Sekhon
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donald Griesdale
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Eric P Thelin
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Rahul Raj
- Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jeanette Tas
- Department of Intensive Care, Maastricht University Medical Center+, and School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Marcel Aries
- Department of Intensive Care, Maastricht University Medical Center+, and School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Clare Gallagher
- Section of Neurosurgery, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Francis Bernard
- Section of Critical Care, Department of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Alwyn Gomez
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Manitoba, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Andreas H Kramer
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Critical Care Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Frederick A Zeiler
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Manitoba, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Centre on Aging, University of Manitoba, Winnipeg, Manitoba, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
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Ponsford JL, Carty M, Olver J, Ponsford M, Acher R, McKenzie D, Downing MG. Considering the Importance of Personal and Injury Factors Influencing Outcome After Traumatic Brain Injury. Arch Phys Med Rehabil 2024:S0003-9993(24)00884-0. [PMID: 38493908 DOI: 10.1016/j.apmr.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/25/2024] [Accepted: 03/04/2024] [Indexed: 03/19/2024]
Abstract
OBJECTIVE Given the high variability in traumatic brain injury (TBI) outcomes and relative lack of examination of the influence of noninjury factors on outcome, this study aimed to examine factors associated with functional outcome at 1 and 2 years after moderate to severe TBI, including both preinjury and injury-related factors. DESIGN Observational cohort study. SETTING Inpatient hospital recruitment with outpatient follow-up at 1 and 2 years post injury. PARTICIPANTS Individuals with moderate to severe TBI were recruited prospectively into a Longitudinal Head Injury Outcome Study. Of the eligible 3253 individuals who were eligible, 1899 participants consented to the study (N=1899). MAIN OUTCOME MEASURE Functional outcome was measured using the Glasgow Outcome Scale-Extended (GOS-E). RESULTS 1476 participants (73.6% males) and 1365 participants (73% males) completed the GOS-E at 1 and 2 years post injury. They had a mean age at injury of 40 years and mean duration of post-traumatic amnesia (PTA) of 26 days. Good recovery, representing return to previous activities on the GOS-E (score 7-8), was present in 31% of participants at 1 year post injury and 33.5% at 2 years post injury. When predictor variables were entered into regression together, good outcome was significantly associated with not being from a culturally and linguistically diverse background and not having preinjury mental health or alcohol treatment, shorter PTA duration, and absence of limb injuries at both 1 and 2 years; higher education was also a significant predictor at 1 year post injury. CONCLUSIONS Alongside consideration of injury severity, understanding and addressing preinjury factors is important to maximize outcomes.
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Affiliation(s)
- Jennie L Ponsford
- Monash Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne; School of Psychological Sciences, Monash University, Melbourne, Australia; Epworth HealthCare, Melbourne.
| | - Meagan Carty
- Monash Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne; Epworth HealthCare, Melbourne
| | - John Olver
- Epworth HealthCare, Melbourne; Faculty of Medicine, Monash University, Melbourne
| | | | | | - Dean McKenzie
- Epworth HealthCare, Melbourne; School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Marina G Downing
- Monash Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne; School of Psychological Sciences, Monash University, Melbourne, Australia
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Gribnau A, van Zuylen ML, Coles JP, Plummer MP, Hermanns H, Hermanides J. Cerebral Glucose Metabolism following TBI: Changes in Plasma Glucose, Glucose Transport and Alternative Pathways of Glycolysis-A Translational Narrative Review. Int J Mol Sci 2024; 25:2513. [PMID: 38473761 DOI: 10.3390/ijms25052513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/05/2024] [Accepted: 02/14/2024] [Indexed: 03/14/2024] Open
Abstract
Traumatic brain injury (TBI) is a major public health concern with significant consequences across various domains. Following the primary event, secondary injuries compound the outcome after TBI, with disrupted glucose metabolism emerging as a relevant factor. This narrative review summarises the existing literature on post-TBI alterations in glucose metabolism. After TBI, the brain undergoes dynamic changes in brain glucose transport, including alterations in glucose transporters and kinetics, and disruptions in the blood-brain barrier (BBB). In addition, cerebral glucose metabolism transitions from a phase of hyperglycolysis to hypometabolism, with upregulation of alternative pathways of glycolysis. Future research should further explore optimal, and possibly personalised, glycaemic control targets in TBI patients, with GLP-1 analogues as promising therapeutic candidates. Furthermore, a more fundamental understanding of alterations in the activation of various pathways, such as the polyol and lactate pathway, could hold the key to improving outcomes following TBI.
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Affiliation(s)
- Annerixt Gribnau
- Department of Anaesthesiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Mark L van Zuylen
- Department of Anaesthesiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
- Department of Paediatric Intensive Care, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Jonathan P Coles
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0QQ, UK
| | - Mark P Plummer
- Intensive Care Unit, Royal Melbourne Hospital, 300 Grattan Street, Parkville, VIC 3050, Australia
| | - Henning Hermanns
- Department of Anaesthesiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Jeroen Hermanides
- Department of Anaesthesiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
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Nelson L, Magnus B, Yue J, Balsis S, Patrick C, Temkin N, Diaz-Arrastia R, Manley G. Data-driven characterization of traumatic brain injury severity from clinical, neuroimaging, and blood-based indicators. RESEARCH SQUARE 2024:rs.3.rs-3954157. [PMID: 38410436 PMCID: PMC10896408 DOI: 10.21203/rs.3.rs-3954157/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
The conventional clinical approach to characterizing traumatic brain injuries (TBIs) as mild, moderate, or severe using the Glasgow Coma Scale (GCS) total score has well-known limitations, prompting calls for more sophisticated strategies to characterize TBI. Here, we use item response theory (IRT) to develop a novel method for quantifying TBI severity that incorporates neuroimaging and blood-based biomarkers along with clinical measures. Within the multicenter Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study sample (N = 2545), we show that a set of 23 clinical, head computed tomography (CT), and blood-based biomarker variables familiar to clinicians and researchers index a common latent continuum of TBI severity. We illustrate how IRT can be used to identify the relative value of these features to estimate an individual's position along the TBI severity continuum. Finally, we show that TBI severity scores generated using this novel IRT-based method incrementally predict functional outcome over classic clinical (mild, moderate, severe) or International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) classification methods. Our findings directly inform ongoing international efforts to refine and deploy new pragmatic, empirically-supported strategies for characterizing TBI, while illustrating a strategy that may be useful to evolve staging systems for other diseases.
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An T, Dong Z, Li X, Ma Y, Jin J, Li L, Xu L. Comparative analysis of CRASH and IMPACT in predicting the outcome of 340 patients with traumatic brain injury. Transl Neurosci 2024; 15:20220327. [PMID: 38529016 PMCID: PMC10961482 DOI: 10.1515/tnsci-2022-0327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/26/2023] [Accepted: 11/29/2023] [Indexed: 03/27/2024] Open
Abstract
Background Both the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) and the Corticosteroid randomization after significant head injury (CRASH) models are globally acknowledged prognostic algorithms for assessing traumatic brain injury (TBI) outcomes. The aim of this study is to externalize the validation process and juxtapose the prognostic accuracy of the CRASH and IMPACT models in moderate-to-severe TBI patients in the Chinese population. Methods We conducted a retrospective study encompassing a cohort of 340 adult TBI patients (aged > 18 years), presenting with Glasgow Coma Scale (GCS) scores ranging from 3 to 12. The data were accrued over 2 years (2020-2022). The primary endpoints were 14-day mortality rates and 6-month Glasgow Outcome Scale (GOS) scores. Analytical metrics, including the area under the receiver operating characteristic curve for discrimination and the Brier score for predictive precision were employed to quantitatively evaluate the model performance. Results Mortality rates at the 14-day and 6-month intervals, as well as the 6-month unfavorable GOS outcomes, were established to be 22.06, 40.29, and 65.59%, respectively. The IMPACT models had area under the curves (AUCs) of 0.873, 0.912, and 0.927 for the 6-month unfavorable GOS outcomes, with respective Brier scores of 0.14, 0.12, and 0.11. On the other hand, the AUCs associated with the six-month mortality were 0.883, 0.909, and 0.912, and the corresponding Brier scores were 0.15, 0.14, and 0.13, respectively. The CRASH models exhibited AUCs of 0.862 and 0.878 for the 6-month adverse outcomes, with uniform Brier scores of 0.18. The 14-day mortality rates had AUCs of 0.867 and 0.87, and corresponding Brier scores of 0.21 and 0.22, respectively. Conclusion Both the CRASH and IMPACT algorithms offer reliable prognostic estimations for patients suffering from craniocerebral injuries. However, compared to the CRASH model, the IMPACT model has superior predictive accuracy, albeit at the cost of increased computational intricacy.
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Affiliation(s)
- Tingting An
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Zibei Dong
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Xiangyang Li
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Yifan Ma
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Jie Jin
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Liqing Li
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Lanjuan Xu
- Department of Critical Care Medicine, Zhengzhou Central Hospital affiliated to Zhengzhou University, Zhengzhou, Henan, 450001, China
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Miranda SP, Morris RS, Rabas M, Creutzfeldt CJ, Cooper Z. Early Shared Decision-Making for Older Adults with Traumatic Brain Injury: Using Time-Limited Trials and Understanding Their Limitations. Neurocrit Care 2023; 39:284-293. [PMID: 37349599 DOI: 10.1007/s12028-023-01764-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 05/11/2023] [Indexed: 06/24/2023]
Abstract
Older adults account for a disproportionate share of the morbidity and mortality after traumatic brain injury (TBI). Predicting functional and cognitive outcomes for individual older adults after TBI is challenging in the acute phase of injury. Given that neurologic recovery is possible and uncertain, life-sustaining therapy may be pursued initially, even if for some, there is a risk of survival to an undesired level of disability or dependence. Experts recommend early conversations about goals of care after TBI, but evidence-based guidelines for these discussions or for the optimal method for communicating prognosis are limited. The time-limited trial (TLT) model may be an effective strategy for managing prognostic uncertainty after TBI. TLTs can provide a framework for early management: specific treatments or procedures are used for a defined period of time while monitoring for an agreed-upon outcome. Outcome measures, including signs of worsening and improvement, are defined at the outset of the trial. In this Viewpoint article, we discuss the use of TLTs for older adults with TBI, their potential benefits, and current challenges to their application. Three main barriers limit the implementation of TLTs in these scenarios: inadequate models for prognostication; cognitive biases faced by clinicians and surrogate decision-makers, which may contribute to prognostic discordance; and ambiguity regarding appropriate endpoints for the TLT. Further study is needed to understand clinician behaviors and surrogate preferences for prognostic communication and how to optimally integrate TLTs into the care of older adults with TBI.
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Affiliation(s)
- Stephen P Miranda
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
- Perelman Center for Advanced Medicine, 15 South Tower, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA.
| | - Rachel S Morris
- Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Mackenzie Rabas
- Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Zara Cooper
- Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
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Stein KY, Froese L, Gomez A, Sainbhi AS, Vakitbilir N, Ibrahim Y, Zeiler FA. Intracranial Pressure Monitoring and Treatment Thresholds in Acute Neural Injury: A Narrative Review of the Historical Achievements, Current State, and Future Perspectives. Neurotrauma Rep 2023; 4:478-494. [PMID: 37636334 PMCID: PMC10457629 DOI: 10.1089/neur.2023.0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023] Open
Abstract
Since its introduction in the 1960s, intracranial pressure (ICP) monitoring has become an indispensable tool in neurocritical care practice and a key component of the management of moderate/severe traumatic brain injury (TBI). The primary utility of ICP monitoring is to guide therapeutic interventions aimed at maintaining physiological ICP and preventing intracranial hypertension. The rationale for such ICP maintenance is to prevent secondary brain injury arising from brain herniation and inadequate cerebral blood flow. There exists a large body of evidence indicating that elevated ICP is associated with mortality and that aggressive ICP control protocols improve outcomes in severe TBI patients. Therefore, current management guidelines recommend a cerebral perfusion pressure (CPP) target range of 60-70 mm Hg and an ICP threshold of >20 or >22 mm Hg, beyond which therapeutic intervention should be initiated. Though our ability to achieve these thresholds has drastically improved over the past decades, there has been little to no change in the mortality and morbidity associated with moderate-severe TBI. This is a result of the "one treatment fits all" dogma of current guideline-based care that fails to take individual phenotype into account. The way forward in moderate-severe TBI care is through the development of continuously derived individualized ICP thresholds. This narrative review covers the topic of ICP monitoring in TBI care, including historical context/achievements, current monitoring technologies and indications, treatment methods, associations with patient outcome and multi-modal cerebral physiology, present controversies surrounding treatment thresholds, and future perspectives on personalized approaches to ICP-directed therapy.
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Affiliation(s)
- Kevin Y. Stein
- Biomedical Engineering, Price Faculty of Engineering, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Logan Froese
- Biomedical Engineering, Price Faculty of Engineering, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Alwyn Gomez
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Amanjyot Singh Sainbhi
- Biomedical Engineering, Price Faculty of Engineering, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Nuray Vakitbilir
- Biomedical Engineering, Price Faculty of Engineering, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Younis Ibrahim
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Frederick A. Zeiler
- Biomedical Engineering, Price Faculty of Engineering, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
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Nelson LD, Temkin NR, Barber J, Brett BL, Okonkwo DO, McCrea MA, Giacino JT, Bodien YG, Robertson C, Corrigan JD, Diaz-Arrastia R, Markowitz AJ, Manley GT. Functional Recovery, Symptoms, and Quality of Life 1 to 5 Years After Traumatic Brain Injury. JAMA Netw Open 2023; 6:e233660. [PMID: 36939699 PMCID: PMC10028488 DOI: 10.1001/jamanetworkopen.2023.3660] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 01/21/2023] [Indexed: 03/21/2023] Open
Abstract
Importance Many level I trauma center patients experience clinical sequelae at 1 year following traumatic brain injury (TBI). Longer-term outcome data are needed to develop better monitoring and rehabilitation services. Objective To examine functional recovery, TBI-related symptoms, and quality of life from 1 to 5 years postinjury. Design, Setting, and Participants This cohort study enrolled trauma patients across 18 US level I trauma centers between 2014 and 2018. Eligible participants were enrolled within 24 hours of injury and followed up to 5 years postinjury. Data were analyzed January 2023. Exposures Mild TBI (mTBI), moderate-severe TBI (msTBI), or orthopedic traumatic controls (OTC). Main Outcomes and Measures Functional independence (Glasgow Outcome Scale-Extended [GOSE] score 5 or higher), complete functional recovery (GOSE score, 8), better (ie, lower) TBI-related symptom burden (Rivermead Post Concussion Symptoms Questionnaire score of 15 or lower), and better (ie, higher) health-related quality of life (Quality of Life After Brain Injury Scale-Overall Scale score 52 or higher); mortality was analyzed as a secondary outcome. Results A total 1196 patients were included in analysis (mean [SD] age, 40.8 [16.9] years; 781 [65%] male; 158 [13%] Black, 965 [81%] White). mTBI and OTC groups demonstrated stable, high rates of functional independence (98% to 100% across time). While odds of independence were lower among msTBI survivors, the majority were independent at 1 year (72%), and this proportion increased over time (80% at 5 years; group × year, P = .005; independence per year: odds ratio [OR] for msTBI, 1.28; 95% CI, 1.03-1.58; OR for mTBI, 0.81; 95% CI, 0.64-1.03). For other outcomes, group differences at 1 year remained stable over time (group × year, P ≥ .44). Odds of complete functional recovery remained lower for persons with mTBI vs OTC (OR, 0.39; 95% CI, 0.28-0.56) and lower for msTBI vs mTBI (OR, 0.34; 95% CI, 0.24-0.48). Odds of better TBI-related symptom burden and quality of life were similar for both TBI subgroups and lower than OTCs. Mortality between 1 and 5 years was higher for msTBI (5.5%) than mTBI (1.5%) and OTC (0.7%; P = .02). Conclusions and Relevance In this cohort study, patients with previous msTBI displayed increased independence over 5 years; msTBI was also associated with increased mortality. These findings, in combination with the persistently elevated rates of unfavorable outcomes in mTBI vs controls imply that more monitoring and rehabilitation are needed for TBI.
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Affiliation(s)
| | | | | | | | - David O. Okonkwo
- University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | | | - Joseph T. Giacino
- Massachusetts General Hospital and Harvard Medical School, Boston
- Spaulding Rehabilitation Hospital, Charlestown, Massachusetts
| | - Yelena G. Bodien
- Massachusetts General Hospital and Harvard Medical School, Boston
- Spaulding Rehabilitation Hospital, Charlestown, Massachusetts
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Mainali S, Park S. Artificial Intelligence and Big Data Science in Neurocritical Care. Crit Care Clin 2023; 39:235-242. [DOI: 10.1016/j.ccc.2022.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Maas AIR, Menon DK, Manley GT, Abrams M, Åkerlund C, Andelic N, Aries M, Bashford T, Bell MJ, Bodien YG, Brett BL, Büki A, Chesnut RM, Citerio G, Clark D, Clasby B, Cooper DJ, Czeiter E, Czosnyka M, Dams-O’Connor K, De Keyser V, Diaz-Arrastia R, Ercole A, van Essen TA, Falvey É, Ferguson AR, Figaji A, Fitzgerald M, Foreman B, Gantner D, Gao G, Giacino J, Gravesteijn B, Guiza F, Gupta D, Gurnell M, Haagsma JA, Hammond FM, Hawryluk G, Hutchinson P, van der Jagt M, Jain S, Jain S, Jiang JY, Kent H, Kolias A, Kompanje EJO, Lecky F, Lingsma HF, Maegele M, Majdan M, Markowitz A, McCrea M, Meyfroidt G, Mikolić A, Mondello S, Mukherjee P, Nelson D, Nelson LD, Newcombe V, Okonkwo D, Orešič M, Peul W, Pisică D, Polinder S, Ponsford J, Puybasset L, Raj R, Robba C, Røe C, Rosand J, Schueler P, Sharp DJ, Smielewski P, Stein MB, von Steinbüchel N, Stewart W, Steyerberg EW, Stocchetti N, Temkin N, Tenovuo O, Theadom A, Thomas I, Espin AT, Turgeon AF, Unterberg A, Van Praag D, van Veen E, Verheyden J, Vyvere TV, Wang KKW, Wiegers EJA, Williams WH, Wilson L, Wisniewski SR, Younsi A, Yue JK, Yuh EL, Zeiler FA, Zeldovich M, Zemek R. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol 2022; 21:1004-1060. [PMID: 36183712 PMCID: PMC10427240 DOI: 10.1016/s1474-4422(22)00309-x] [Citation(s) in RCA: 187] [Impact Index Per Article: 93.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 07/22/2022] [Indexed: 02/06/2023]
Abstract
Traumatic brain injury (TBI) has the highest incidence of all common neurological disorders, and poses a substantial public health burden. TBI is increasingly documented not only as an acute condition but also as a chronic disease with long-term consequences, including an increased risk of late-onset neurodegeneration. The first Lancet Neurology Commission on TBI, published in 2017, called for a concerted effort to tackle the global health problem posed by TBI. Since then, funding agencies have supported research both in high-income countries (HICs) and in low-income and middle-income countries (LMICs). In November 2020, the World Health Assembly, the decision-making body of WHO, passed resolution WHA73.10 for global actions on epilepsy and other neurological disorders, and WHO launched the Decade for Action on Road Safety plan in 2021. New knowledge has been generated by large observational studies, including those conducted under the umbrella of the International Traumatic Brain Injury Research (InTBIR) initiative, established as a collaboration of funding agencies in 2011. InTBIR has also provided a huge stimulus to collaborative research in TBI and has facilitated participation of global partners. The return on investment has been high, but many needs of patients with TBI remain unaddressed. This update to the 2017 Commission presents advances and discusses persisting and new challenges in prevention, clinical care, and research. In LMICs, the occurrence of TBI is driven by road traffic incidents, often involving vulnerable road users such as motorcyclists and pedestrians. In HICs, most TBI is caused by falls, particularly in older people (aged ≥65 years), who often have comorbidities. Risk factors such as frailty and alcohol misuse provide opportunities for targeted prevention actions. Little evidence exists to inform treatment of older patients, who have been commonly excluded from past clinical trials—consequently, appropriate evidence is urgently required. Although increasing age is associated with worse outcomes from TBI, age should not dictate limitations in therapy. However, patients injured by low-energy falls (who are mostly older people) are about 50% less likely to receive critical care or emergency interventions, compared with those injured by high-energy mechanisms, such as road traffic incidents. Mild TBI, defined as a Glasgow Coma sum score of 13–15, comprises most of the TBI cases (over 90%) presenting to hospital. Around 50% of adult patients with mild TBI presenting to hospital do not recover to pre-TBI levels of health by 6 months after their injury. Fewer than 10% of patients discharged after presenting to an emergency department for TBI in Europe currently receive follow-up. Structured follow-up after mild TBI should be considered good practice, and urgent research is needed to identify which patients with mild TBI are at risk for incomplete recovery. The selection of patients for CT is an important triage decision in mild TBI since it allows early identification of lesions that can trigger hospital admission or life-saving surgery. Current decision making for deciding on CT is inefficient, with 90–95% of scanned patients showing no intracranial injury but being subjected to radiation risks. InTBIR studies have shown that measurement of blood-based biomarkers adds value to previously proposed clinical decision rules, holding the potential to improve efficiency while reducing radiation exposure. Increased concentrations of biomarkers in the blood of patients with a normal presentation CT scan suggest structural brain damage, which is seen on MR scanning in up to 30% of patients with mild TBI. Advanced MRI, including diffusion tensor imaging and volumetric analyses, can identify additional injuries not detectable by visual inspection of standard clinical MR images. Thus, the absence of CT abnormalities does not exclude structural damage—an observation relevant to litigation procedures, to management of mild TBI, and when CT scans are insufficient to explain the severity of the clinical condition. Although blood-based protein biomarkers have been shown to have important roles in the evaluation of TBI, most available assays are for research use only. To date, there is only one vendor of such assays with regulatory clearance in Europe and the USA with an indication to rule out the need for CT imaging for patients with suspected TBI. Regulatory clearance is provided for a combination of biomarkers, although evidence is accumulating that a single biomarker can perform as well as a combination. Additional biomarkers and more clinical-use platforms are on the horizon, but cross-platform harmonisation of results is needed. Health-care efficiency would benefit from diversity in providers. In the intensive care setting, automated analysis of blood pressure and intracranial pressure with calculation of derived parameters can help individualise management of TBI. Interest in the identification of subgroups of patients who might benefit more from some specific therapeutic approaches than others represents a welcome shift towards precision medicine. Comparative-effectiveness research to identify best practice has delivered on expectations for providing evidence in support of best practices, both in adult and paediatric patients with TBI. Progress has also been made in improving outcome assessment after TBI. Key instruments have been translated into up to 20 languages and linguistically validated, and are now internationally available for clinical and research use. TBI affects multiple domains of functioning, and outcomes are affected by personal characteristics and life-course events, consistent with a multifactorial bio-psycho-socio-ecological model of TBI, as presented in the US National Academies of Sciences, Engineering, and Medicine (NASEM) 2022 report. Multidimensional assessment is desirable and might be best based on measurement of global functional impairment. More work is required to develop and implement recommendations for multidimensional assessment. Prediction of outcome is relevant to patients and their families, and can facilitate the benchmarking of quality of care. InTBIR studies have identified new building blocks (eg, blood biomarkers and quantitative CT analysis) to refine existing prognostic models. Further improvement in prognostication could come from MRI, genetics, and the integration of dynamic changes in patient status after presentation. Neurotrauma researchers traditionally seek translation of their research findings through publications, clinical guidelines, and industry collaborations. However, to effectively impact clinical care and outcome, interactions are also needed with research funders, regulators, and policy makers, and partnership with patient organisations. Such interactions are increasingly taking place, with exemplars including interactions with the All Party Parliamentary Group on Acquired Brain Injury in the UK, the production of the NASEM report in the USA, and interactions with the US Food and Drug Administration. More interactions should be encouraged, and future discussions with regulators should include debates around consent from patients with acute mental incapacity and data sharing. Data sharing is strongly advocated by funding agencies. From January 2023, the US National Institutes of Health will require upload of research data into public repositories, but the EU requires data controllers to safeguard data security and privacy regulation. The tension between open data-sharing and adherence to privacy regulation could be resolved by cross-dataset analyses on federated platforms, with the data remaining at their original safe location. Tools already exist for conventional statistical analyses on federated platforms, however federated machine learning requires further development. Support for further development of federated platforms, and neuroinformatics more generally, should be a priority. This update to the 2017 Commission presents new insights and challenges across a range of topics around TBI: epidemiology and prevention (section 1 ); system of care (section 2 ); clinical management (section 3 ); characterisation of TBI (section 4 ); outcome assessment (section 5 ); prognosis (Section 6 ); and new directions for acquiring and implementing evidence (section 7 ). Table 1 summarises key messages from this Commission and proposes recommendations for the way forward to advance research and clinical management of TBI.
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Affiliation(s)
- Andrew I R Maas
- Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Geoffrey T Manley
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Mathew Abrams
- International Neuroinformatics Coordinating Facility, Karolinska Institutet, Stockholm, Sweden
| | - Cecilia Åkerlund
- Department of Physiology and Pharmacology, Section of Perioperative Medicine and Intensive Care, Karolinska Institutet, Stockholm, Sweden
| | - Nada Andelic
- Division of Clinical Neuroscience, Department of Physical Medicine and Rehabilitation, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Marcel Aries
- Department of Intensive Care, Maastricht UMC, Maastricht, Netherlands
| | - Tom Bashford
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Michael J Bell
- Critical Care Medicine, Neurological Surgery and Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Yelena G Bodien
- Department of Neurology and Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA
| | - Benjamin L Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - András Büki
- Department of Neurosurgery, Faculty of Medicine and Health Örebro University, Örebro, Sweden
- Department of Neurosurgery, Medical School; ELKH-PTE Clinical Neuroscience MR Research Group; and Neurotrauma Research Group, Janos Szentagothai Research Centre, University of Pecs, Pecs, Hungary
| | - Randall M Chesnut
- Department of Neurological Surgery and Department of Orthopaedics and Sports Medicine, University of Washington, Harborview Medical Center, Seattle, WA, USA
| | - Giuseppe Citerio
- School of Medicine and Surgery, Universita Milano Bicocca, Milan, Italy
- NeuroIntensive Care, San Gerardo Hospital, Azienda Socio Sanitaria Territoriale (ASST) Monza, Monza, Italy
| | - David Clark
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Betony Clasby
- Department of Sociological Studies, University of Sheffield, Sheffield, UK
| | - D Jamie Cooper
- School of Public Health and Preventive Medicine, Monash University and The Alfred Hospital, Melbourne, VIC, Australia
| | - Endre Czeiter
- Department of Neurosurgery, Medical School; ELKH-PTE Clinical Neuroscience MR Research Group; and Neurotrauma Research Group, Janos Szentagothai Research Centre, University of Pecs, Pecs, Hungary
| | - Marek Czosnyka
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance and Department of Neurology, Brain Injury Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Véronique De Keyser
- Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - Ramon Diaz-Arrastia
- Department of Neurology and Center for Brain Injury and Repair, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ari Ercole
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Thomas A van Essen
- Department of Neurosurgery, Leiden University Medical Center, Leiden, Netherlands
- Department of Neurosurgery, Medical Center Haaglanden, The Hague, Netherlands
| | - Éanna Falvey
- College of Medicine and Health, University College Cork, Cork, Ireland
| | - Adam R Ferguson
- Brain and Spinal Injury Center, Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco and San Francisco Veterans Affairs Healthcare System, San Francisco, CA, USA
| | - Anthony Figaji
- Division of Neurosurgery and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Melinda Fitzgerald
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Perron Institute for Neurological and Translational Sciences, Nedlands, WA, Australia
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati Gardner Neuroscience Institute, University of Cincinnati, Cincinnati, OH, USA
| | - Dashiell Gantner
- School of Public Health and Preventive Medicine, Monash University and The Alfred Hospital, Melbourne, VIC, Australia
| | - Guoyi Gao
- Department of Neurosurgery, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine
| | - Joseph Giacino
- Department of Physical Medicine and Rehabilitation, Harvard Medical School and Spaulding Rehabilitation Hospital, Charlestown, MA, USA
| | - Benjamin Gravesteijn
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Fabian Guiza
- Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Deepak Gupta
- Department of Neurosurgery, Neurosciences Centre and JPN Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi, India
| | - Mark Gurnell
- Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Flora M Hammond
- Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, Rehabilitation Hospital of Indiana, Indianapolis, IN, USA
| | - Gregory Hawryluk
- Section of Neurosurgery, GB1, Health Sciences Centre, University of Manitoba, Winnipeg, MB, Canada
| | - Peter Hutchinson
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Mathieu van der Jagt
- Department of Intensive Care, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Sonia Jain
- Biostatistics Research Center, Herbert Wertheim School of Public Health, University of California, San Diego, CA, USA
| | - Swati Jain
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Ji-yao Jiang
- Department of Neurosurgery, Shanghai Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hope Kent
- Department of Psychology, University of Exeter, Exeter, UK
| | - Angelos Kolias
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Erwin J O Kompanje
- Department of Intensive Care, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Fiona Lecky
- Centre for Urgent and Emergency Care Research, Health Services Research Section, School of Health and Related Research, University of Sheffield, Sheffield, UK
| | - Hester F Lingsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marc Maegele
- Cologne-Merheim Medical Center, Department of Trauma and Orthopedic Surgery, Witten/Herdecke University, Cologne, Germany
| | - Marek Majdan
- Institute for Global Health and Epidemiology, Department of Public Health, Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia
| | - Amy Markowitz
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Michael McCrea
- Department of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Geert Meyfroidt
- Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Leuven, Belgium
| | - Ana Mikolić
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Stefania Mondello
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - David Nelson
- Section for Anesthesiology and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Lindsay D Nelson
- Department of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Virginia Newcombe
- Division of Anaesthesia, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - David Okonkwo
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matej Orešič
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Wilco Peul
- Department of Neurosurgery, Leiden University Medical Center, Leiden, Netherlands
| | - Dana Pisică
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Suzanne Polinder
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jennie Ponsford
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Louis Puybasset
- Department of Anesthesiology and Intensive Care, APHP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
| | - Rahul Raj
- Department of Neurosurgery, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Chiara Robba
- Department of Anaesthesia and Intensive Care, Policlinico San Martino IRCCS for Oncology and Neuroscience, Genova, Italy, and Dipartimento di Scienze Chirurgiche e Diagnostiche, University of Genoa, Italy
| | - Cecilie Røe
- Division of Clinical Neuroscience, Department of Physical Medicine and Rehabilitation, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - David J Sharp
- Department of Brain Sciences, Imperial College London, London, UK
| | - Peter Smielewski
- Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Murray B Stein
- Department of Psychiatry and Department of Family Medicine and Public Health, UCSD School of Medicine, La Jolla, CA, USA
| | - Nicole von Steinbüchel
- Institute of Medical Psychology and Medical Sociology, University Medical Center Goettingen, Goettingen, Germany
| | - William Stewart
- Department of Neuropathology, Queen Elizabeth University Hospital and University of Glasgow, Glasgow, UK
| | - Ewout W Steyerberg
- Department of Biomedical Data Sciences Leiden University Medical Center, Leiden, Netherlands
| | - Nino Stocchetti
- Department of Pathophysiology and Transplantation, Milan University, and Neuroscience ICU, Fondazione IRCCS Ca Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Nancy Temkin
- Departments of Neurological Surgery, and Biostatistics, University of Washington, Seattle, WA, USA
| | - Olli Tenovuo
- Department of Rehabilitation and Brain Trauma, Turku University Hospital, and Department of Neurology, University of Turku, Turku, Finland
| | - Alice Theadom
- National Institute for Stroke and Applied Neurosciences, Faculty of Health and Environmental Studies, Auckland University of Technology, Auckland, New Zealand
| | - Ilias Thomas
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Abel Torres Espin
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Alexis F Turgeon
- Department of Anesthesiology and Critical Care Medicine, Division of Critical Care Medicine, Université Laval, CHU de Québec-Université Laval Research Center, Québec City, QC, Canada
| | - Andreas Unterberg
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Dominique Van Praag
- Departments of Clinical Psychology and Neurosurgery, Antwerp University Hospital, and University of Antwerp, Edegem, Belgium
| | - Ernest van Veen
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - Thijs Vande Vyvere
- Department of Radiology, Faculty of Medicine and Health Sciences, Department of Rehabilitation Sciences (MOVANT), Antwerp University Hospital, and University of Antwerp, Edegem, Belgium
| | - Kevin K W Wang
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Eveline J A Wiegers
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - W Huw Williams
- Centre for Clinical Neuropsychology Research, Department of Psychology, University of Exeter, Exeter, UK
| | - Lindsay Wilson
- Division of Psychology, University of Stirling, Stirling, UK
| | - Stephen R Wisniewski
- University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Alexander Younsi
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - John K Yue
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Esther L Yuh
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Frederick A Zeiler
- Departments of Surgery, Human Anatomy and Cell Science, and Biomedical Engineering, Rady Faculty of Health Sciences and Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Marina Zeldovich
- Institute of Medical Psychology and Medical Sociology, University Medical Center Goettingen, Goettingen, Germany
| | - Roger Zemek
- Departments of Pediatrics and Emergency Medicine, University of Ottawa, Children’s Hospital of Eastern Ontario, ON, Canada
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Abstract
PURPOSE OF REVIEW Outcome following traumatic brain injury (TBI) remains variable, and derangements in cerebral metabolism are a common finding in patients with poor outcome. This review compares our understanding of cerebral metabolism in health with derangements seen following TBI. RECENT FINDINGS Ischemia is common within the first 24 h of injury and inconsistently detected by bedside monitoring. Metabolic derangements can also result from tissue hypoxia in the absence of ischemic reductions in blood flow due to microvascular ischemia and mitochondrial dysfunction. Glucose delivery across the injured brain is dependent on blood glucose and regional cerebral blood flow, and is an important contributor to derangements in glucose metabolism. Alternative energy substrates such as lactate, ketone bodies and succinate that may support mitochondrial function, and can be utilized when glucose availability is low, have been studied following TBI but require further investigation. SUMMARY Mitochondrial dysfunction and the use of alternative energy substrates are potential therapeutic targets, but improved understanding of the causes, impact and significance of metabolic derangements in clinical TBI are needed. Maintaining adequate oxygen and glucose delivery across the injured brain may accelerate the recovery of mitochondrial function and cerebral energy metabolism and remain important management targets.
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Affiliation(s)
- Simon Demers-Marcil
- Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Anesthesiology and Critical Care, CHU de Québec-Université Laval, Quebec City, Quebec, Canada
| | - Jonathan P. Coles
- Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
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de Cássia Almeida Vieira R, Silveira JCP, Paiva WS, de Oliveira DV, de Souza CPE, Santana-Santos E, de Sousa RMC. Prognostic Models in Severe Traumatic Brain Injury: A Systematic Review and Meta-analysis. Neurocrit Care 2022; 37:790-805. [PMID: 35941405 DOI: 10.1007/s12028-022-01547-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 06/04/2022] [Indexed: 11/30/2022]
Abstract
This review aimed to analyze the results of investigations that performed external validation or that compared prognostic models to identify the models and their variations that showed the best performance in predicting mortality, survival, and unfavorable outcome after severe traumatic brain injury. Pubmed, Embase, Scopus, Web of Science, Cumulative Index to Nursing and Allied Health Literature, Google Scholar, TROVE, and Open Grey databases were searched. A total of 1616 studies were identified and screened, and 15 studies were subsequently included for analysis after applying the selection criteria. The Corticosteroid Randomization After Significant Head Injury (CRASH) and International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) models were the most externally validated among studies of severe traumatic brain injury. The results of the review showed that most publications encountered an area under the curve ≥ 0.70. The area under the curve meta-analysis showed similarity between the CRASH and IMPACT models and their variations for predicting mortality and unfavorable outcomes. Calibration results showed that the variations of CRASH and IMPACT models demonstrated adequate calibration in most studies for both outcomes, but without a clear indication of uncertainties in the evaluations of these models. Based on the results of this meta-analysis, the choice of prognostic models for clinical application may depend on the availability of predictors, characteristics of the population, and trauma care services.
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Affiliation(s)
- Rita de Cássia Almeida Vieira
- CAPES Foundation, Ministry of Education, Brasilia, Brazil.
- School of Nursing, University of Sao Paulo, São Paulo, Brazil.
- Nursing Postgraduate Program, University of Sergipe, Sao Cristovao, Sergipe, Brazil.
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14
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Management of moderate to severe traumatic brain injury: an update for the intensivist. Intensive Care Med 2022; 48:649-666. [PMID: 35595999 DOI: 10.1007/s00134-022-06702-4] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 04/09/2022] [Indexed: 01/04/2023]
Abstract
Traumatic brain injury (TBI) remains one of the most fatal and debilitating conditions in the world. Current clinical management in severe TBI patients is mainly concerned with reducing secondary insults and optimizing the balance between substrate delivery and consumption. Over the past decades, multimodality monitoring has become more widely available, and clinical management protocols have been published that recommend potential interventions to correct pathophysiological derangements. Even while evidence from randomized clinical trials is still lacking for many of the recommended interventions, these protocols and algorithms can be useful to define a clear standard of therapy where novel interventions can be added or be compared to. Over the past decade, more attention has been paid to holistic management, in which hemodynamic, respiratory, inflammatory or coagulation disturbances are detected and treated accordingly. Considerable variability with regards to the trajectories of recovery exists. Even while most of the recovery occurs in the first months after TBI, substantial changes may still occur in a later phase. Neuroprognostication is challenging in these patients, where a risk of self-fulfilling prophecies is a matter of concern. The present article provides a comprehensive and practical review of the current best practice in clinical management and long-term outcomes of moderate to severe TBI in adult patients admitted to the intensive care unit.
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15
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Thomas I, Dickens AM, Posti JP, Czeiter E, Duberg D, Sinioja T, Kråkström M, Retel Helmrich IRA, Wang KKW, Maas AIR, Steyerberg EW, Menon DK, Tenovuo O, Hyötyläinen T, Büki A, Orešič M. Serum metabolome associated with severity of acute traumatic brain injury. Nat Commun 2022; 13:2545. [PMID: 35538079 PMCID: PMC9090763 DOI: 10.1038/s41467-022-30227-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 04/21/2022] [Indexed: 12/12/2022] Open
Abstract
Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.
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Affiliation(s)
- Ilias Thomas
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Alex M Dickens
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.,Department of Chemistry, University of Turku, Turku, Finland
| | - Jussi P Posti
- Neurocenter, Department of Neurosurgery and Turku Brain Injury Center, Turku University Hospital and University of Turku, Turku, Finland
| | - Endre Czeiter
- Department of Neurosurgery, Medical School, University of Pécs, Pécs, Hungary.,Neurotrauma Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary.,MTA-PTE Clinical Neuroscience MR Research Group, Pécs, Hungary
| | - Daniel Duberg
- Department of Chemistry, Örebro University, Örebro, Sweden
| | - Tim Sinioja
- Department of Chemistry, Örebro University, Örebro, Sweden
| | - Matilda Kråkström
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
| | - Isabel R A Retel Helmrich
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, The Netherlands
| | - Kevin K W Wang
- Program for Neurotrauma, Neuroproteomics & Biomarkers Research, Department of Emergency Medicine, McKnight Brin Institute of the University of Florida, Gainesville, Florida, USA
| | - Andrew I R Maas
- Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium
| | - Ewout W Steyerberg
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, The Netherlands.,Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Olli Tenovuo
- Neurocenter, Department of Neurosurgery and Turku Brain Injury Center, Turku University Hospital and University of Turku, Turku, Finland
| | | | - András Büki
- School of Medical Sciences, Örebro University, Örebro, Sweden.,Department of Neurosurgery, Medical School, University of Pécs, Pécs, Hungary.,Neurotrauma Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary
| | - Matej Orešič
- School of Medical Sciences, Örebro University, Örebro, Sweden. .,Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
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16
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Helmrich IRAR, Mikolić A, Kent DM, Lingsma HF, Wynants L, Steyerberg EW, van Klaveren D. Does poor methodological quality of prediction modeling studies translate to poor model performance? An illustration in traumatic brain injury. Diagn Progn Res 2022; 6:8. [PMID: 35509061 PMCID: PMC9068255 DOI: 10.1186/s41512-022-00122-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/09/2022] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Prediction modeling studies often have methodological limitations, which may compromise model performance in new patients and settings. We aimed to examine the relation between methodological quality of model development studies and their performance at external validation. METHODS We systematically searched for externally validated multivariable prediction models that predict functional outcome following moderate or severe traumatic brain injury. Risk of bias and applicability of development studies was assessed with the Prediction model Risk Of Bias Assessment Tool (PROBAST). Each model was rated for its presentation with sufficient detail to be used in practice. Model performance was described in terms of discrimination (AUC), and calibration. Delta AUC (dAUC) was calculated to quantify the percentage change in discrimination between development and validation for all models. Generalized estimation equations (GEE) were used to examine the relation between methodological quality and dAUC while controlling for clustering. RESULTS We included 54 publications, presenting ten development studies of 18 prediction models, and 52 external validation studies, including 245 unique validations. Two development studies (four models) were found to have low risk of bias (RoB). The other eight publications (14 models) showed high or unclear RoB. The median dAUC was positive in low RoB models (dAUC 8%, [IQR - 4% to 21%]) and negative in high RoB models (dAUC - 18%, [IQR - 43% to 2%]). The GEE showed a larger average negative change in discrimination for high RoB models (- 32% (95% CI: - 48 to - 15) and unclear RoB models (- 13% (95% CI: - 16 to - 10)) compared to that seen in low RoB models. CONCLUSION Lower methodological quality at model development associates with poorer model performance at external validation. Our findings emphasize the importance of adherence to methodological principles and reporting guidelines in prediction modeling studies.
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Affiliation(s)
- Isabel R A Retel Helmrich
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, the Netherlands.
| | - Ana Mikolić
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, the Netherlands
| | - David M Kent
- Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies/Tufts Medical Center, Boston, USA
| | - Hester F Lingsma
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, the Netherlands
| | - Laure Wynants
- Department of Epidemiology, School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Ewout W Steyerberg
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, the Netherlands
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - David van Klaveren
- Department of Public Health, Center for Medical Decision Making, Erasmus MC-University Medical Center, Rotterdam, the Netherlands
- Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies/Tufts Medical Center, Boston, USA
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17
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Morris RS, Figueroa JF, Pokrzywa CJ, Barber JK, Temkin NR, Bergner C, Karam BS, Murphy P, Nelson LD, Laud P, Cooper Z, de Moya M, Trevino C, Tignanelli CJ, deRoon-Cassini TA. Predicting outcomes after traumatic brain injury: A novel hospital prediction model for a patient reported outcome. Am J Surg 2022; 224:1150-1155. [DOI: 10.1016/j.amjsurg.2022.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/14/2022] [Accepted: 05/17/2022] [Indexed: 11/28/2022]
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18
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Cruz Navarro J, Ponce Mejia LL, Robertson C. A Precision Medicine Agenda in Traumatic Brain Injury. Front Pharmacol 2022; 13:713100. [PMID: 35370671 PMCID: PMC8966615 DOI: 10.3389/fphar.2022.713100] [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] [Received: 05/21/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
Traumatic brain injury remains a leading cause of death and disability across the globe. Substantial uncertainty in outcome prediction continues to be the rule notwithstanding the existing prediction models. Additionally, despite very promising preclinical data, randomized clinical trials (RCTs) of neuroprotective strategies in moderate and severe TBI have failed to demonstrate significant treatment effects. Better predictive models are needed, as the existing validated ones are more useful in prognosticating poor outcome and do not include biomarkers, genomics, proteonomics, metabolomics, etc. Invasive neuromonitoring long believed to be a "game changer" in the care of TBI patients have shown mixed results, and the level of evidence to support its widespread use remains insufficient. This is due in part to the extremely heterogenous nature of the disease regarding its etiology, pathology and severity. Currently, the diagnosis of traumatic brain injury (TBI) in the acute setting is centered on neurological examination and neuroimaging tools such as CT scanning and MRI, and its treatment has been largely confronted using a "one-size-fits-all" approach, that has left us with many unanswered questions. Precision medicine is an innovative approach for TBI treatment that considers individual variability in genes, environment, and lifestyle and has expanded across the medical fields. In this article, we briefly explore the field of precision medicine in TBI including biomarkers for therapeutic decision-making, multimodal neuromonitoring, and genomics.
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Affiliation(s)
- Jovany Cruz Navarro
- Departments of Anesthesiology and Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Lucido L Ponce Mejia
- Departments of Neurosurgery and Neurology, LSU Health Science Center, New Orleans, LA, United States
| | - Claudia Robertson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
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19
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Continuous Determination of the Optimal Bispectral Index Value Based on Cerebrovascular Reactivity in Moderate/Severe Traumatic Brain Injury: A Retrospective Observational Cohort Study of a Novel Individualized Sedation Target. Crit Care Explor 2022; 4:e0656. [PMID: 35265854 PMCID: PMC8901214 DOI: 10.1097/cce.0000000000000656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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20
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Froese L, Gomez A, Sainbhi AS, Batson C, Stein K, Alizadeh A, Zeiler FA. Dynamic Temporal Relationship Between Autonomic Function and Cerebrovascular Reactivity in Moderate/Severe Traumatic Brain Injury. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:837860. [PMID: 36926091 PMCID: PMC10013014 DOI: 10.3389/fnetp.2022.837860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/28/2022] [Indexed: 12/12/2022]
Abstract
There has been little change in morbidity and mortality in traumatic brain injury (TBI) in the last 25 years. However, literature has emerged linking impaired cerebrovascular reactivity (a surrogate of cerebral autoregulation) with poor outcomes post-injury. Thus, cerebrovascular reactivity (derived through the pressure reactivity index; PRx) is emerging as an important continuous measure. Furthermore, recent literature indicates that autonomic dysfunction may drive impaired cerebrovascular reactivity in moderate/severe TBI. Thus, to improve our understanding of this association, we assessed the physiological relationship between PRx and the autonomic variables of heart rate variability (HRV), blood pressure variability (BPV), and baroreflex sensitivity (BRS) using time-series statistical methodologies. These methodologies include vector autoregressive integrative moving average (VARIMA) impulse response function analysis, Granger causality, and hierarchical clustering. Granger causality testing displayed inconclusive results, where PRx and the autonomic variables had varying bidirectional relationships. Evaluating the temporal profile of the impulse response function plots demonstrated that the autonomic variables of BRS, ratio of low/high frequency of HRV and very low frequency HRV all had a strong relation to PRx, indicating that the sympathetic autonomic response may be more closely linked to cerebrovascular reactivity, then other variables. Finally, BRS was consistently associated with PRx, possibly demonstrating a deeper relationship to PRx than other autonomic measures. Taken together, cerebrovascular reactivity and autonomic response are interlinked, with a bidirectional impact between cerebrovascular reactivity and circulatory autonomics. However, this work is exploratory and preliminary, with further study required to extract and confirm any underlying relationships.
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Affiliation(s)
- Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Alwyn Gomez
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Amanjyot Singh Sainbhi
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Carleen Batson
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Kevin Stein
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Arsalan Alizadeh
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Frederick A. Zeiler
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Centre on Aging, University of Manitoba, Winnipeg, MB, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
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21
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Ponsford J, Spitz G, Hicks AJ. Highlights in traumatic brain injury research in 2021. Lancet Neurol 2021; 21:5-6. [PMID: 34942137 DOI: 10.1016/s1474-4422(21)00424-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 11/23/2021] [Indexed: 12/30/2022]
Affiliation(s)
- Jennie Ponsford
- Monash Epworth Rehabilitation Research Centre, Richmond, VIC, 3121, Australia; Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.
| | - Gershon Spitz
- Monash Epworth Rehabilitation Research Centre, Richmond, VIC, 3121, Australia; Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Amelia J Hicks
- Monash Epworth Rehabilitation Research Centre, Richmond, VIC, 3121, Australia; Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
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22
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Batson C, Froese L, Gomez A, Sainbhi AS, Stein KY, Alizadeh A, Zeiler FA. Impact of Age and Biological Sex on Cerebrovascular Reactivity in Adult Moderate/Severe Traumatic Brain Injury: An Exploratory Analysis. Neurotrauma Rep 2021; 2:488-501. [PMID: 34901944 PMCID: PMC8655816 DOI: 10.1089/neur.2021.0039] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Age and biological sex are two potential important modifiers of cerebrovascular reactivity post-traumatic brain injury (TBI) requiring close evaluation for potential subgroup responses. The goal of this study was to provide a preliminary exploratory analysis of the impact of age and biological sex on measures of cerebrovascular function in moderate/severe TBI. Forty-nine patients from the prospectively maintained TBI database at the University of Manitoba with archived high-frequency digital cerebral physiology were evaluated. Cerebrovascular reactivity indices were derived as follows: PRx (correlation between intracranial pressure [ICP] and mean arterial pressure [MAP]), PAx (correlation between pulse amplitude of ICP [AMP] and MAP), and RAC (correlation between AMP and cerebral perfusion pressure [CPP]). Time above clinically significant thresholds for each index was calculated over different periods of the acute intensive care unit stay. The association between PRx, PAx, and RAC measures with age was assessed using linear regression, and an age trichotomization scheme (<40, 40-60, >60) using Kruskal-Wallis testing. Similarly, association with biological sex was tested using Mann-Whitney U testing. Biological sex did not demonstrate an impact on any measures of cerebrovascular reactivity. Linear regression between age and PAx and RAC demonstrated a statistically significant positive linear relationship. Median PAx and RAC measures between trichotomized age categories demonstrated statistically significant increases with advancing age. The PRx failed to demonstrate any statistically significant relationship with age in this cohort, suggesting that in elderly patients with controlled ICP, PAx and RAC may be better metrics for detecting impaired cerebrovascular reactivity. Biological sex appears to not be associated with differences in cerebrovascular reactivity in this cohort. The PRx performed the worst in detecting impaired cerebrovascular reactivity in those with advanced age, where PAx and RAC appear to have excelled. Future work is required to validate these findings and explore the utility of different cerebrovascular reactivity indices.
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Affiliation(s)
- Carleen Batson
- Department of Human Anatomy and Cell Science, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Alwyn Gomez
- Department of Human Anatomy and Cell Science, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Amanjyot Singh Sainbhi
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Kevin Y. Stein
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Arsalan Alizadeh
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Frederick A. Zeiler
- Department of Human Anatomy and Cell Science, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Centre on Aging, University of Manitoba, Winnipeg, Manitoba, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
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23
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Zeiler FA, Iturria-Medina Y, Thelin EP, Gomez A, Shankar JJ, Ko JH, Figley CR, Wright GEB, Anderson CM. Integrative Neuroinformatics for Precision Prognostication and Personalized Therapeutics in Moderate and Severe Traumatic Brain Injury. Front Neurol 2021; 12:729184. [PMID: 34557154 PMCID: PMC8452858 DOI: 10.3389/fneur.2021.729184] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 08/09/2021] [Indexed: 01/13/2023] Open
Abstract
Despite changes in guideline-based management of moderate/severe traumatic brain injury (TBI) over the preceding decades, little impact on mortality and morbidity have been seen. This argues against the “one-treatment fits all” approach to such management strategies. With this, some preliminary advances in the area of personalized medicine in TBI care have displayed promising results. However, to continue transitioning toward individually-tailored care, we require integration of complex “-omics” data sets. The past few decades have seen dramatic increases in the volume of complex multi-modal data in moderate and severe TBI care. Such data includes serial high-fidelity multi-modal characterization of the cerebral physiome, serum/cerebrospinal fluid proteomics, admission genetic profiles, and serial advanced neuroimaging modalities. Integrating these complex and serially obtained data sets, with patient baseline demographics, treatment information and clinical outcomes over time, can be a daunting task for the treating clinician. Within this review, we highlight the current status of such multi-modal omics data sets in moderate/severe TBI, current limitations to the utilization of such data, and a potential path forward through employing integrative neuroinformatic approaches, which are applied in other neuropathologies. Such advances are positioned to facilitate the transition to precision prognostication and inform a top-down approach to the development of personalized therapeutics in moderate/severe TBI.
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Affiliation(s)
- Frederick A Zeiler
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada.,Centre on Aging, University of Manitoba, Winnipeg, MB, Canada.,Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada.,Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
| | - Eric P Thelin
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Alwyn Gomez
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Jai J Shankar
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Chase R Figley
- Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Galen E B Wright
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chris M Anderson
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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24
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Khaki D, Hietanen V, Corell A, Hergès HO, Ljungqvist J. Selection of CT variables and prognostic models for outcome prediction in patients with traumatic brain injury. Scand J Trauma Resusc Emerg Med 2021; 29:94. [PMID: 34274009 PMCID: PMC8285829 DOI: 10.1186/s13049-021-00901-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/11/2021] [Indexed: 11/26/2022] Open
Abstract
Background Traumatic brain injuries (TBI) are associated with high risk of morbidity and mortality. Early outcome prediction in patients with TBI require reliable data input and stable prognostic models. The aim of this investigation was to analyze different CT classification systems and prognostic calculators in a representative population of TBI-patients, with known outcomes, in a neurointensive care unit (NICU), to identify the most suitable CT scoring system for continued research. Materials and methods We retrospectively included 158 consecutive patients with TBI admitted to the NICU at a level 1 trauma center in Sweden from 2012 to 2016. Baseline data on admission was recorded, CT scans were reviewed, and patient outcome one year after trauma was assessed according to Glasgow Outcome Scale (GOS). The Marshall classification, Rotterdam scoring system, Helsinki CT score and Stockholm CT score were tested, in addition to the IMPACT and CRASH prognostic calculators. The results were then compared with the actual outcomes. Results Glasgow Coma Scale score on admission was 3–8 in 38%, 9–13 in 27.2%, and 14–15 in 34.8% of the patients. GOS after one year showed good recovery in 15.8%, moderate disability in 27.2%, severe disability in 24.7%, vegetative state in 1.3% and death in 29.7%. When adding the variables from the IMPACT base model to the CT scoring systems, the Stockholm CT score yielded the strongest relationship to actual outcome. The results from the prognostic calculators IMPACT and CRASH were divided into two subgroups of mortality (percentages); ≤50% (favorable outcome) and > 50% (unfavorable outcome). This yielded favorable IMPACT and CRASH scores in 54.4 and 38.0% respectively. Conclusion The Stockholm CT score and the Helsinki score yielded the closest relationship between the models and the actual outcomes in this consecutive patient series, representative of a NICU TBI-population. Furthermore, the Stockholm CT score yielded the strongest overall relationship when adding variables from the IMPACT base model and would be our method of choice for continued research when using any of the current available CT score models. Supplementary Information The online version contains supplementary material available at 10.1186/s13049-021-00901-6.
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Affiliation(s)
- Djino Khaki
- Department of Neurosurgery, Sahlgrenska University Hospital, SE-413 45, Gothenburg, Sweden. .,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
| | - Virpi Hietanen
- Department of Anesthesia and Intensive Care, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alba Corell
- Department of Neurosurgery, Sahlgrenska University Hospital, SE-413 45, Gothenburg, Sweden.,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Helena Odenstedt Hergès
- Department of Anesthesia and Intensive Care, Sahlgrenska University Hospital, Gothenburg, Sweden.,Institute of Anesthesiology and Intensive Care Medicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Johan Ljungqvist
- Department of Neurosurgery, Sahlgrenska University Hospital, SE-413 45, Gothenburg, Sweden. .,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
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25
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Edlow BL, Naccache L. Unmasking Covert Language Processing in the Intensive Care Unit with Electroencephalography. Ann Neurol 2021; 89:643-645. [PMID: 33491250 PMCID: PMC8048541 DOI: 10.1002/ana.26030] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/20/2021] [Accepted: 01/21/2021] [Indexed: 01/16/2023]
Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
| | - Lionel Naccache
- PICNIC Lab Team, INSERM, U 1127, CNRS UMR 7225, Faculté de Médecine de Sorbonne Université, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, Hôpital Pitié-Salpêtrière, Paris, France.,APHP, Departments of Neurology and of Clinical Neurophysiology, Hôpital de la Salpêtriere, Paris, France
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