Collaborative European NeuroTrauma Effectiveness Research In Traumatic Brain Injury Research Articles

Early versus delayed cranioplasty after decompressive craniectomy in traumatic brain injury: a multicenter observational study within CENTER-TBI and Net-QuRe.

The aim of this study was to compare the outcomes of early (≤ 90 days) and delayed (> 90 days) cranioplasty following decompressive craniectomy (DC) in patients with traumatic brain injury (TBI). The authors analyzed participants enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) and the Neurotraumatology Quality Registry (Net-QuRe) studies who were diagnosed with TBI and underwent DC and subsequent cranioplasty. These prospective, multicenter, observational cohort studies included 5091 patients enrolled from 2014 to 2020. The effect of cranioplasty timing on functional outcome was evaluated with multivariable ordinal regression and with propensity score matching (PSM) in a sensitivity analysis of functional outcome (Glasgow Outcome Scale-Extended [GOSE] score) and quality of life (Quality of Life After Brain Injury [QOLIBRI] instrument) at 12 months following DC. Among 173 eligible patients, 73 (42%) underwent early cranioplasty and 100 (58%) underwent delayed cranioplasty. In the ordinal logistic regression and PSM, similar 12-month GOSE scores were found between the two groups (adjusted odds ratio [aOR] 0.87, 95% CI 0.61-1.21 and 0.88, 95% CI 0.48-1.65, respectively). In the ordinal logistic regression, early cranioplasty was associated with a higher risk for hydrocephalus than that with delayed cranioplasty (aOR 4.0, 95% CI 1.2-16). Postdischarge seizure rates (early cranioplasty: aOR 1.73, 95% CI 0.7-4.7) and QOLIBRI scores (β -1.9, 95% CI -9.1 to 9.6) were similar between the two groups. Functional outcome and quality of life were similar between early and delayed cranioplasty in patients who had undergone DC for TBI. Neurosurgeons may consider performing cranioplasty during the index admission (early) to simplify the patient's chain of care and prevent readmission for cranioplasty but should be vigilant for an increased possibility of hydrocephalus. Clinical trial registration nos.: CENTER-TBI, NCT02210221 (clinicaltrials.gov); Net-QuRe, NTR6003 (trialsearch.who.int) and NL5761 (onderzoekmetmensen.nl).

Frequency and predictors of headache in the first 12 months after traumatic brain injury: results from CENTER-TBI

BackgroundHeadache is a prevalent and debilitating symptom following traumatic brain injury (TBI). Large-scale, prospective cohort studies are needed to establish long-term headache prevalence and associated factors after TBI. This study aimed to assess the frequency and severity of headache after TBI and determine whether sociodemographic factors, injury severity characteristics, and pre- and post-injury comorbidities predicted changes in headache frequency and severity during the first 12 months after injury.MethodsA large patient sample from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study was used. Patients were stratified based on their clinical care pathway: admitted to an emergency room (ER), a ward (ADM) or an intensive care unit (ICU) in the acute phase. Headache was assessed using a single item from the Rivermead Post-Concussion Symptoms Questionnaire measured at baseline, 3, 6 and 12 months after injury. Mixed-effect logistic regression analyses were applied to investigate changes in headache frequency and associated predictors.ResultsA total of 2,291 patients responded to the headache item at baseline. At study enrolment, 59.3% of patients reported acute headache, with similar frequencies across all strata. Female patients and those aged up to 40 years reported a higher frequency of headache at baseline compared to males and older adults. The frequency of severe headache was highest in patients admitted to the ICU. The frequency of headache in the ER stratum decreased substantially from baseline to 3 months and remained from 3 to 6 months. Similar trajectory trends were observed in the ICU and ADM strata across 12 months. Younger age, more severe TBI, fatigue, neck pain and vision problems were among the predictors of more severe headache over time. More than 25% of patients experienced headache at 12 months after injury.ConclusionsHeadache is a common symptom after TBI, especially in female and younger patients. It typically decreases in the first 3 months before stabilising. However, more than a quarter of patients still experienced headache at 12 months after injury. Translational research is needed to advance the clinical decision-making process and improve targeted medical treatment for headache.Trial registrationClinicalTrials.gov NCT02210221.

Imaging Findings in Acute Traumatic Brain Injury: a National Institute of Neurological Disorders and Stroke Common Data Element-Based Pictorial Review and Analysis of Over 4000 Admission Brain Computed Tomography Scans from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

In 2010, the National Institute of Neurological Disorders and Stroke (NINDS) created a set of common data elements (CDEs) to help standardize the assessment and reporting of imaging findings in traumatic brain injury (TBI). However, as opposed to other standardized radiology reporting systems, a visual overview and data to support the proposed standardized lexicon are lacking. We used over 4000 admission computed tomography (CT) scans of patients with TBI from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study to develop an extensive pictorial overview of the NINDS TBI CDEs, with visual examples and background information on individual pathoanatomical lesion types, up to the level of supplemental and emerging information (e.g., location and estimated volumes). We documented the frequency of lesion occurrence, aiming to quantify the relative importance of different CDEs for characterizing TBI, and performed a critical appraisal of our experience with the intent to inform updating of the CDEs. In addition, we investigated the co-occurrence and clustering of lesion types and the distribution of six CT classification systems. The median age of the 4087 patients in our dataset was 50 years (interquartile range, 29-66; range, 0-96), including 238 patients under 18 years old (5.8%). Traumatic subarachnoid hemorrhage (45.3%), skull fractures (37.4%), contusions (31.3%), and acute subdural hematoma (28.9%) were the most frequently occurring CT findings in acute TBI. The ranking of these lesions was the same in patients with mild TBI (baseline Glasgow Coma Scale [GCS] score 13-15) compared with those with moderate-severe TBI (baseline GCS score 3-12), but the frequency of occurrence was up to three times higher in moderate-severe TBI. In most TBI patients with CT abnormalities, there was co-occurrence and clustering of different lesion types, with significant differences between mild and moderate-severe TBI patients. More specifically, lesion patterns were more complex in moderate-severe TBI patients, with more co-existing lesions and more frequent signs of mass effect. These patients also had higher and more heterogeneous CT score distributions, associated with worse predicted outcomes. The critical appraisal of the NINDS CDEs was highly positive, but revealed that full assessment can be time consuming, that some CDEs had very low frequencies, and identified a few redundancies and ambiguity in some definitions. Whilst primarily developed for research, implementation of CDE templates for use in clinical practice is advocated, but this will require development of an abbreviated version. In conclusion, with this study, we provide an educational resource for clinicians and researchers to help assess, characterize, and report the vast and complex spectrum of imaging findings in patients with TBI. Our data provides a comprehensive overview of the contemporary landscape of TBI imaging pathology in Europe, and the findings can serve as empirical evidence for updating the current NINDS radiologic CDEs to version 3.0.

Early vs Late Fixation of Extremity Fractures Among Adults With Traumatic Brain Injury

The optimal timing for fixation of extremity fractures after traumatic brain injury (TBI) remains controversial. To investigate whether patients who underwent extremity fixation within 24 hours of TBI experienced worse outcomes than those who had the procedure 24 hours or more after TBI. This cohort study used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. Patients 16 years or older with TBI who underwent internal extremity fixation met inclusion criteria. To compare outcomes, patients who underwent the procedure within 24 hours were propensity score matched with those who underwent it 24 hours or later. Patients were treated from December 9, 2014, to December 17, 2017. Data analysis was conducted between August 1, 2022, and December 25, 2023. The primary outcome was an unfavorable functional status at 6 months (Glasgow Outcome Scale-Extended [GOSE] score ≤4). A total of 253 patients were included in this study. The median age was 41 (IQR, 27-57) years, and 184 patients (72.7%) were male. The median Injury Severity Score (ISS) was 41 (IQR, 27-49). Approximately half of the patients (122 [48.2%]) had a mild TBI while 120 (47.4%) had moderate to severe TBI. Seventy-four patients (29.2%) underwent an internal extremity fixation within 24 hours, while 179 (70.8%) had the procedure 24 hours or later. At 6 months, 86 patients (34.0%) had an unfavorable functional outcome. After propensity score matching, there were no statistically significant differences in unfavorable functional outcomes at 6 months (odds ratio [OR], 1.12 [95% CI, 0.51-1.99]; P = .77) in patients with TBI of any severity. Similar results were observed in patients with mild TBI (OR, 0.71 [95% CI, 0.22-2.29]; P = .56) and moderate to severe TBI (OR, 1.08 [95% CI, 0.32-3.70]; P = .90). The outcomes of extremity fracture fixation performed within 24 hours after TBI appear not to be worse than those of procedures performed 24 hours or later. This finding suggests that early fixation after TBI could be considered in patients with mild head injuries.

Early systemic insults following traumatic brain injury: association with biomarker profiles, therapy for intracranial hypertension, and neurological outcomes—an analysis of CENTER-TBI data

PurposeWe analysed the impact of early systemic insults (hypoxemia and hypotension, SIs) on brain injury biomarker profiles, acute care requirements during intensive care unit (ICU) stay, and 6-month outcomes in patients with traumatic brain injury (TBI).MethodsFrom patients recruited to the Collaborative European neurotrauma effectiveness research in TBI (CENTER-TBI) study, we documented the prevalence and risk factors for SIs and analysed their effect on the levels of brain injury biomarkers [S100 calcium-binding protein B (S100B), neuron-specific enolase (NSE), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and protein Tau], critical care needs, and 6-month outcomes [Glasgow Outcome Scale Extended (GOSE)].ResultsAmong 1695 TBI patients, 24.5% had SIs: 16.1% had hypoxemia, 15.2% had hypotension, and 6.8% had both. Biomarkers differed by SI category, with higher S100B, Tau, UCH-L1, NSE and NfL values in patients with hypotension or both SIs. The ratio of neural to glial injury (quantified as UCH-L1/GFAP and Tau/GFAP ratios) was higher in patients with hypotension than in those with no SIs or hypoxia alone. At 6 months, 380 patients died (22%), and 759 (45%) had GOSE ≤ 4. Patients who experienced at least one SI had higher mortality than those who did not (31.8% vs. 19%, p < 0.001).ConclusionThough less frequent than previously described, SIs in TBI patients are associated with higher release of neuronal than glial injury biomarkers and with increased requirements for ICU therapies aimed at reducing intracranial hypertension. Hypotension or combined SIs are significantly associated with adverse 6-month outcomes. Current criteria for hypotension may lead to higher biomarker levels and more negative outcomes than those for hypoxemia suggesting a need to revisit pressure targets in the prehospital settings.

Association Between Early External Ventricular Drain Insertion and Functional Outcomes 6 Months Following Moderate-to-Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is a leading global cause of morbidity and mortality. Intracranial hypertension following moderate-to-severe TBI (m-sTBI) is a potentially modifiable secondary cerebral insult and one of the central therapeutic targets of contemporary neurocritical care. External ventricular drain (EVD) insertion is a common therapeutic intervention used to control intracranial hypertension and attenuate secondary brain injury. However, the optimal timing of EVD insertion in the setting of m-sTBI is uncertain and practice variation is widespread. Therefore, we aimed to assess if there is an association between timing of EVD placement and functional neurological outcome at 6 months post m-sTBI. We pooled individual patient data for all relevant harmonizable variables from the Erythropoietin in Traumatic Brain Injury (EPO-TBI) and Prophylactic Hypothermia Trial to Lessen Traumatic Brain Injury (POLAR) randomized control trials, and the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) Core Study version 3.0 and Australia-Europe NeuroTrauma Effectiveness Research in TBI (Oz-ENTER) prospective observational studies to create a combined dataset. The Glasgow Coma Scale (GCS) score was used to define TBI severity and we included all patients admitted to an intensive care unit with a GCS ≤12, who were 15 years or older and underwent EVD placement within 7 days of injury. We used hierarchical multi-variable logistic regression models to study the association between EVD insertion within 24 h of injury (early) compared with EVD insertion more than 24 h after injury (late) and 6-month functional neurological outcome measured using the Glasgow Outcome Score Extended (GOSE). In total, 2536 patients were assessed. Of these, 502 (20%) underwent early EVD insertion and 145 (6%) underwent late EVD insertion. Following adjustment for the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in TBI) score extended (Core + CT), sex, injury severity score, study and treatment site, patients receiving a late EVD had higher odds of death or severe disability (GOSE 1-4) at 6 months follow-up than those receiving an early EVD adjusted odds ratio; 95% confidence interval, 2.14; 1.22-3.76; p = 0.008. Our study suggests that in patients with m-sTBI where an EVD is needed, early (≤ 24 h post-injury) insertion may result in better long-term functional outcomes. This finding supports future prospective investigation in this area.

Development of a Multimodal Machine Learning-Based Prognostication Model for Traumatic Brain Injury Using Clinical Data and Computed Tomography Scans: A CENTER-TBI and CINTER-TBI Study.

Computed tomography (CT) is an important imaging modality for guiding prognostication in patients with traumatic brain injury (TBI). However, because of the specialized expertise necessary, timely and dependable TBI prognostication based on CT imaging remains challenging. This study aimed to enhance the efficiency and reliability of TBI prognostication by employing machine learning (ML) techniques on CT images. A retrospective analysis was conducted on the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) data set (n = 1016). An ML-driven binary classifier was developed to predict favorable or unfavorable outcomes at 6 months post-injury. The prognostic performance was assessed using the area under the curve (AUC) over fivefold cross-validation and compared with conventional models that depend on clinical variables and CT scoring systems. An external validation was performed using the Comparative Indian Neurotrauma Effectiveness Research in Traumatic Brain Injury (CINTER-TBI) data set (n = 348). The developed model achieved superior performance without the necessity for manual CT assessments (AUC = 0.846 [95% CI: 0.843-0.849]) compared with the model based on the clinical and laboratory variables (AUC = 0.817 [95% CI: 0.814-0.820]) and established CT scoring systems requiring manual interpretations (AUC = 0.829 [95% CI: 0.826-0.832] for Marshall and 0.838 [95% CI: 0.835-0.841] for International Mission for Prognosis and Analysis of Clinical Trials in TBI [IMPACT]). The external validation demonstrated the prognostic capacity of the developed model to be significantly better (AUC = 0.859 [95% CI: 0.857-0.862]) than the model using clinical variables (AUC = 0.809 [95% CI: 0.798-0.820]). This study established an ML-based model that provides efficient and reliable TBI prognosis based on CT scans, with potential implications for earlier intervention and improved patient outcomes.

Clinical descriptors of disease trajectories in patients with traumatic brain injury in the intensive care unit (CENTER-TBI): a multicentre observational cohort study

Patients with traumatic brain injury are a heterogeneous population, and the most severely injured individuals are often treated in an intensive care unit (ICU). The primary injury at impact, and the harmful secondary events that can occur during the first week of the ICU stay, will affect outcome in this vulnerable group of patients. We aimed to identify clinical variables that might distinguish disease trajectories among patients with traumatic brain injury admitted to the ICU. We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. We included patients aged 18 years or older with traumatic brain injury who were admitted to the ICU at one of the 65 CENTER-TBI participating centres, which range from large academic hospitals to small rural hospitals. For every patient, we obtained pre-injury data and injury features, clinical characteristics on admission, demographics, physiological parameters, laboratory features, brain biomarkers (ubiquitin carboxy-terminal hydrolase L1 [UCH-L1], S100 calcium-binding protein B [S100B], tau, neurofilament light [NFL], glial fibrillary acidic protein [GFAP], and neuron-specific enolase [NSE]), and information about intracranial pressure lowering treatments during the first 7 days of ICU stay. To identify clinical variables that might distinguish disease trajectories, we applied a novel clustering method to these data, which was based on a mixture of probabilistic graph models with a Markov chain extension. The relation of clusters to the extended Glasgow Outcome Scale (GOS-E) was investigated. Between Dec 19, 2014, and Dec 17, 2017, 4509 patients with traumatic brain injury were recruited into the CENTER-TBI core dataset, of whom 1728 were eligible for this analysis. Glucose variation (defined as the difference between daily maximum and minimum glucose concentrations) and brain biomarkers (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were consistently found to be the main clinical descriptors of disease trajectories (ie, the leading variables contributing to the distinguishing clusters) in patients with traumatic brain injury in the ICU. The disease trajectory cluster to which a patient was assigned in a model was analysed as a predictor together with variables from the IMPACT model, and prediction of both mortality and unfavourable outcome (dichotomised GOS-E ≤4) was improved. First-day ICU admission data are not the only clinical descriptors of disease trajectories in patients with traumatic brain injury. By analysing temporal variables in our study, variation of glucose was identified as the most important clinical descriptor that might distinguish disease trajectories in the ICU, which should direct further research. Biomarkers of brain injury (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were also top clinical descriptors over time, suggesting they might be important in future clinical practice. European Union 7th Framework program, Hannelore Kohl Stiftung, OneMind, Integra LifeSciences Corporation, and NeuroTrauma Sciences.

Therapy Intensity Level Scale for Traumatic Brain Injury: Clinimetric Assessment on Neuro-Monitored Patients Across 52 European Intensive Care Units.

Intracranial pressure (ICP) data from traumatic brain injury (TBI) patients in the intensive care unit (ICU) cannot be interpreted appropriately without accounting for the effect of administered therapy intensity level (TIL) on ICP. A 15-point scale was originally proposed in 1987 to quantify the hourly intensity of ICP-targeted treatment. This scale was subsequently modified-through expert consensus-during the development of TBI Common Data Elements to address statistical limitations and improve usability. The latest 38-point scale (hereafter referred to as TIL) permits integrated scoring for a 24-h period and has a five-category, condensed version (TIL(Basic)) based on qualitative assessment. Here, we perform a total- and component-score analysis of TIL and TIL(Basic) to: 1) validate the scales across the wide variation in contemporary ICP management; 2) compare their performance against that of predecessors; and 3) derive guidelines for proper scale use. From the observational Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study, we extract clinical data from a prospective cohort of ICP-monitored TBI patients (n = 873) from 52 ICUs across 19 countries. We calculate daily TIL and TIL(Basic) scores (TIL24 and TIL(Basic)24, respectively) from each patient's first week of ICU stay. We also calculate summary TIL and TIL(Basic) scores by taking the first-week maximum (TILmax and TIL(Basic)max) and first-week median (TILmedian and TIL(Basic)median) of TIL24 and TIL(Basic)24 scores for each patient. We find that, across all measures of construct and criterion validity, the latest TIL scale performs significantly greater than or similarly to all alternative scales (including TIL(Basic)) and integrates the widest range of modern ICP treatments. TILmedian outperforms both TILmax and summarized ICP values in detecting refractory intracranial hypertension (RICH) during ICU stay. The RICH detection thresholds which maximize the sum of sensitivity and specificity are TILmedian ≥ 7.5 and TILmax ≥ 14. The TIL24 threshold which maximizes the sum of sensitivity and specificity in the detection of surgical ICP control is TIL24 ≥ 9. The median scores of each TIL component therapy over increasing TIL24 reflect a credible staircase approach to treatment intensity escalation, from head positioning to surgical ICP control, as well as considerable variability in the use of cerebrospinal fluid drainage and decompressive craniectomy. Since TIL(Basic)max suffers from a strong statistical ceiling effect and only covers 17% (95% confidence interval [CI]: 16-18%) of the information in TILmax, TIL(Basic) should not be used instead of TIL for rating maximum treatment intensity. TIL(Basic)24 and TIL(Basic)median can be suitable replacements for TIL24 and TILmedian, respectively (with up to 33% [95% CI: 31-35%] information coverage) when full TIL assessment is infeasible. Accordingly, we derive numerical ranges for categorising TIL24 scores into TIL(Basic)24 scores. In conclusion, our results validate TIL across a spectrum of ICP management and monitoring approaches. TIL is a more sensitive surrogate for pathophysiology than ICP and thus can be considered an intermediate outcome after TBI.

Prognostic Value of Serum Biomarkers in Patients With Moderate-Severe Traumatic Brain Injury, Differentiated by Marshall Computer Tomography Classification.

Prognostication is challenging in patients with traumatic brain injury (TBI) in whom computed tomography (CT) fails to fully explain a low level of consciousness. Serum biomarkers reflect the extent of structural damage in a different way than CT does, but it is unclear whether biomarkers provide additional prognostic value across the range of CT abnormalities. This study aimed to determine the added predictive value of biomarkers, differentiated by imaging severity. This prognostic study used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (2014-2017). The analysis included patients aged ≥16 years with a moderate-severe TBI (Glasgow Coma Scale [GCS] <13) who had an acute CT and serum biomarkers obtained ≤24h of injury. Of six protein biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH-L1), the most prognostic panel was selected using lasso regression. The performance of established prognostic models (CRASH and IMPACT) was assessed before and after the addition of the biomarker panel and compared between patients with different CT Marshall scores (Marshall score <3 vs. Marshall score ≥3). Outcome was assessed at six months post-injury using the extended Glasgow Outcome Scale (GOSE), and dichotomized into favorable and unfavorable (GOSE <5). We included 872 patients with moderate-severe TBI. The mean age was 47 years (range 16-95); 647 (74%) were male and 438 (50%) had a Marshall CT score <3. The serum biomarkers GFAP, NFL, S100B and UCH-L1 provided complementary prognostic information; NSE and Tau showed no added value. The addition of the biomarker panel to established prognostic models increased the area under the curve (AUC) by 0.08 and 0.03, and the explained variation in outcome by 13-14% and 7-8%, for patients with a Marshall score of <3 and ≥3, respectively. The incremental AUC of biomarkers for individual models was significantly greater when the Marshall score was <3 compared with ≥3 (p < 0.001). Serum biomarkers improve outcome prediction after moderate-severe TBI across the range of imaging severities and especially in patients with a Marshall score <3.

Analysis of intracranial pressure pulse waveform in traumatic brain injury patients: a CENTER-TBI study.

Intracranial pressure (ICP) pulse waveform analysis may provide valuable information about cerebrospinal pressure-volume compensation in patients with traumatic brain injury (TBI). The authors applied spectral methods to analyze ICP waveforms in terms of the pulse amplitude of ICP (AMP), high frequency centroid (HFC), and higher harmonics centroid (HHC) and also used a morphological classification approach to assess changes in the shape of ICP pulse waveforms using the pulse shape index (PSI). The authors included 184 patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High-Resolution Sub-Study in the analysis. HFC was calculated as the average power-weighted frequency within the 4- to 15-Hz frequency range of the ICP power density spectrum. HHC was defined as the center of mass of the ICP pulse waveform harmonics from the 2nd to the 10th. PSI was defined as the weighted sum of artificial intelligence-based ICP pulse class numbers from 1 (normal pulse waveform) to 4 (pathological waveform). AMP and PSI increased linearly with mean ICP. HFC increased proportionally to ICP until the upper breakpoint (average ICP of 31 mm Hg), whereas HHC slightly increased with ICP and then decreased significantly when ICP exceeded 25 mm Hg. AMP (p < 0.001), HFC (p = 0.003), and PSI (p < 0.001) were significantly greater in patients who died than in patients who survived. Among those patients with low ICP (< 15 mm Hg), AMP, PSI, and HFC were greater in those with poor outcome than in those with good outcome (all p < 0.001). Whereas HFC, AMP, and PSI could be used as predictors of mortality, HHC may potentially serve as an early warning sign of intracranial hypertension. Elevated HFC, AMP, and PSI were associated with poor outcome in TBI patients with low ICP.

Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3-week post-concussion and mental health symptoms. Predictors were selected based on Akaike's Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better discriminative ability (C = 0.71[0.69 to 0.72] with early symptoms; 0.71[0.70 to 0.72] with CT variables or with blood biomarkers; 0.72[0.71 to 0.73] with all three categories). The performance of models for RPQ was modest (R2 = 4% Core; R2 = 9% Clinical), and extensions with early symptoms increased the R2 to 12%. The 2-3-week models had better performance for both outcomes in the subset of participants with these symptoms measured (C = 0.74 [0.71 to 0.78] vs. C = 0.63[0.61 to 0.67] for GOSE; R2 = 37% vs. 6% for RPQ). In conclusion, the models based on variables available before discharge have moderate performance for the prediction of GOSE and poor performance for the prediction of PPCS. Symptoms assessed at 2-3 weeks are required for better predictive ability of both outcomes. The performance of the proposed models should be examined in independent cohorts.

Comparative Effectiveness of Mannitol Versus Hypertonic Saline in Patients With Traumatic Brain Injury: A CENTER-TBI Study.

Increased intracranial pressure (ICP) is one of the most important modifiable and immediate threats to critically ill patients suffering from traumatic brain injury (TBI). Two hyperosmolar agents (HOAs), mannitol and hypertonic saline (HTS), are routinely used in clinical practice to treat increased ICP. We aimed to assess whether a preference for mannitol, HTS, or their combined use translated into differences in outcome. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study is a prospective multi-center cohort study. For this study, patients with TBI, admitted to the intensive care unit (ICU), treated with mannitol and/or HTS, and aged ≥16 years were included. Patients and centers were differentiated based on treatment preference with mannitol and/or HTS based on structured, data-driven criteria such as first administered HOA in the ICU. We assessed influence of center and patient characteristics in the choice of agent using adjusted multi-variate models. Further, we assessed the influence of HOA preference on outcome using adjusted ordinal and logistic regression models, and instrumental variable analyses. In total, 2056 patients were assessed. Of these, 502 (24%) patients received mannitol and/or HTS in the ICU. The first received HOA was HTS for 287 (57%) patients, mannitol for 149 (30%) patients, or both mannitol and HTS on the same day for 66 (13%) patients. Two unreactive pupils were more common in patients receiving both (13, 21%), compared with patients receiving HTS (40, 14%) or mannitol (22, 16%). Center, rather than patient characteristics, was independently associated with the preferred choice of HOA (p-value <0.05). ICU mortality and 6-month outcome were similar between patients preferably treated with mannitol compared with HTS (odds ratio [OR] = 1.0, confidence interval [CI] = 0.4-2.2; OR = 0.9, CI = 0.5-1.6, respectively). Patients who received both also had a similar ICU mortality and 6-month outcome compared with patients receiving HTS (OR = 1.8, CI = 0.7-5.0; OR = 0.6, CI = 0.3-1.7, respectively). We found between-center variability regarding HOA preference. Moreover, we found that center is a more important driver of the choice of HOA than patient characteristics. However, our study indicates that this variability is an acceptable practice given absence of differences in outcomes associated with a specific HOA.

Mortality Prediction in Severe Traumatic Brain Injury Using Traditional and Machine Learning Algorithms.

Prognostic prediction of traumatic brain injury (TBI) in patients is crucial in clinical decision and health care policy making. This study aimed to develop and validate prediction models for in-hospital mortality after severe traumatic brain injury (sTBI). We developed and validated logistic regression (LR), LASSO regression, and machine learning (ML) algorithms including support vector machines (SVM) and XGBoost models. Fifty-four candidate predictors were included. Model performance was expressed in terms of discrimination (C-statistic) and calibration (intercept and slope). For model development, 2804 patients with sTBI in the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China Registry study were included. External validation was performed in 1113 patients with sTBI in the CENTER-TBI European Registry study. XGBoost achieved high discrimination in mortality prediction, and it outperformed logistic and LASSO regression. The XGBoost model established in this study also outperformed prediction models currently available, including the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) core and International Mission for Prognosis and Analysis of Clinical Trials (CRASH) basic models. When including 54 variables, XGBoost and SVM reached C-statistics of 0.87 (95% confidence interval [CI]: 0.81-0.92) and 0.85 (95% CI: 0.79-0.90) at internal validation, and 0.88 (95% CI: 0.87-0.88) and 0.86 (95% CI: 0.85-0.87) at external validation, respectively. A simplified version of XGBoost and SVM using 26 variables selected by recursive feature elimination (RFE) reached C-statistics of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.91) at internal validation, and 0.87 (95% CI: 0.87-0.88) and 0.87 (95% CI: 0.86-0.87) at external validation, respectively. However, when the number of variables included decreased, the difference between ML and LR diminished. All the prediction models can be accessed via a web-based calculator. Glasgow Coma Scale (GCS) score, age, pupillary light reflex, Injury Severity Score (ISS) for brain region, and the presence of acute subdural hematoma were the five strongest predictors for mortality prediction. The study showed that ML techniques such as XGBoost may capture information hidden in demographic and clinical predictors of patients with sTBI and yield more precise predictions compared with LR approaches.

Serum biomarkers identify critically ill traumatic brain injury patients for MRI

BackgroundMagnetic resonance imaging (MRI) carries prognostic importance after traumatic brain injury (TBI), especially when computed tomography (CT) fails to fully explain the level of unconsciousness. However, in critically ill patients, the risk of deterioration during transfer needs to be balanced against the benefit of detecting prognostically relevant information on MRI. We therefore aimed to assess if day of injury serum protein biomarkers could identify critically ill TBI patients in whom the risks of transfer are compensated by the likelihood of detecting management-altering neuroimaging findings.MethodsData were obtained from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. Eligibility criteria included: TBI patients aged ≥ 16 years, Glasgow Coma Score (GCS) < 13 or patient intubated with unrecorded pre-intubation GCS, CT with Marshall score < 3, serum biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH-L1) sampled ≤ 24 h of injury, MRI < 30 days of injury. The degree of axonal injury on MRI was graded using the Adams-Gentry classification. The association between serum concentrations of biomarkers and Adams-Gentry stage was assessed and the optimum threshold concentration identified, assuming different minimum sensitivities for the detection of brainstem injury (Adams-Gentry stage 3). A cost–benefit analysis for the USA and UK health care settings was also performed.ResultsAmong 65 included patients (30 moderate-severe, 35 unrecorded) axonal injury was detected in 54 (83%) and brainstem involvement in 33 (51%). In patients with moderate-severe TBI, brainstem injury was associated with higher concentrations of NSE, Tau, UCH-L1 and GFAP. If the clinician did not want to miss any brainstem injury, NSE could have avoided MRI transfers in up to 20% of patients. If a 94% sensitivity was accepted considering potential transfer-related complications, GFAP could have avoided 30% of transfers. There was no added net cost, with savings up to £99 (UK) or $612 (US). No associations between proteins and axonal injury were found in intubated patients without a recorded pre-intubation GCS.ConclusionsSerum protein biomarkers show potential to safely reduce the number of transfers to MRI in critically ill patients with moderate-severe TBI at no added cost.

Development and External Validation of a Machine Learning Model for the Early Prediction of Doses of Harmful Intracranial Pressure in Patients with Severe Traumatic Brain Injury.

Treatment and prevention of elevated intracranial pressure (ICP) is crucial in patients with severe traumatic brain injury (TBI). Elevated ICP is associated with secondary brain injury, and both intensity and duration of an episode of intracranial hypertension, often referred to as "ICP dose," are associated with worse outcomes. Prediction of such harmful episodes of ICP dose could allow for a more proactive and preventive management of TBI, with potential implications on patients' outcomes. The goal of this study was to develop and validate a machine-learning (ML) model to predict potentially harmful ICP doses in patients with severe TBI. The prediction target was defined based on previous studies and included a broad range of doses of elevated ICP that have been associated with poor long-term neurological outcomes. The ML models were used, with minute-by-minute ICP and mean arterial blood pressure signals as inputs. Harmful ICP episodes were predicted with a 30 min forewarning. Models were developed in a multi-center dataset of 290 adult patients with severe TBI and externally validated on 264 patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) dataset. The external validation of the prediction model on the CENTER-TBI dataset demonstrated good discrimination and calibration (area under the curve: 0.94, accuracy: 0.89, precision: 0.87, sensitivity: 0.78, specificity: 0.94, calibration-in-the-large: 0.03, calibration slope: 0.93). The proposed prediction model provides accurate and timely predictions of harmful doses of ICP on the development and external validation dataset. A future interventional study is needed to assess whether early intervention on the basis of ICP dose predictions will result in improved outcomes.

Concomitant spine trauma in patients with traumatic brain injury: Patient characteristics and outcomes.

Spine injury is highly prevalent in patients with poly-trauma, but data on the co-occurrence of spine trauma in patients with traumatic brain injury (TBI) are scarce. In this study, we used the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) database to assess the prevalence, characteristics, and outcomes of patients with TBI and a concurrent traumatic spinal injury (TSI). Data from the European multi-center CENTER-TBI study were analyzed. Adult patients with TBI (≥18 years) presenting with a concomitant, isolated TSI of at least serious severity (Abbreviated Injury Scale; AIS ≥3) were included. For outcome analysis, comparison groups of TBI patients with TSI and systemic injuries (non-isolated TSI) and without TSI were created using propensity score matching. Rates of mortality, unfavorable outcomes (Glasgow Outcome Scale Extended; GOSe < 5), and full recovery (GOSe 7-8) of all patients and separately for patients with only mild TBI (mTBI) were compared between groups at 6-month follow-up. A total of 164 (4%) of the 4,254 CENTER-TBI core study patients suffered from a concomitant isolated TSI. The median age was 53 [interquartile range (IQR): 37-66] years and 71% of patients were men. mTBI was documented in 62% of cases, followed by severe TBI (26%), and spine injuries were mostly cervical (63%) or thoracic (31%). Surgical spine stabilization was performed in 19% of cases and 57% of patients were admitted to the ICU. Mortality at 6 months was 11% and only 36% of patients regained full recovery. There were no significant differences in the 6-month rates of mortality, unfavorable outcomes, or full recovery between TBI patients with and without concomitant isolated TSI. However, concomitant non-isolated TSI was associated with an unfavorable outcome and a higher mortality. In patients with mTBI, a negative association with full recovery could be observed for both concomitant isolated and non-isolated TSI. Rates of mortality, unfavorable outcomes, and full recovery in TBI patients with and without concomitant, isolated TSIs were comparable after 6 months. However, in patients with mTBI, concomitant TSI was a negative predictor for a full recovery. These findings might indicate that patients with moderate to severe TBI do not necessarily exhibit worse outcomes when having a concomitant TSI, whereas patients with mTBI might be more affected.

Incremental prognostic value of acute serum biomarkers for functional outcome after traumatic brain injury (CENTER-TBI): an observational cohort study

Several studies have reported an association between serum biomarker values and functional outcome following traumatic brain injury. We aimed to examine the incremental (added) prognostic value of serum biomarkers over demographic, clinical, and radiological characteristics and over established prognostic models, such as IMPACT and CRASH, for prediction of functional outcome. We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core study. We included patients aged 14 years or older who had blood sampling within 24 h of injury, results from a CT scan, and outcome assessment according to the Glasgow Outcome Scale-Extended (GOSE) at 6 months. Amounts in serum of six biomarkers (S100 calcium-binding protein B, neuron-specific enolase, glial fibrillary acidic protein, ubiquitin C-terminal hydrolase L1 [UCH-L1], neurofilament protein-light, and total tau) were measured. The incremental prognostic value of these biomarkers was determined separately and in combination. The primary outcome was the GOSE 6 months after injury. Incremental prognostic value, using proportional odds and a dichotomised analysis, was assessed by delta C-statistic and delta R2 between models with and without serum biomarkers, corrected for optimism with a bootstrapping procedure. Serum biomarker values and 6-month GOSE were available for 2283 of 4509 patients. Higher biomarker levels were associated with worse outcome. Adding biomarkers improved the C-statistic by 0·014 (95% CI 0·009-0·020) and R2 by 4·9% (3·6-6·5) for predicting GOSE compared with demographic, clinical, and radiological characteristics. UCH-L1 had the greatest incremental prognostic value. Adding biomarkers to established prognostic models resulted in a relative increase in R2 of 48-65% for IMPACT and 30-34% for CRASH prognostic models. Serum biomarkers have incremental prognostic value for functional outcome after traumatic brain injury. Our findings support integration of biomarkers-particularly UCH-L1-in established prognostic models. European Union's Seventh Framework Programme, Hannelore Kohl Stiftung, OneMind, Integra LifeSciences, and NeuroTrauma Sciences.

The leap to ordinal: Detailed functional prognosis after traumatic brain injury with a flexible modelling approach.

When a patient is admitted to the intensive care unit (ICU) after a traumatic brain injury (TBI), an early prognosis is essential for baseline risk adjustment and shared decision making. TBI outcomes are commonly categorised by the Glasgow Outcome Scale-Extended (GOSE) into eight, ordered levels of functional recovery at 6 months after injury. Existing ICU prognostic models predict binary outcomes at a certain threshold of GOSE (e.g., prediction of survival [GOSE > 1]). We aimed to develop ordinal prediction models that concurrently predict probabilities of each GOSE score. From a prospective cohort (n = 1,550, 65 centres) in the ICU stratum of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) patient dataset, we extracted all clinical information within 24 hours of ICU admission (1,151 predictors) and 6-month GOSE scores. We analysed the effect of two design elements on ordinal model performance: (1) the baseline predictor set, ranging from a concise set of ten validated predictors to a token-embedded representation of all possible predictors, and (2) the modelling strategy, from ordinal logistic regression to multinomial deep learning. With repeated k-fold cross-validation, we found that expanding the baseline predictor set significantly improved ordinal prediction performance while increasing analytical complexity did not. Half of these gains could be achieved with the addition of eight high-impact predictors to the concise set. At best, ordinal models achieved 0.76 (95% CI: 0.74-0.77) ordinal discrimination ability (ordinal c-index) and 57% (95% CI: 54%- 60%) explanation of ordinal variation in 6-month GOSE (Somers' Dxy). Model performance and the effect of expanding the predictor set decreased at higher GOSE thresholds, indicating the difficulty of predicting better functional outcomes shortly after ICU admission. Our results motivate the search for informative predictors that improve confidence in prognosis of higher GOSE and the development of ordinal dynamic prediction models.

Tailoring Multi-Dimensional Outcomes to Level of Functional Recovery after Traumatic Brain Injury.

There is increasing emphasis on assessing multi-dimensional outcomes in traumatic brain injury (TBI), but achieving this aim is hampered by a plethora of overlapping assessment tools. There is a clear need for advice on the choice of outcomes and we examined level of functional recovery as a framework to guide selection of assessments. In this cohort study we analysed cross-sectional data from 2604 patients enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) project. Patients were followed up 6 months after injury and assessed on the Glasgow Outcome Scale-Extended (GOSE), cognitive tests, and patient-reported outcomes. We describe assessment completeness and prevalence of impairment. Relationships between outcomes were visualized using UpSet plots and hierarchical cluster analysis. GOSE categories varied markedly for both completion rates, 34-91% for patient-reported outcomes and 9-81% for cognitive tests, and prevalence of impairment, 3-82% for patient-reported outcomes and 9-59% for cognitive tests. In complete case samples, the GOSE identified impairment in 59-61%, whereas the most impaired patient-reported outcome was the Short Form-12 version 2 (SF-12v2) Physical Component Summary (28% overall), and the most impaired cognitive test was Trail Making Test (TMT) Part A (19% overall). The findings show that degree of disability is a key context of use for cognitive tests and patient-reported outcomes. Level of functional recovery provides a guide to the feasibility of different types of assessment and the likelihood of impairment, and can help tailor suitable assessment approaches in clinical practice and research studies.