IMPACT database of traumatic brain injury: design and description

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

The importance of sharing experimental data in neuroscience grows with the amount and complexity of data acquired and various techniques used to obtain and process these data. However, the majority of experimental data, especially from individual studies of regular-sized laboratories never reach wider research community. A graphical user interface (GUI) engine called Neurovascular Network Explorer 2.0 (NNE 2.0) has been created as a tool for simple and low-cost sharing and exploring of vascular imaging data. NNE 2.0 interacts with a database containing optogenetically-evoked dilation/constriction time-courses of individual vessels measured in mice somatosensory cortex in vivo by 2-photon microscopy. NNE 2.0 enables selection and display of the time-courses based on different criteria (subject, branching order, cortical depth, vessel diameter, arteriolar tree) as well as simple mathematical manipulation (e.g. averaging, peak-normalization) and data export. It supports visualization of the vascular network in 3D and enables localization of the individual functional vessel diameter measurements within vascular trees. NNE 2.0, its source code, and the corresponding database are freely downloadable from UCSD Neurovascular Imaging Laboratory website¹. The source code can be utilized by the users to explore the associated database or as a template for databasing and sharing their own experimental results provided the appropriate format.

[Topical respiratory strategies in neurocritical care]

Management of the respiratory tract and maintenance of adequate gas exchange are the basic goals of critical care. Injury to the nervous system is often accompanied by development of respiratory disorders. On the other hand, changes in the gas composition of arterial blood can cause brain damage. In addition, approaches to the patient with respiratory failure, which are used in general critical care and neurocritical care, may differ. The presented literature review is devoted to modern respiratory strategies used in neurocritical care.

Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities

OBJECTIVE Clinical features such as those included in the Glasgow Coma Scale (GCS) score, pupil reactivity, and patient age, as well as CT findings, have clear established relationships with patient outcomes due to neurotrauma. Nevertheless, predictions made from combining these features in probabilistic models have not found a role in clinical practice. In this study, the authors aimed to develop a method of displaying probabilities graphically that would be simple and easy to use, thus improving the usefulness of prognostic information in neurotrauma. This work builds on a companion paper describing the GCS-Pupils score (GCS-P) as a tool for assessing the clinical severity of neurotrauma. METHODS Information about early GCS score, pupil response, patient age, CT findings, late outcome according to the Glasgow Outcome Scale, and mortality were obtained at the individual adult patient level from the CRASH (Corticosteroid Randomisation After Significant Head Injury; n = 9045) and IMPACT (International Mission for Prognosis and Clinical Trials in TBI; n = 6855) databases. These data were combined into a pooled data set for the main analysis. Logistic regression was first used to model the combined association between the GCS-P and patient age and outcome, following which CT findings were added to the models. The proportion of variability in outcomes "explained" by each model was assessed using Nagelkerke's R². RESULTS The authors observed that patient age and GCS-P have an additive effect on outcome. The probability of mortality 6 months after neurotrauma is greater with increasing age, and for all age groups the probability of death is greater with decreasing GCS-P. Conversely, the probability of favorable recovery becomes lower with increasing age and lessens with decreasing GCS-P. The effect of combining the GCS-P with patient age was substantially more informative than the GCS-P, age, GCS score, or pupil reactivity alone. Two-dimensional charts were produced displaying outcome probabilities, as percentages, for 5-year increments in age between 15 and 85 years, and for GCS-Ps ranging from 1 to 15; it is readily seen that the movement toward combinations at the top right of the charts reflects a decreasing likelihood of mortality and an increasing likelihood of favorable outcome. Analysis of CT findings showed that differences in outcome are very similar between patients with or without a hematoma, absent cisterns, or subarachnoid hemorrhage. Taken in combination, there is a gradation in risk that aligns with increasing numbers of any of these abnormalities. This information provides added value over age and GCS-P alone, supporting a simple extension of the earlier prognostic charts by stratifying the original charts in the following 3 CT groupings: none, only 1, and 2 or more CT abnormalities. CONCLUSIONS The important prognostic features in neurotrauma can be brought together to display graphically their combined effects on risks of death or on prospects for independent recovery. This approach can support decision making and improve communication of risk among health care professionals, patients, and their relatives. These charts will not replace clinical judgment, but they will reduce the risk of influences from biases.

Cranioplasty After Severe Traumatic Brain Injury: Effects of Trauma and Patient Recovery on Cranioplasty Outcome

Background

In patients with severe traumatic brain injury (sTBI) treated with decompressive craniectomy (DC), factors affecting the success of later cranioplasty are poorly known.

Objective

We sought to investigate if injury- and treatment-related factors, and state of recovery could predict the risk of major complications in cranioplasty requiring implant removal, and how these complications affect the outcome.

Methods

A retrospective cohort of 40 patients with DC following sTBI and subsequent cranioplasty was studied. Non-injury-related factors were compared with a reference population of 115 patients with DC due to other conditions.

Results

Outcome assessed 1 day before cranioplasty did not predict major complications leading to implant removal. Successful cranioplasty was associated with better outcome, whereas a major complication attenuates patient recovery: in patients with favorable outcome assessed 1 year after cranioplasty, major complication rate was 7%, while in patients with unfavorable outcome the rate was 42% (p = 0.003). Of patients with traumatic subarachnoid hemorrhage (tSAH) on admission imaging 30% developed a major complication, while none of patients without tSAH had a major complication (p = 0.014). Other imaging findings, age, admission Glasgow Coma Scale, extracranial injuries, length of stay at intensive care unit, cranioplasty materials, and timing of cranioplasty were not associated with major complications.

Conclusion

A successful cranioplasty after sTBI and DC predicts favorable outcome 1 year after cranioplasty, while stage of recovery before cranioplasty does not predict cranioplasty success or failure. tSAH on admission imaging is a major risk factor for a major complication leading to implant removal.

Temporal Trends in Functional Outcomes after Severe Traumatic Brain Injury: 2006-2015

Severe traumatic brain injury (TBI) is associated with poor outcomes; however, little is known about whether these outcomes are improving over time. This study examined temporal trends in functional outcomes of severe TBI at six months post-injury. We conducted a retrospective cohort study (January 1, 2006 to December 31, 2015) of hospitalized adult (≥16 years) patients with severe TBI using data from the population-based Victorian State Trauma Registry. The primary outcome was the Glasgow Outcome Scale-Extended (GOS-E) at six months post-injury, dichotomized as upper severe disability or worse (GOS-E ≤4, termed "unfavorable outcome") and lower moderate disability or better (GOS-E ≥5; termed "favorable outcome"). Multivariable logistic regression was used to investigate temporal trends in functional outcomes at six months post-injury. Of the 1966 patients with severe TBI who were followed up at six months post-injury (median age, 42 years (interquartile range [IQR]: 25-68); male, 73%), a majority of patients had an unfavorable outcome (GOS-E ≤4; n = 1372, 70%). After adjusting for confounders, there was no change in functional outcomes over time (adjusted odds ratio [AOR] = 1.02, 95% confidence interval [CI]: 0.98,1.06; p = 0.35). Similarly, there was no change in the adjusted odds of death (GOS-E = 1) at six months post-injury (AOR = 1.04, 95% CI: 1.00,1.08; p = 0.08). Using a population-wide, high quality, comprehensive registry, we demonstrated no change in death or functional outcomes after severe TBI between 2006 and 2015 in a mature trauma system. There is a clear need to identify targeted improvements in the treatment of these patients with the aim of reducing in-hospital death and improving long-term outcomes.

Assessment of Platelet Function in Traumatic Brain Injury-A Retrospective Observational Study in the Neuro-Critical Care Setting

BACKGROUND

Despite seemingly functional coagulation, hemorrhagic lesion progression is a common and devastating condition following traumatic brain injury (TBI), stressing the need for new diagnostic techniques. Multiple electrode aggregometry (MEA) measures platelet function and could aid in coagulopathy assessment following TBI. The aims of this study were to evaluate MEA temporal dynamics, influence of concomitant therapy, and its capabilities to predict lesion progression and clinical outcome in a TBI cohort.

MATERIAL AND METHODS

Adult TBI patients in a neurointensive care unit that underwent MEA sampling were retrospectively included. MEA was sampled if the patient was treated with antiplatelet therapy, bled heavily during surgery, or had abnormal baseline coagulation values. We assessed platelet activation pathways involving the arachidonic acid receptor (ASPI), P2Y12 receptor, and thrombin receptor (TRAP). ASPI was the primary focus of analysis. If several samples were obtained, they were included. Retrospective data were extracted from hospital charts. Outcome variables were radiologic hemorrhagic progression and Glasgow Outcome Scale assessed prospectively at 12 months posttrauma. MEA levels were compared between patients on antiplatelet therapy. Linear mixed effect models and uni-/multivariable regression models were used to study longitudinal dynamics, hemorrhagic progression and outcome, respectively.

RESULTS

In total, 178 patients were included (48% unfavorable outcome). ASPI levels increased from initially low values in a time-dependent fashion (p < 0.001). Patients on cyclooxygenase inhibitors demonstrated low ASPI levels (p < 0.001), while platelet transfusion increased them (p < 0.001). The first ASPI (p = 0.039) and TRAP (p = 0.009) were significant predictors of outcome, but not lesion progression, in univariate analyses. In multivariable analysis, MEA values were not independently correlated with outcome.

CONCLUSION

A general longitudinal trend of MEA is identified in this TBI cohort, even in patients without known antiplatelet therapies. Values appear also affected by platelet inhibitory treatment and by platelet transfusions. While significant in univariate models to predict outcome, MEA values did not independently correlate to outcome or lesion progression in multivariable analyses. Further prospective studies to monitor coagulation in TBI patients are warranted, in particular the interpretation of pathological MEA values in patients without antiplatelet therapies.

Efficacy of decompressive craniectomy in the management of intracranial pressure in severe traumatic brain injury

Traumatic brain injury (TBI) is a common cause of permanent disability for which clinical management remains suboptimal. Elevated intracranial pressure (ICP) is a common sequela following TBI leading to death and permanent disability if not properly managed. While clinicians often employ stepwise acute care algorithms to reduce ICP, a number of patients will fail medical management and may be considered for surgical decompression. Decompressive craniectomy (DC) involves removing a component of the bony skull to allow cerebral tissue expansion in order to reduce ICP. However, the impact of DC, which is performed in the setting of neurological instability, ongoing secondary injury, and patient resuscitation, has been challenging to study and outcomes are not well understood. This review summarizes historical and recent studies to elucidate indications for DC and the nuances, risks and complications in its application. The pathophysiology driving ICP elevation, and the corresponding medical interventions for their temporization and treatment, are thoroughly described. The current state of DC - including appropriate injury classification, surgical techniques, concurrent medical therapies, mortality and functional outcomes - is presented. We also report on the recent updates from large randomized controlled trials in severe TBI (Decompressive Craniectomy [DECRA] and Randomized Evaluation of Surgery with Craniectomy for Uncontrollable Elevation of ICP [RESCUEicp]), and recommendations for early DC to treat refractory ICP elevations in malignant middle cerebral artery syndrome. Limitations for DC, such as the equipoise between immediate reduction in ICP and clinically meaningful functional outcomes, are discussed in support of future investigations.

The Levels of Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase-L1 During the First Week After a Traumatic Brain Injury: Correlations With Clinical and Imaging Findings

BACKGROUND

Glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) are promising biomarkers of traumatic brain injury (TBI).

OBJECTIVE

We investigated the relation of the GFAP and UCH-L1 levels to the severity of TBI during the first week after injury.

METHODS

Plasma UCH-L1 and GFAP were measured from 324 consecutive patients with acute TBI and 81 control subject enrolled in a 2-center prospective study. The baseline measures included initial Glasgow Coma Scale (GCS), head computed tomographic (CT) scan at admission, and blood samples for protein biomarkers that were collected at admission and on days 1, 2, 3, and 7 after injury.

RESULTS

Plasma levels of GFAP and UCH-L1 during the first 2 days after the injury strongly correlated with the initial severity of TBI as assessed with GCS. Additionally, levels of UCH-L1 on the seventh day after the injury were significantly related to the admission GCS scores. At admission, both biomarkers were capable of distinguishing mass lesions from diffuse injuries in CT, and the area under the curve of the receiver-operating characteristic curve for prediction of any pathological finding in CT was 0.739 (95% confidence interval, 0.636-0.815) and 0.621 (95% confidence interval, 0.517-0.713) for GFAP and UCH-L1, respectively.

CONCLUSION

These results support the prior findings of the potential role of GFAP and UCH-L1 in acute-phase diagnostics of TBI. The novel finding is that levels of GFAP and UCH-L1 correlated with the initial severity of TBI during the first 2 days after the injury, thus enabling a window for TBI diagnostics with latency.

ABBREVIATIONS

AUC, area under the curveCI, confidence intervalED, emergency departmentGCS, Glasgow Coma ScaleGRAP, glial fibrillary acidic proteinIMPACT, International Mission for Prognosis and Clinical TrialROC, receiver-operating characteristicTBI, traumatic brain injuryTRACK-TBI, Transforming Research and Clinical Knowledge in Traumatic Brain InjuryUCH-L1, ubiquitin C-terminal hydrolase-L1.

The aggressiveness of neurotrauma practitioners and the influence of the IMPACT prognostic calculator

Published guidelines have helped to standardize the care of patients with traumatic brain injury; however, there remains substantial variation in the decision to pursue or withhold aggressive care. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic calculator offers the opportunity to study and decrease variability in physician aggressiveness. The authors wish to understand how IMPACT’s prognostic calculations currently influence patient care and to better understand physician aggressiveness. The authors conducted an anonymous international, multidisciplinary survey of practitioners who provide care to patients with traumatic brain injury. Questions were designed to determine current use rates of the IMPACT prognostic calculator and thresholds of age and risk for death or poor outcome that might cause practitioners to consider withholding aggressive care. Correlations between physician aggressiveness, putative predictors of aggressiveness, and demographics were examined. One hundred fifty-four responses were received, half of which were from physicians who were familiar with the IMPACT calculator. The most frequent use of the calculator was to improve communication with patients and their families. On average, respondents indicated that in patients older than 76 years or those with a >85% chance of death or poor outcome it might be reasonable to pursue non-aggressive care. These thresholds were robust and were not influenced by provider or institutional characteristics. This study demonstrates the need to educate physicians about the IMPACT prognostic calculator. The consensus values for age and prognosis identified in our study may be explored in future studies aimed at reducing variability in physician aggressiveness and should not serve as a basis for withdrawing care.

Volumetric analysis of day of injury computed tomography is associated with rehabilitation outcomes after traumatic brain injury

BACKGROUND

Day-of-injury (DOI) brain lesion volumes in traumatic brain injury (TBI) patients are rarely used to predict long-term outcomes in the acute setting. The purpose of this study was to investigate the relationship between acute brain injury lesion volume and rehabilitation outcomes in patients with TBI at a level one trauma center.

METHODS

Patients with TBI who were admitted to our rehabilitation unit after the acute care trauma service from February 2009-July 2011 were eligible for the study. Demographic data and outcome variables including cognitive and motor Functional Independence Measure (FIM) scores, length of stay (LOS) in the rehabilitation unit, and ability to return to home were obtained. The DOI quantitative injury lesion volumes and degree of midline shift were obtained from DOI brain computed tomography scans. A multiple stepwise regression model including 13 independent variables was created. This model was used to predict postrehabilitation outcomes, including FIM scores and ability to return to home. A p value less than 0.05 was considered significant.

RESULTS

Ninety-six patients were enrolled in the study. Mean age was 43 ± 21 years, admission Glasgow Coma Score was 8.4 ± 4.8, Injury Severity Score was 24.7 ± 9.9, and head Abbreviated Injury Scale score was 3.73 ± 0.97. Acute hospital LOS was 12.3 ± 8.9 days, and rehabilitation LOS was 15.9 ± 9.3 days. Day-of-injury TBI lesion volumes were inversely associated with cognitive FIM scores at rehabilitation admission (p = 0.004) and discharge (p = 0.004) and inversely associated with ability to be discharged to home after rehabilitation (p = 0.006).

CONCLUSION

In a cohort of patients with moderate to severe TBI requiring a rehabilitation unit stay after the acute care hospital stay, DOI brain injury lesion volumes are associated with worse cognitive FIM scores at the time of rehabilitation admission and discharge. Smaller-injury volumes were associated with eventual discharge to home. Volumetric neuroimaging in the acute injury phase may improve surgeons' ultimate outcome predictions in TBI patients.

LEVEL OF EVIDENCE

Prognostic/epidemiologic study, level V.

Mortality Risk Stratification After Traumatic Brain Injury and Hazard of Death With Titrated Hypothermia in the Eurotherm3235Trial

Supplemental Digital Content is available in the text.

Objectives:

Hypothermia reduces intracranial hypertension in patients with traumatic brain injury but was associated with harm in the Eurotherm3235Trial. We stratified trial patients by International Mission for Prognosis and Analysis of Clinical Trials in [Traumatic Brain Injury] (IMPACT) extended model sum scores to determine where the balance of risks lay with the intervention.

Design:

The Eurotherm3235Trial was a randomized controlled trial, with standardized and blinded outcome assessment. Patients in the trial were split into risk tertiles by IMPACT extended model sum scores. A proportional hazard analysis for death between randomization and 6 months was performed by intervention and IMPACT extended model sum scores tertiles in both the intention-to-treat and the per-protocol populations of the Eurotherm3235Trial.

Setting:

Forty-seven neurologic critical care units in 18 countries.

Patients:

Adult traumatic brain injury patients admitted to intensive care who had suffered a primary, closed traumatic brain injury; increased intracranial pressure; an initial head injury less than 10 days earlier; a core temperature at least 36°C; and an abnormal brain CT.

Intervention:

Titrated Hypothermia in the range 32-35°C as the primary intervention to reduce raised intracranial pressure.

Measurements and Main Results:

Three hundred eighty-six patients were available for analysis in the intention-to-treat and 257 in the per-protocol population. The proportional hazard analysis (intention-to-treat and per-protocol populations) showed that the treatment effect behaves similarly across all risk stratums. However, there is a trend that indicates that patients in the low-risk group could be at greater risk of suffering harm due to hypothermia.

Conclusions:

Hypothermia as a first line measure to reduce intracranial pressure to less than 20 mm Hg is harmful in patients with a lower severity of injury and no clear benefit exists in patients with more severe injuries.

Predictors of improved functional outcome following inpatient rehabilitation for patients with traumatic brain injury

OBJECTIVE

To determine factors associated with response to inpatient rehabilitation treatment among TBI patients.

SETTING

Inpatient rehabilitation service at a Level I trauma center.

PARTICIPANTS

Moderate-severe TBI patients ages ≥ 18years old admitted between January 1, 2002 and December 31, 2012.

MAIN MEASURES

Response to inpatient rehabilitation, measured by the Functional Independence Measure (FIM) score.

DESIGN

Retrospective cohort study.

RESULTS

Of 1,984 patients treated for TBI, 184 (10.8%) underwent inpatient rehabilitation. The largest proportion of patients improved in mobility (98.9%), followed by self-care (93.7%), communication/social cognition (84.0%), and sphincter control (65.7%). Of these, 99 (53.8%) improved by 2 or more levels of functional independence and were considered rehabilitation responders. Responders were younger (53.1 years vs. 63.8, p < 0.01), had longer average rehabilitation stays (15.4 days vs. 12.2, p < 0.01), and were less likely to have an admission SBP <100 mmHg (7.1% vs. 17.1%, p = 0.01). On multivariate analysis, normotension at admission (AOR 0.06, p = 0.01) and longer rehabilitation LOS (AOR 1.11, p < 0.01) were associated with a response to inpatient rehabilitation.

CONCLUSION

Of the TBI patients who qualified for same-center inpatient rehabilitation, approximately half responded to treatment. Longer rehabilitation time and normotension at admission predicted response to rehabilitation. Further efforts are necessary to identify and optimize TBI patients for inpatient rehabilitation.

Informatics in neurocritical care: new ideas for Big Data

PURPOSE OF REVIEW

Big data is the new hype in business and healthcare. Data storage and processing has become cheap, fast, and easy. Business analysts and scientists are trying to design methods to mine these data for hidden knowledge. Neurocritical care is a field that typically produces large amounts of patient-related data, and these data are increasingly being digitized and stored. This review will try to look beyond the hype, and focus on possible applications in neurointensive care amenable to Big Data research that can potentially improve patient care.

RECENT FINDINGS

The first challenge in Big Data research will be the development of large, multicenter, and high-quality databases. These databases could be used to further investigate recent findings from mathematical models, developed in smaller datasets. Randomized clinical trials and Big Data research are complementary. Big Data research might be used to identify subgroups of patients that could benefit most from a certain intervention, or can be an alternative in areas where randomized clinical trials are not possible.

SUMMARY

The processing and the analysis of the large amount of patient-related information stored in clinical databases is beyond normal human cognitive ability. Big Data research applications have the potential to discover new medical knowledge, and improve care in the neurointensive care unit.

Data Publications Correlate with Citation Impact

Neuroscience and molecular biology have been generating large datasets over the past years that are reshaping how research is being conducted. In their wake, open data sharing has been singled out as a major challenge for the future of research. We conducted a comparative study of citations of data publications in both fields, showing that the average publication tagged with a data-related term by the NCBI MeSH (Medical Subject Headings) curators achieves a significantly larger citation impact than the average in either field. We introduce a new metric, the data article citation index (DAC-index), to identify the most prolific authors among those data-related publications. The study is fully reproducible from an executable Rmd (R Markdown) script together with all the citation datasets. We hope these results can encourage authors to more openly publish their data.

Pharmacologic Neuroprotection for Functional Outcomes After Traumatic Brain Injury: A Systematic Review of the Clinical Literature

INTRODUCTION

Traumatic brain injury (TBI) is a major cause of death and disability worldwide. The deleterious effects of secondary brain injury may be attenuated by early pharmacological therapy in the emergency room and intensive care unit (ICU). Current medical management of acute TBI is primarily supportive, aimed at reducing intracranial pressure (ICP) and optimizing cerebral perfusion. There are no pharmacological therapies to date that have been unequivocally demonstrated to improve neurological outcomes after TBI.

OBJECTIVES

The purpose of this systematic review was to evaluate the recent clinical studies from January 2013 through November 2015 that investigated neuroprotective functional outcomes of pharmacological agents after TBI.

METHODS

The following databases were searched for relevant studies: MEDLINE (OvidSP January Week 1, 2013-November Week 2 2015), Embase (OvidSP 2013 January 1-2015 November 24), and the unindexed material in PubMed (National Library of Medicine/National Institutes of Health [NLM/NIH]). This systematic review included only full-length clinical studies and case series that included at least five patients and were published in the English language. Only studies that examined functional clinical outcomes were included.

RESULTS

Twenty-five of 527 studies met our inclusion criteria, which investigated 15 independent pharmacological therapies. Eight of these therapies demonstrated possible neuroprotective properties and improved functional outcomes, of which five were investigated with randomized clinical trials: statins, N-acetyl cysteine (NAC), Enzogenol, Cerebrolysin, and nitric oxide synthase inhibitor (VAS203). Three pharmacological agents did not demonstrate neuroprotective effects, and four agents had mixed results.

CONCLUSIONS

While there is currently no single pharmacological therapy that will unequivocally improve clinical outcomes after TBI, several agents have demonstrated promising clinical benefits for specific TBI patients and should be investigated further.

Past, Present, and Future of Traumatic Brain Injury Research

Traumatic brain injury (TBI) is the greatest cause of death and severe disability in young adults; its incidence is increasing in the elderly and in the developing world. Outcome from severe TBI has improved dramatically as a result of advancements in trauma systems and supportive critical care, however we remain without a therapeutic which acts directly to attenuate brain injury. Recognition of secondary injury and its molecular mediators has raised hopes for such targeted treatments. Unfortunately, over 30 late-phase clinical trials investigating promising agents have failed to translate a therapeutic for clinical use. Numerous explanations for this failure have been postulated and are reviewed here. With this historical context we review ongoing research and anticipated future trends which are armed with lessons from past trials, new scientific advances, as well as improved research infrastructure and funding. There is great hope that these new efforts will finally lead to an effective therapeutic for TBI as well as better clinical management strategies.

Effectiveness of a Very Early Stepping Verticalization Protocol in Severe Acquired Brain Injured Patients: A Randomized Pilot Study in ICU

BACKGROUND AND OBJECTIVE

Verticalization was reported to improve the level of arousal and awareness in patients with severe acquired brain injury (ABI) and to be safe in ICU. We evaluated the effectiveness of a very early stepping verticalization protocol on their functional and neurological outcome.

METHODS

Consecutive patients with Vegetative State or Minimally Conscious State were enrolled in ICU on the third day after an ABI. They were randomized to undergo conventional physiotherapy alone or associated to fifteen 30-minute sessions of verticalization, using a tilt table with robotic stepping device. Once stabilized, patients were transferred to our Neurorehabilitation unit for an individualized treatment. Outcome measures (Glasgow Coma Scale, Coma Recovery Scale revised -CRSr-, Disability Rating Scale-DRS- and Levels of Cognitive Functioning) were assessed on the third day from the injury (T0), at ICU discharge (T1) and at Rehab discharge (T2). Between- and within-group comparisons were performed by the Mann-Whitney U test and Wilcoxon signed-rank test, respectively.

RESULTS

Of the 40 patients enrolled, 31 completed the study without adverse events (15 in the verticalization group and 16 in the conventional physiotherapy). Early verticalization started 12.4±7.3 (mean±SD) days after ABI. The length of stay in ICU was longer for the verticalization group (38.8 ± 15.7 vs 25.1 ± 11.2 days, p = 0.01), while the total length of stay (ICU+Neurorehabilitation) was not significantly different (153.2 ± 59.6 vs 134.0 ± 61.0 days, p = 0.41). All outcome measures significantly improved in both groups after the overall period (T2 vs T0, p<0.001 all), as well as after ICU stay (T1 vs T0, p<0.004 all) and after Neurorehabilitation (T2 vs T1, p<0.004 all). The improvement was significantly better in the experimental group for CRSr (T2-T0 p = 0.033, T1-T0 p = 0.006) and (borderline) for DRS (T2-T0 p = 0.040, T1-T0 p = 0.058).

CONCLUSIONS

A stepping verticalization protocol, started since the acute stages, improves the short-term and long-term functional and neurological outcome of ABI patients.

TRIAL REGISTRATION

clinicaltrials.gov NCT02828371.

Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis

Background

Traumatic brain injury remains a global health problem. Understanding the relative importance of outcome predictors helps optimize our treatment strategies by informing assessment protocols, clinical decisions and trial designs. In this study we establish importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models. We then explore the associations between key outcome predictors using Bayesian networks to gain further insight into predictor importance.

Methods

We analyzed the corticosteroid randomization after significant head injury (CRASH) trial database of 10008 patients and included patients for whom demographics, injury characteristics, computer tomography (CT) findings and Glasgow Outcome Scale (GCS) were recorded (total of 13 predictors, which would be available to clinicians within a few hours following the injury in 6945 patients). Predictions of clinical outcome (death or severe disability at 6 months) were performed using logistic regression models with 5-fold cross validation. Predictive performance was measured using standardized partial area (pAUC) under the receiver operating curve (ROC) and we used Delong test for comparisons. Variable importance ranking was based on pAUC targeted at specificity (pAUC_SP) and sensitivity (pAUC_SE) intervals of 90–100%. Probabilistic associations were depicted using Bayesian networks.

Results

Complete AUC analysis showed very good predictive power (AUC = 0.8237, 95% CI: 0.8138–0.8336) for the complete model. Specificity focused importance ranking highlighted age, pupillary, motor responses, obliteration of basal cisterns/3rd ventricle and midline shift. Interestingly when targeting model sensitivity, the highest-ranking variables were age, severe extracranial injury, verbal response, hematoma on CT and motor response. Simplified models, which included only these key predictors, had similar performance (pAUC_SP = 0.6523, 95% CI: 0.6402–0.6641 and pAUC_SE = 0.6332, 95% CI: 0.62–0.6477) compared to the complete models (pAUC_SP = 0.6664, 95% CI: 0.6543–0.679, pAUC_SE = 0.6436, 95% CI: 0.6289–0.6585, de Long p value 0.1165 and 0.3448 respectively). Bayesian networks showed the predictors that did not feature in the simplified models were associated with those that did.

Conclusion

We demonstrate that importance based variable selection allows simplified predictive models to be created while maintaining prediction accuracy. Variable selection targeting specificity confirmed key components of clinical assessment in TBI whereas sensitivity based ranking suggested extracranial injury as one of the important predictors. These results help refine our approach to head injury assessment, decision-making and outcome prediction targeted at model sensitivity and specificity. Bayesian networks proved to be a comprehensive tool for depicting probabilistic associations for key predictors giving insight into why the simplified model has maintained accuracy.

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury

BACKGROUND AND OBJECTIVE

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity.

METHODS

We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models.

RESULTS

For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10).

CONCLUSION

In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial.

External Validation of the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury: Prognostic Models for Traumatic Brain Injury on the Study of the Neuroprotective Activity of Progesterone in Severe Traumatic Brain Injuries Trial

Prediction models for patients with traumatic brain injury (TBI) are important for multiple reasons, including case-mix adjustment, trial design, and benchmarking for quality-of-care evaluation. Models should be generalizable and therefore require regular external validation. We aimed to validate the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic models for moderate and severe TBI in a recent randomized controlled trial. We studied 1124 patients enrolled in the multi-center randomized placebo-controlled Study of the Neuroprotective Activity of Progesterone in Severe Traumatic Brain Injuries (SyNAPSe) trial that evaluated the efficacy of progesterone in TBI. Treatment and placebo groups were combined for analysis. We evaluated the predictive performance of the three prognostic models (core, extended, and lab) from the IMPACT study with regard to discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (comparison of observed to predicted risks). Substantial differences were found in case-mix and outcome distribution between IMPACT and SyNAPSe. In line with the more homogeneous case-mix of a clinical trial, the discriminative performance was reasonable. For the core model, an AUC of 0.677 and 0.684 was obtained for 6-month mortality and unfavorable outcome, respectively. Performance was slightly better for the extended model (0.693 and 0.705) and for the lab model (0.689 and 0.711, respectively). For calibration, we found overestimation of mortality, especially at higher risk predictions, and underestimation of unfavorable outcome, especially at lower risk predictions. This pattern of miscalibration was consistent across all three models. In a contemporary trial setting, the IMPACT models have reasonable discrimination if enrollment restrictions apply. Observed changes in outcome distribution necessitate updating of previously developed prognostic models.

Predicting outcome in traumatic brain injury: Sharing experience of pilot traumatic brain injury registry

Background:

A reliable prediction of outcome for the victims of traumatic brain injury (TBI) on admission is possible from concurrent data analysis from any systematic real-time registry.

Objective:

To determine the clinical relevance of the findings from our TBI registry to develop prognostic futuristic models with readily available traditional and novel predictors.

Materials and Methods:

Prospectively collected data using predesigned pro forma were analyzed from the first phase of a trauma registry from a South Indian Trauma Centre, compatible with computerized management system at electronic data entry and web data entry interface on demographics, clinical, management, and discharge status.

Statistical Analysis:

On univariate analysis, the variables with P < 0.15 were chosen for binary logistic model. On regression model, variables were selected with test of coefficient 0.001 and with Nagelkerke R² with alpha error of 5%.

Results:

From 337 cases, predominantly males from rural areas in their productive age, road traffic injuries accounted for two-thirds cases, one-fourths occurred during postmonsoon while two-wheeler was the most common prerequisite. Fifty percent of patients had moderate to severe brain injury; the most common finding was unconsciousness followed by vomiting, ear bleed, seizures, and traumatic amnesia. Fifteen percent required intracranial surgery. Patients with severe Glasgow coma scale score were 4.5 times likely to have the fatal outcome (P = 0.003). Other important clinical variables accountable for fatal outcomes were oral bleeds and cervical spine injury while imperative socio-demographic risk correlates were age and seasons.

Conclusion:

TBI registry helped us finding predictors of clinical relevance for the outcomes in victims of TBI in search of prognostic futuristic models in TBI victims.

Predictors of Outcomes in Traumatic Brain Injury

INTRODUCTION

The purpose of this study was to retrospectively evaluate patients treated for traumatic brain injuries (TBI) to determine how multiple organ trauma (MOT) and lung injuries sustained at the time of initial injury affect outcome.

METHODS

A single institution retrospective review of all patients diagnosed with TBI at a level I trauma center from 2000 to 2014 was conducted. Clinical outcome was based on Glasgow Outcome Scale at hospital discharge. Lung injury was defined as the presence of pulmonary contusions, pneumothorax, hemothorax, rib fractures, or diaphragmatic rupture proven by x-ray or computed tomography scan. MOT was defined as trauma to one body region with an Abbreviated Injury Scale (AIS) score ≥3 plus trauma to 2 additional body regions with AIS scores ≥1. Regression analysis was conducted with SPSS 21.

RESULTS

There were 409 patients reviewed. The majority of patients were male (73%), average age was 46 years (range, 16-94 years), average Glasgow Coma Scale (GCS) score was 7, and 71% had a severe TBI (GCS ≤8). Thirty percent of patients had poor outcome (Glasgow Outcome Scale = 1-2) Regression analysis indicated age (odds ratio [OR] 1.03, P < 0.001), initial GCS (OR 0.88, P < 0.001), Injury Severity Score (OR 1.03, P = 0.021), and head AIS ≥5 (OR 0.55, P = 0.019) were significant independent predictors of poor outcome. Sex, MOT, lung injury, and lung injury severity were not significant predictors of outcome.

CONCLUSIONS

Age, GCS, Injury Severity Score, and critical head injuries (AIS ≥5) were significant tools in predicting outcome in this patient cohort. MOT and traumatic lung injury may cause significant damage to a patient suffering from a severe TBI, but these injuries do not predict mortality in this patient population.

Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic) (age, GCS score, and pupil reactivity to light), as well as with additional CT findings (CRASH CT). Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7) years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR) for mortality was 2.65. Unfavorable outcome (GOSE < 5) was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI.

Contrecoup Traumatic Intracerebral Hemorrhage: A Geometric Study of the Impact Site and Association with Hemorrhagic Progression

Traumatic intracerebral hemorrhage (TICH) represents 13-48% of the lesions after a traumatic brain injury (TBI). The frequency of TICH-hemorrhagic progression (TICH-HP) is estimated to be approximately 38-63%. The relationship between the impact site and TICH location has been described in many autopsy-based series. This association, however, has not been consistently demonstrated since the introduction of computed tomography (CT) for studying TBI. This study aimed to determine the association between the impact site and TICH location in patients with moderate and severe TBI. We also analyzed the associations between the TICH location, the impact site, the production mechanism (coup or contrecoup), and hemorrhagic progression. We retrospectively analyzed the records of 408 patients after a moderate or severe TBI between January 2010 and November 2014. We identified 177 patients with a total of 369 TICHs. We found a statistically significant association between frontal TICHs and impact sites located on the anterior area of the head (OR 5.8, p < 0.001). The temporal TICH location was significantly associated with impact sites located on the posterior head area (OR 4.9, p < 0.001). Anterior and lateral TICHs were associated with impact sites located at less than 90 degrees (coup) (OR 1.64, p = 0.03) and more than 90 degrees (contrecoup), respectively. Factors independently associated with TICH-HP obtained through logistic regression included an initial volume of <1 cc, cisternal compression, falls, acute subdural hematoma, multiple TICHs, and contrecoup TICHs. We demonstrated a significant association between the TICH location and impact site. The contrecoup represents a risk factor independently associated with hemorrhagic progression.

Analysis of long-term (median 10.5 years) outcomes in children presenting with traumatic brain injury and an initial Glasgow Coma Scale score of 3 or 4

OBJECT

Patients with traumatic brain injury (TBI) with low presenting Glasgow Coma Scale (GCS) scores have very high morbidity and mortality rates. Neurosurgeons may be faced with difficult decisions in managing the most severely injured (GCS scores of 3 or 4) patients. The situation may be considered hopeless, with little chance of a functional recovery. Long-term data are limited regarding the clinical outcome of children with severe head injury. The authors evaluate predictor variables and the clinical outcomes at discharge, 1 year, and long term (median 10.5 years) in a cohort of children with TBI presenting with postresuscitation GCS scores of 3 and 4.

METHODS

A review of a prospectively collected trauma database was performed. Patients treated at Riley Hospital for Children (Indianapolis, Indiana) from 1988 to 2004 were reviewed. All children with initial GCS (modified for pediatric patients) scores of 3 or 4 were identified. Patients with a GCS score of 3 were compared with those with a GCS score of 4. The outcomes of all patients at the time of death or discharge and at 1-year and long-term follow-up were measured with a modified Glasgow Outcome Scale (GOS) that included a "normal" outcome. Long-term outcomes were evaluated by contacting surviving patients. Statistical "classification trees" were formed for survival and outcome, based on predictor variables.

RESULTS

Sixty-seven patients with a GCS score of 3 or 4 were identified in a database of 1636 patients (4.1%). Three of the presenting factors differed between the GCS 3 patients (n = 44) and the GCS 4 patients (n = 23): presence of hypoxia, single seizure, and open basilar cisterns on CT scan. The clinical outcomes were statistically similar between the 2 groups. In total, 48 (71.6%) of 67 patients died, remained vegetative, or were severely disabled by 1 year. Eight patients (11.9%) were normal at 1 year. Ten of the 22 patients with long-term follow-up were either normal or had a GOS score of 5. Multiple clinical, historical, and radiological factors were analyzed for correlation with survival and clinical outcome. Classification trees were formed to stratify predictive factors. The pupillary response was the factor most predictive of both survival and outcome. Other factors that either positively or negatively correlated with survival included hypothermia, mechanism of injury (abuse), hypotension, major concurrent symptoms, and midline shift on CT scan. Other factors that either positively or negatively predicted long-term outcome included hypothermia, mechanism of injury, and the assessment of the fontanelle.

CONCLUSIONS

In this cohort of 67 TBI patients with a presenting GCS score of 3 or 4, 56.6% died within 1 year. However, approximately 15% of patients had a good outcome at 10 or more years. Factors that correlated with survival and outcome included the pupillary response, hypothermia, and mechanism. The authors discuss factors that may help surgeons make critical decisions regarding their most serious pediatric trauma patients.

Osteoporosis Self-Assessment Tool for Asians Can Predict Neurologic Prognosis in Patients with Isolated Moderate Traumatic Brain Injury

Objectives

Osteoporosis Self-Assessment Tool for Asians (OSTA) has been proved to be a simple and effective tool for recognizing osteoporosis risk. Our previous study has demonstrated that the preoperative OSTA index was a good prognostic predictor for stage II and III colon cancer patients after surgery. We aim to evaluate the value of OSTA index in prognostication of isolated traumatic brain injury with moderate severity (GCS 9-13).

Methods

We retrospectively reviewed all patients visiting Kaohsiung Medical University Hospital emergency department due to isolated moderate traumatic brain injury from Jan. 2010 to Dec. 2012. Background data (including the OSTA index), clinical presentations, management and outcomes (ICU admission days, total admission days, complications, Glasgow outcome score (GOS) at discharge, mortality) of the patients were recorded for further analysis. Our major outcome was good neurologic recovery defined as GOS of 5. Pearson chi-square test and the Mann-Whitney U test were used to compare demographic features. Multiple logistic regression was used to identify independent risk factors.

Results

107 isolated moderate TBI patients were studied. 40 patients (37.4%) showed good recovery and 10 (9.3%) died at discharge. The univariate analysis revealed that younger age, higher OSTA index, lower ISS, lower AIS-H, and avoidance to neurosurgery were associated with better neurologic outcome for all moderate TBI patients. Multivariate analysis revealed that lower ISS, higher OSTA, and the avoidance of neurosurgery were independent risk factors predicting good neurologic recovery.

Conclusion

Higher ISS, lower OSTA index and exposure to neurosurgery were the independent risk factors for poorer recovery from isolated moderate TBI. In addition to labeling the cohort harboring osteoporotic risk, OSTA index could predict neurologic prognosis in patients with isolated moderate traumatic brain injury.

Imaging in Chronic Traumatic Encephalopathy and Traumatic Brain Injury

Context:

The diagnosis of chronic traumatic encephalopathy (CTE) can only be made pathologically, and there is no concordance of defined clinical criteria for premorbid diagnosis. The absence of established criteria and the insufficient imaging findings to detect this disease in a living athlete are of growing concern.

Evidence Acquisition:

The article is a review of the current literature on CTE. Databases searched include Medline, PubMed, JAMA evidence, and evidence-based medicine guidelines Cochrane Library, Hospital for Special Surgery, and Cornell Library databases.

Study Design:

Clinical review.

Level of Evidence:

Level 4.

Results:

Chronic traumatic encephalopathy cannot be diagnosed on imaging. Examples of imaging findings in common types of head trauma are discussed.

Conclusion:

Further study is necessary to correlate the clinical and imaging findings of repetitive head injuries with the pathologic diagnosis of CTE.

Traumatic Intracerebral Hemorrhage: Risk Factors Associated with Progression

The increase in the volume of a traumatic intracerebral hemorrhage (TICH) is a widely studied phenomenon that has a direct impact on the prognosis of patients. The objective of this study was to identify the risk factors associated with the progression of TICH. We retrospectively analyzed the records of 1970 adult patients >15 years of age who were consecutively admitted after sustaining a closed severe traumatic brain injury (TBI) between January 1987 and November 2013 at a single center. Beginning in 2007, patients with moderate TBIs were also included. A total of 782 patients exhibited one or more TICH on the initial CT scan, and met the selection criteria. The main outcome variable was the presence or absence of progression of the TICH. Univariate and multivariate statistical analyses were performed. Factors independently associated with the growth of TICH obtained through logistic regression included the following: an initial volume <5 cc (odds ratio [OR] 2.42, p<0.001), cisternal compression (OR 1.95, p<0.001), decompressive craniectomy (OR 2.18, p<0.001), age (mean 37.67 vs. 42.95 years; OR 1.01, p<0.001), falls as mechanism of trauma (OR 1.72, p=0.001), multiple TICHs (OR 1.56, p=0.007), and hypoxia (OR 1.56, p=0.02). TICH progression occurred with a frequency of 63% in our study. We showed that there was a correlation between TICH growth and some variables, such as multiple TICHs, a lower initial volume, acute subdural hematoma, cisternal compression, older patient age, hypoxia, falls, and decompressive craniectomy.

Temporal trends in surgical intervention for severe traumatic brain injury caused by extra-axial hemorrhage, 1995 to 2012

BACKGROUND

Surgical intervention for severe traumatic brain injury (TBI) caused by extra-axial hemorrhage has declined in recent decades. The effect of this change on patient outcomes is unknown.

OBJECTIVE

To determine the change over time in surgical intervention in this population and to assess changes in patient outcomes.

METHODS

In this retrospective cohort study, the Washington State Trauma Registry was queried from 1995 to 2012 for patients with extra-axial hemorrhage and head Abbreviated Injury Scale score of 3 to 5. Data were linked to the state-wide death registry to analyze long-term mortality. The primary outcome was inpatient mortality. Secondary outcomes included 6- and 12-month mortality and modified Functional Independence Measure at discharge. Multivariable analyses were completed for all outcomes.

RESULTS

A total of 22974 patients met inclusion criteria. Over the study period, surgical intervention for severe TBI declined from 36% to 7%. There was a decline in case fatality from 22% to 12%. In 2012, the relative risk of inpatient mortality was 23% lower compared with 1995 (adjusted mortality risk ratio, 0.77; 95% confidence interval, 0.63-0.94). Changes in 6- and 12-month adjusted mortality and modified Functional Independence Measure were not statistically significant.

CONCLUSION

The decline in surgical intervention for severe TBI caused by extra-axial hemorrhage in Washington State was ubiquitous across regional, demographic, and injury characteristic strata. There was concurrently a reduction in inpatient mortality in this population. Functional status and long-term mortality, however, have remained the same. Future studies are needed to better identify modifiable risk factors for improvement in functional status and long-term mortality in this population.

An experimental study: does the neuroprotective effect increase when hypothermia deepens after traumatic brain injury?

BACKGROUND

Experimental approaches have been promising with the use of therapeutic hypothermia after Traumatic Brain Injury (TBI) whereas clinical data have not supported its efficacy.

OBJECTIVES

This study aimed to investigate whether using selective deeper brain cooling correlates with a more neuroprotective effect on Intracranial Pressure (ICP) increments following TBI in rats.

MATERIALS AND METHODS

Adult male Sprague-Dawley rats (mean weight = 300 g; n = 25) were subjected to brain injury using a modified Marmarou method. Immediately after the onset of TBI, rats were randomized into three groups. Selective brain cooling was applied around the head using ice packages. Intracranial Temperature (ICT) and ICP were continuously measured at 0, 30, 60, 120, and 180 minutes and recorded for all groups. Group 1 (n = 5) was normothermia and was assigned as the control group. Group 2 (n = 10) received moderate hypothermia with a target ICT of between 32°C - 33°C and Group 3 (n = 10) was given a deeper hypothermia with a target ICT of below 32°C.

RESULTS

All subjects reached the target ICT by the 30th minute of hypothermia induction. The ICT was significantly different in Group 2 compared to Group 1 only at the 120th minute (P = 0.017), while ICP was significantly lower starting from the 30th minute (P = 0.015). The ICT was significantly lower in Group 3 compared to Groups 1 and 2 starting from the 30th minute (P = 0.001 and P = 0.003, respectively). The ICP was significantly lower in Group 3 compared to Group 1 starting from 30th minute (P = 0.001); however, a significant difference in ICP between Group 3 and Group 2 was observed only at the 180th minute (P = 0.047).

CONCLUSIONS

Results of this study indicate that selective brain cooling is an effective method of decreasing ICP in rats; however, the deeper hypothermia caused a greater decrease in ICP three hours after hypothermia induction.

Classification of traumatic brain injury: past, present, and future

Disease classification is central to the practice of medicine; it systematizes clinical knowledge and experience. Classification is essential for diagnosis and effective treatment of human disease. Progress in classifying traumatic brain injury (TBI) for targeted treatment has lagged behind other diseases such as cancer, and has contributed to a lack of progress in the field. Today TBI is most frequently classified as mild, moderate, or severe using the Glasgow Coma Scale (GCS). However, the GCS is symptoms-based and does not allow for targeting of specific pathology. Here we review general schemas for disease classification and how they have evolved over time. We discuss the characteristics of an ideal classification system and the unique challenges inherent to achieving such a system for TBI. Current means of classifying TBI are reviewed, as are the strengths and limitations of these approaches. Generating the data required to modernize TBI classification and to perhaps facilitate a targeted, precision medicine approach to its management will require a highly collaborative international effort. Fortunately these efforts are underway and will benefit from the lessons and tools that have come from other areas of medicine that have already found success with this approach.

Recent developments in clinical trials for the treatment of traumatic brain injury

The clinical understanding of traumatic brain injury (TBI) and its manifestations is beginning to change. Both clinicians and research scientists are recognizing that TBI and related disorders such as stroke are complex, systemic inflammatory and degenerative diseases that require an approach to treatment more sophisticated than targeting a single gene, receptor, or signaling pathway. It is becoming increasingly clear that TBI is a form of degenerative disorder affecting the brain and other organs, and that its manifestations can unfold days, weeks, and years after the initial damage. Until recently, and despite numerous industry- and government-sponsored clinical trials, attempts to find a safe and effective neuroprotective agent have all failed - probably because the research and development strategies have been based on an outdated early 20th century paradigm seeking a magic bullet that will affect a narrowly circumscribed target. We propose that more attention be given to the development of drugs, given alone or in combination, that are pleiotropic in their actions and that have systemic as well as central nervous system effects. We review current Phase II and Phase III trials for acute pharmacologic treatments for TBI and report on their aims, methods, status, and important associated research issues.

Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

BACKGROUND

Modern modelling techniques may potentially provide more accurate predictions of binary outcomes than classical techniques. We aimed to study the predictive performance of different modelling techniques in relation to the effective sample size ("data hungriness").

METHODS

We performed simulation studies based on three clinical cohorts: 1282 patients with head and neck cancer (with 46.9% 5 year survival), 1731 patients with traumatic brain injury (22.3% 6 month mortality) and 3181 patients with minor head injury (7.6% with CT scan abnormalities). We compared three relatively modern modelling techniques: support vector machines (SVM), neural nets (NN), and random forests (RF) and two classical techniques: logistic regression (LR) and classification and regression trees (CART). We created three large artificial databases with 20 fold, 10 fold and 6 fold replication of subjects, where we generated dichotomous outcomes according to different underlying models. We applied each modelling technique to increasingly larger development parts (100 repetitions). The area under the ROC-curve (AUC) indicated the performance of each model in the development part and in an independent validation part. Data hungriness was defined by plateauing of AUC and small optimism (difference between the mean apparent AUC and the mean validated AUC <0.01).

RESULTS

We found that a stable AUC was reached by LR at approximately 20 to 50 events per variable, followed by CART, SVM, NN and RF models. Optimism decreased with increasing sample sizes and the same ranking of techniques. The RF, SVM and NN models showed instability and a high optimism even with >200 events per variable.

CONCLUSIONS

Modern modelling techniques such as SVM, NN and RF may need over 10 times as many events per variable to achieve a stable AUC and a small optimism than classical modelling techniques such as LR. This implies that such modern techniques should only be used in medical prediction problems if very large data sets are available.

Big data from small data: data-sharing in the 'long tail' of neuroscience

The launch of the US BRAIN and European Human Brain Projects coincides with growing international efforts toward transparency and increased access to publicly funded research in the neurosciences. The need for data-sharing standards and neuroinformatics infrastructure is more pressing than ever. However, 'big science' efforts are not the only drivers of data-sharing needs, as neuroscientists across the full spectrum of research grapple with the overwhelming volume of data being generated daily and a scientific environment that is increasingly focused on collaboration. In this commentary, we consider the issue of sharing of the richly diverse and heterogeneous small data sets produced by individual neuroscientists, so-called long-tail data. We consider the utility of these data, the diversity of repositories and options available for sharing such data, and emerging best practices. We provide use cases in which aggregating and mining diverse long-tail data convert numerous small data sources into big data for improved knowledge about neuroscience-related disorders.

Predicting outcome after traumatic brain injury: development of prognostic scores based on the IMPACT and the APACHE II

Prediction models are important tools for heterogeneity adjustment in clinical trials and for the evaluation of quality of delivered care to patients with traumatic brain injury (TBI). We sought to improve the predictive performance of the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials) prognostic model by combining it with the APACHE II (Acute Physiology and Chronic Health Evaluation II) for 6-month outcome prediction in patients with TBI treated in the intensive care unit. A total of 890 patients with TBI admitted to a large urban level 1 trauma center in 2009-2012 comprised the study population. The IMPACT and the APACHE II scores were combined using binary logistic regression. A randomized, split-sample technique with secondary bootstrapping was used for model development and internal validation. Model performance was assessed by discrimination (by area under the curve [AUC]), calibration, precision, and net reclassification improvement (NRI). Overall 6-month mortality was 22% and unfavorable neurological outcome 47%. The predictive power of the new combined IMPACT-APACHE II models was significantly superior, compared to the original IMPACT models (AUC, 0.81-0.82 vs. 0.84-0.85; p<0.05) for 6-month mortality prediction, but not for unfavorable outcome prediction (AUC, 0.81-0.82 vs. 0.83; p>0.05). However, NRI showed a significant improvement in risk stratification of patients with unfavorable outcome by the IMPACT-APACHE II models, compared to the original models (NRI, 5.4-23.2%; p<0.05). Internal validation using split-sample and resample bootstrap techniques yielded equivalent results, indicating low grade of overestimation. Our findings show that by combining the APACHE II with the IMPACT, improved 6-month outcome predictive performance is achieved. This may be applicable for heterogeneity adjustment in forthcoming TBI studies.

Development of a database for translational spinal cord injury research

Efforts to understand spinal cord injury (SCI) and other complex neurotrauma disorders at the pre-clinical level have shown progress in recent years. However, successful translation of basic research into clinical practice has been slow, partly because of the large, heterogeneous data sets involved. In this sense, translational neurological research represents a "big data" problem. In an effort to expedite translation of pre-clinical knowledge into standards of patient care for SCI, we describe the development of a novel database for translational neurotrauma research known as Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI). We present demographics, descriptive statistics, and translational syndromic outcomes derived from our ongoing efforts to build a multi-center, multi-species pre-clinical database for SCI models. We leveraged archived surgical records, postoperative care logs, behavioral outcome measures, and histopathology from approximately 3000 mice, rats, and monkeys from pre-clinical SCI studies published between 1993 and 2013. The majority of animals in the database have measures collected for health monitoring, such as weight loss/gain, heart rate, blood pressure, postoperative monitoring of bladder function and drug/fluid administration, behavioral outcome measures of locomotion, and tissue sparing postmortem. Attempts to align these variables with currently accepted common data elements highlighted the need for more translational outcomes to be identified as clinical endpoints for therapeutic testing. Last, we use syndromic analysis to identify conserved biological mechanisms of recovery after cervical SCI between rats and monkeys that will allow for more-efficient testing of therapeutics that will need to be translated toward future clinical trials.

Improving the transparency of prognosis research: the role of reporting, data sharing, registration, and protocols

George Peat and colleagues review and discuss current approaches to transparency and published debates and concerns about efforts to standardize prognosis research practice, and make five recommendations.

Please see later in the article for the Editors' Summary

Decompressive craniectomy for management of traumatic brain injury: an update

Decompressive craniectomy (DC) for the management of severe traumatic brain injury (TBI) has a long history but remains controversial. Although DC has been shown to improve both survival and functional outcome in patients with malignant cerebral infarctions, evidence of benefit in patients with TBI is decidedly more mixed. Craniectomy can clearly be life-saving in the presence of medically intractable elevations of intracranial pressure. Craniectomy also has been consistently demonstrated to reduce "therapeutic intensity" in the ICU, to reduce the need for intracranial-pressure-directed and brain-oxygen-directed interventions, and to reduce ICU length of stay. Still, the only randomized trial of DC in TBI failed to demonstrate any benefit. Studies of therapies for TBI, including hemicraniectomy, are challenging owing to the inherent heterogeneity in the pathophysiology observed in this disease. Craniectomy can be life-saving for patients with severe TBI, but many questions remain regarding its ideal application, and the outcome remains highly correlated with the severity of the initial injury.

Fever burden is an independent predictor for prognosis of traumatic brain injury

OBJECTIVE

To evaluate fever burden as an independent predictor for prognosis of traumatic brain injury (TBI).

METHODS

This retrospective study involved 355 TBI patients with Glasgow Coma Scale (GCS) ≤14, who presented at the emergency department of our hospital between November 2010 and October 2012. At 6 months follow-up, patients were divided into 5 groups based on Glasgow Outcome Scale (GOS) and dichotomized to GOS score (high (4 to 5) vs. low (1 to 3)). The relationship between fever burden and GOS was assessed.

RESULTS

Fever burden increased as GOS scores decreased from 5 to 2, except for score 1 of GOS, which corresponded to a significant lower fever burden. Following dichotomization, patients in the high GOS group were younger, and showed less abnormal pupil reactivity (P<0.001), a higher median GCS score (P<0.001), and a lower median fever burden (P<0.001), compared with patients in the low GOS group. Univariate logistic regression analysis revealed that poor TBI prognosis was related to age, GCS, pupil reactivity, and fever burden (OR: 1.166 [95% CI: 1.117-1.217] P<0.0001). Multivariate logistic regression analysis identified fever burden as an independent predictor of poor prognosis after TBI (OR 1.098; 95% CI: 1.031-1.169; P = 0.003). These observations were confirmed by evaluation of the receiver operating characteristic (ROC) curve for fever burden (area under the curve [AUC] 0.73 [95% CI: 0.663-0.760]).

CONCLUSION

Fever burden might be an independent predictor for prognosis of TBI. High fever burden in the early stage of the disease course associated with TBI could increase the risk of poor prognosis.

Meta-analysis and aggregation of multiple published prediction models

Published clinical prediction models are often ignored during the development of novel prediction models despite similarities in populations and intended usage. The plethora of prediction models that arise from this practice may still perform poorly when applied in other populations. Incorporating prior evidence might improve the accuracy of prediction models and make them potentially better generalizable. Unfortunately, aggregation of prediction models is not straightforward, and methods to combine differently specified models are currently lacking. We propose two approaches for aggregating previously published prediction models when a validation dataset is available: model averaging and stacked regressions. These approaches yield user-friendly stand-alone models that are adjusted for the new validation data. Both approaches rely on weighting to account for model performance and between-study heterogeneity but adopt a different rationale (averaging versus combination) to combine the models. We illustrate their implementation in a clinical example and compare them with established methods for prediction modeling in a series of simulation studies. Results from the clinical datasets and simulation studies demonstrate that aggregation yields prediction models with better discrimination and calibration in a vast majority of scenarios, and results in equivalent performance (compared to developing a novel model from scratch) when validation datasets are relatively large. In conclusion, model aggregation is a promising strategy when several prediction models are available from the literature and a validation dataset is at hand. The aggregation methods do not require existing models to have similar predictors and can be applied when relatively few data are at hand.

Lifetime attributable risk of cancer from CT among patients surviving severe traumatic brain injury

OBJECTIVE

The purpose of this study was to determine the lifetime attributable risk of cancer from CT among patients surviving severe traumatic brain injury.

MATERIALS AND METHODS

A retrospective cross-sectional study was conducted with prospectively collected data on patients 16 years old and older admitted with a Glasgow coma scale score of 8 or less to a single level 1 trauma center from 2007 to 2010. The effective dose of each CT examination the patients underwent was predicted with literature-accepted effective dose values of standard helical CT protocols. The lifetime attributable risk of cancer and related mortality incurred as a result of CT were estimated with the cumulative effective dose incurred from the time of injury to a 1-year follow-up evaluation and with the approach established by the Biologic Effects of Ionizing Radiation VII report.

RESULTS

The average patient was a 34-year-old man. The median number of CT examinations received during the first 12 months after injury was 20, and the average cumulative effective dose was 87 ± 45 mSv. This resulted in increases in the lifetime incidence of all cancer types from 45.5% to 46.3% and in the lifetime incidence of cancer-related mortality from 22.1% to 22.5%.

CONCLUSION

Radiation exposure from the use of CT in the evaluation and management of severe traumatic brain injury causes negligible increases in lifetime attributable risk of cancer and cancer-related mortality. Treating physicians should not allow the concern for future risk of radiation-induced cancer to influence decisions regarding radiographic evaluation in the acute treatment of traumatic brain injury.