Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics

Background

Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable prediction of outcome on admission is of great clinical relevance. We aimed to develop prognostic models with readily available traditional and novel predictors.

Methods and Findings

Prospectively collected individual patient data were analyzed from 11 studies. We considered predictors available at admission in logistic regression models to predict mortality and unfavorable outcome according to the Glasgow Outcome Scale at 6 mo after injury. Prognostic models were developed in 8,509 patients with severe or moderate TBI, with cross-validation by omission of each of the 11 studies in turn. External validation was on 6,681 patients from the recent Medical Research Council Corticosteroid Randomisation after Significant Head Injury (MRC CRASH) trial. We found that the strongest predictors of outcome were age, motor score, pupillary reactivity, and CT characteristics, including the presence of traumatic subarachnoid hemorrhage. A prognostic model that combined age, motor score, and pupillary reactivity had an area under the receiver operating characteristic curve (AUC) between 0.66 and 0.84 at cross-validation. This performance could be improved (AUC increased by approximately 0.05) by considering CT characteristics, secondary insults (hypotension and hypoxia), and laboratory parameters (glucose and hemoglobin). External validation confirmed that the discriminative ability of the model was adequate (AUC 0.80). Outcomes were systematically worse than predicted, but less so in 1,588 patients who were from high-income countries in the CRASH trial.

Conclusions

Prognostic models using baseline characteristics provide adequate discrimination between patients with good and poor 6 mo outcomes after TBI, especially if CT and laboratory findings are considered in addition to traditional predictors. The model predictions may support clinical practice and research, including the design and analysis of randomized controlled trials.     

Exendin-4 Ameliorates Traumatic Brain Injury-Induced Cognitive Impairment in Rats

Traumatic brain injury represents a major public health issue that affects 1.7 million Americans each year and is a primary contributing factor (30.5%) of all injury-related deaths in the United States. The occurrence of traumatic brain injury is likely underestimated and thus has been termed “a silent epidemic”. Exendin-4 is a long-acting glucagon-like peptide-1 receptor agonist approved for the treatment of type 2 diabetes mellitus that not only effectively induces glucose-dependent insulin secretion to regulate blood glucose levels but also reduces apoptotic cell death of pancreatic β-cells. Accumulating evidence also supports a neurotrophic and neuroprotective role of glucagon-like peptide-1 in an array of cellular and animal neurodegeneration models. In this study, we evaluated the neuroprotective effects of Exendin-4 using a glutamate toxicity model in vitro and fluid percussion injury in vivo. We found neuroprotective effects of Exendin-4 both in vitro, using markers of cell death, and in vivo, using markers of cognitive function, as assessed by Morris Water Maze. In combination with the reported benefits of ex-4 in other TBI models, these data support repositioning of Exendin-4 as a potential treatment for traumatic brain injury.     

A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome

PurposeTo identify risk factors and develop a prediction model for the development of profound and recurrent shock amongst children presenting with dengue shock syndrome (DSS)MethodsWe analyzed data from a prospective cohort of children with DSS recruited at the Paediatric Intensive Care Unit of the Hospital for Tropical Disease in Ho Chi Minh City, Vietnam. The primary endpoint was “profound DSS”, defined as ≥2 recurrent shock episodes (for subjects presenting in compensated shock), or ≥1 recurrent shock episodes (for subjects presenting initially with decompensated/hypotensive shock), and/or requirement for inotropic support. Recurrent shock was evaluated as a secondary endpoint. Risk factors were pre-defined clinical and laboratory variables collected at the time of presentation with shock. Prognostic model development was based on logistic regression and compared to several alternative approaches.ResultsThe analysis population included 1207 children of whom 222 (18%) progressed to “profound DSS” and 433 (36%) had recurrent shock. Independent risk factors for both endpoints included younger age, earlier presentation, higher pulse rate, higher temperature, higher haematocrit and, for females, worse hemodynamic status at presentation. The final prognostic model for “profound DSS” showed acceptable discrimination (AUC=0.69 for internal validation) and calibration and is presented as a simple score-chart.ConclusionsSeveral risk factors for development of profound or recurrent shock among children presenting with DSS were identified. The score-chart derived from the prognostic models should improve triage and management of children presenting with DSS in dengue-endemic areas.     

Longitudinal Treatment Outcomes of Microsurgical Treatment of Neurosensory Deficit after Lower Third Molar Surgery: A Prospective Case Series

Objective

To prospectively evaluate the longitudinal subjective and objective outcomes of the microsurgical treatment of lingual nerve (LN) and inferior alveolar nerve (IAN) injury after third molar surgery.

Materials and Methods

A 1-year longitudinal observational study was conducted on patients who received LN or IAN repair after third molar surgery-induced nerve injury. Subjective assessments (“numbness”, “hyperaesthesia”, “pain”, “taste disturbance”, “speech” and “social life impact”) and objective assessments (light touch threshold, two-point discrimination, pain threshold, and taste discrimination) were recorded.

Results

12 patients (10 females) with 10 LN and 2 IAN repairs were recruited. The subjective outcomes at post-operative 12 months for LN and IAN repair were improved. “Pain” and “hyperaesthesia” were most drastically improved. Light touch threshold improved from 44.7g to 1.2g for LN repair and 2g to 0.5g for IAN repair.

Conclusion

Microsurgical treatment of moderate to severe LN injury after lower third molar surgery offered significant subjective and objective sensory improvements. 100% FSR was achieved at post-operative 6 months.     

Modelling long term disability following injury: comparison of three approaches for handling multiple injuries

Background

Injury is a leading cause of the global burden of disease (GBD). Estimates of non-fatal injury burden have been limited by a paucity of empirical outcomes data. This study aimed to (i) establish the 12-month disability associated with each GBD 2010 injury health state, and (ii) compare approaches to modelling the impact of multiple injury health states on disability as measured by the Glasgow Outcome Scale – Extended (GOS-E).

Methods

12-month functional outcomes for 11,337 survivors to hospital discharge were drawn from the Victorian State Trauma Registry and the Victorian Orthopaedic Trauma Outcomes Registry. ICD-10 diagnosis codes were mapped to the GBD 2010 injury health states. Cases with a GOS-E score >6 were defined as “recovered.” A split dataset approach was used. Cases were randomly assigned to development or test datasets. Probability of recovery for each health state was calculated using the development dataset. Three logistic regression models were evaluated: a) additive, multivariable; b) “worst injury;” and c) multiplicative. Models were adjusted for age and comorbidity and investigated for discrimination and calibration.

Findings

A single injury health state was recorded for 46% of cases (1–16 health states per case). The additive (C-statistic 0.70, 95% CI: 0.69, 0.71) and “worst injury” (C-statistic 0.70; 95% CI: 0.68, 0.71) models demonstrated higher discrimination than the multiplicative (C-statistic 0.68; 95% CI: 0.67, 0.70) model. The additive and “worst injury” models demonstrated acceptable calibration.

Conclusions

The majority of patients survived with persisting disability at 12-months, highlighting the importance of improving estimates of non-fatal injury burden. Additive and “worst” injury models performed similarly. GBD 2010 injury states were moderately predictive of recovery 1-year post-injury. Further evaluation using additional measures of health status and functioning and comparison with the GBD 2010 disability weights will be needed to optimise injury states for future GBD studies.     

The Emergence of Three Human Development Clubs

We examine the joint distribution of levels of income per capita, life expectancy, and years of schooling across countries in 1960 and in 2000. In 1960 countries were clustered in two groups; a rich, highly educated, high longevity “developed” group and a poor, less educated, high mortality, “underdeveloped” group. By 2000 however we see the emergence of three groups; one underdeveloped group remaining near 1960 levels, a developed group with higher levels of education, income, and health than in 1960, and an intermediate group lying between these two. This finding is consistent with both the ideas of a new “middle income trap” that countries face even if they escape the “low income trap”, as well as the notion that countries which escaped the poverty trap form a temporary “transition regime” along their path to the “developed” group.     

Increased Gray Matter Diffusion Anisotropy in Patients with Persistent Post-Concussive Symptoms following Mild Traumatic Brain Injury

A significant percentage of individuals diagnosed with mild traumatic brain injury (mTBI) experience persistent post-concussive symptoms (PPCS). Little is known about the pathology of these symptoms and there is often no radiological evidence based on conventional clinical imaging. We aimed to utilize methods to evaluate microstructural tissue changes and to determine whether or not a link with PPCS was present. A novel analysis method was developed to identify abnormalities in high-resolution diffusion tensor imaging (DTI) when the location of brain injury is heterogeneous across subjects. A normative atlas with 145 brain regions of interest (ROI) was built from 47 normal controls. Comparing each subject’s diffusion measures to the atlas generated subject-specific profiles of injury. Abnormal ROIs were defined by absolute z-score values above a given threshold. The method was applied to 11 PPCS patients following mTBI and 11 matched controls. Z-score information for each individual was summarized with two location-independent measures: “load” (number of abnormal regions) and “severity” (largest absolute z-score). Group differences were then computed using Wilcoxon rank sum tests. Results showed statistically significantly higher load (p = 0.018) and severity (p = 0.006) for fractional anisotropy (FA) in patients compared with controls. Subject-specific profiles of injury evinced abnormally high FA regions in gray matter (30 occurrences over 11 patients), and abnormally low FA in white matter (3 occurrences over 11 subjects). Subject-specific profiles provide important information regarding the pathology associated with PPCS. Increased gray matter (GM) anisotropy is a novel in-vivo finding, which is consistent with an animal model of brain trauma that associates increased FA in GM with pathologies such as gliosis. In addition, the individualized analysis shows promise for enhancing the clinical care of PPCS patients as it could play a role in the diagnosis of brain injury not revealed using conventional imaging.     

Call Off the Dog(ma): M1/M2 Polarization Is Concurrent following Traumatic Brain Injury

Following the primary mechanical impact, traumatic brain injury (TBI) induces the simultaneous production of a variety of pro- and anti-inflammatory molecular mediators. Given the variety of cell types and their requisite expression of cognate receptors this creates a highly complex inflammatory milieu. Increasingly in neurotrauma research there has been an effort to define injury-induced inflammatory responses within the context of in vitro defined macrophage polarization phenotypes, known as “M1” and “M2”. Herein, we expand upon our previous work in a rodent model of TBI to show that the categorization of inflammatory response cannot be so easily delineated using this nomenclature. Specifically, we show that TBI elicited a wide spectrum of concurrent expression responses within both pro- and anti-inflammatory arms. Moreover, we show that the cells principally responsible for the production of these inflammatory mediators, microglia/macrophages, simultaneously express both “M1” and “M2” phenotypic markers. Overall, these data align with recent reports suggesting that microglia/macrophages cannot adequately switch to a polarized “M1-only” or “M2-only” phenotype, but display a mixed phenotype due to the complex signaling events surrounding them.     

Comparison of the performances of copeptin and multiple biomarkers in long-term prognosis of severe traumatic brain injury

Enhanced blood levels of copeptin correlate with poor clinical outcomes after acute critical illness. This study aimed to compare the prognostic performances of plasma concentrations of copeptin and other biomarkers like myelin basic protein, glial fibrillary astrocyte protein, S100B, neuron-specific enolase, phosphorylated axonal neurofilament subunit H, Tau and ubiquitin carboxyl-terminal hydrolase L1 in severe traumatic brain injury. We recruited 102 healthy controls and 102 acute patients with severe traumatic brain injury. Plasma concentrations of these biomarkers were determined using enzyme-linked immunosorbent assay. Their prognostic predictive performances of 6-month mortality and unfavorable outcome (Glasgow Outcome Scale score of 1–3) were compared. Plasma concentrations of these biomarkers were statistically significantly higher in all patients than in healthy controls, in non-survivors than in survivors and in patients with unfavorable outcome than with favorable outcome. Areas under receiver operating characteristic curves of plasma concentrations of these biomarkers were similar to those of Glasgow Coma Scale score for prognostic prediction. Except plasma copeptin concentration, other biomarkers concentrations in plasma did not statistically significantly improve prognostic predictive value of Glasgow Coma Scale score. Copeptin levels may be a useful tool to predict long-term clinical outcomes after severe traumatic brain injury and have a potential to assist clinicians.     

A Flexible Alternative to the Cox Proportional Hazards Model for Assessing the Prognostic Accuracy of Hospice Patient Survival

Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models. However, it may be suboptimal due to the inflexibility to model the baseline survival function and when the proportional hazards assumption is violated. The aim of this study was to use internal validation to compare the predictive power of a flexible Royston-Parmar family of survival functions with the Cox proportional hazards model. We applied the Palliative Performance Scale on a dataset of 590 hospice patients at the time of hospice admission. The retrospective data were obtained from the Lifepath Hospice and Palliative Care center in Hillsborough County, Florida, USA. The criteria used to evaluate and compare the models'' predictive performance were the explained variation statistic R², scaled Brier score, and the discrimination slope. The explained variation statistic demonstrated that overall the Royston-Parmar family of survival functions provided a better fit (R² = 0.298; 95% CI: 0.236–0.358) than the Cox model (R² = 0.156; 95% CI: 0.111–0.203). The scaled Brier scores and discrimination slopes were consistently higher under the Royston-Parmar model. Researchers involved in prognosticating patient survival are encouraged to consider the Royston-Parmar model as an alternative to Cox.     

Modeling Stroke in Mice: Permanent Coagulation of the Distal Middle Cerebral Artery

Stroke is the third most common cause of death and a main cause of acquired adult disability in developed countries. Only very limited therapeutical options are available for a small proportion of stroke patients in the acute phase. Current research is intensively searching for novel therapeutic strategies and is increasingly focusing on the sub-acute and chronic phase after stroke because more patients might be eligible for therapeutic interventions in a prolonged time window. These delayed mechanisms include important pathophysiological pathways such as post-stroke inflammation, angiogenesis, neuronal plasticity and regeneration. In order to analyze these mechanisms and to subsequently evaluate novel drug targets, experimental stroke models with clinical relevance, low mortality and high reproducibility are sought after. Moreover, mice are the smallest mammals in which a focal stroke lesion can be induced and for which a broad spectrum of transgenic models are available. Therefore, we describe here the mouse model of transcranial, permanent coagulation of the middle cerebral artery via electrocoagulation distal of the lenticulostriatal arteries, the so-called “coagulation model”. The resulting infarct in this model is located mainly in the cortex; the relative infarct volume in relation to brain size corresponds to the majority of human strokes. Moreover, the model fulfills the above-mentioned criteria of reproducibility and low mortality. In this video we demonstrate the surgical methods of stroke induction in the “coagulation model” and report histological and functional analysis tools.     

The Prognostic Value of Serum Neuron-Specific Enolase in Traumatic Brain Injury: Systematic Review and Meta-Analysis

Background

Several studies have suggested that neuron-specific enolase (NSE) in serum may be a biomarker of traumatic brain injury. However, whether serum NSE levels correlate with outcomes remains unclear. The purpose of this review was to evaluate the prognostic value of serum NSE protein after traumatic brain injury.

Methods

PubMed and Embase were searched for relevant studies published up to October 2013. Full-text publications on the relationship of NSE to TBI were included if the studies concerned patients with closed head injury, NSE levels in serum after injury, and Glasgow Outcome Scale (GOS) or Extended GOS (GOSE) scores or mortality. Study design, inclusion criteria, assay, blood sample collection time, NSE cutoff, sensitivity and specificity of NSE for mortality prediction (if sufficient information was provided to calculate these values), and main outcomes were recorded.

Results

Sixteen studies were eligible for the current meta-analysis. In the six studies comparing NSE concentrations between TBI patients who died and those who survived, NSE concentrations correlated with mortality (M.D. 0.28, 95% confidence interval (CI), 0.21 to 0.34; I² 55%). In the eight studies evaluating GOS or GOSE, patients with unfavorable outcomes had significantly higher NSE concentrations than those with favorable outcomes (M.D. 0.24, 95% CI, 0.17 to 0.31; I² 64%). From the studies providing sufficient data, the pooled sensitivity and specificity for mortality were 0.79 and 0.50, and 0.72 and 0.66 for unfavorable neurological prognosis, respectively. The areas under the SROC curve (AUC) of NSE concentrations were 0.73 (95% CI, 0.66–0.80) for unfavorable outcome and 0.76 (95% CI, 0.62–0.90) for mortality.

Conclusions

Mortality and unfavorable outcome were significantly associated with greater NSE concentrations. In addition, NSE has moderate discriminatory ability to predict mortality and neurological outcome in TBI patients. The optimal discrimination cutoff values and optimal sampling time remain uncertain because of significant variations between studies.     

A simple mortality risk prediction score for viper envenoming in India (VENOMS): A model development and validation study

BackgroundSnakebite is a neglected problem with a high mortality in India. There are no simple clinical prognostic tools which can predict mortality in viper envenomings. We aimed to develop and validate a mortality-risk prediction score for patients of viper envenoming from Southern India.MethodsWe used clinical predictors from a prospective cohort of 248 patients with syndromic diagnosis of viper envenoming and had a positive 20-minute whole blood clotting test (WBCT 20) from a tertiary-care hospital in Puducherry, India. We applied multivariable logistic regression with backward elimination approach. External validation of this score was done among 140 patients from the same centre and its performance was assessed with concordance statistic and calibration plots.FindingsThe final model termed VENOMS from the term “Viper ENvenOming Mortality Score included 7 admission clinical parameters (recorded in the first 48 hours after bite): presence of overt bleeding manifestations, presence of capillary leak syndrome, haemoglobin <10 g/dL, bite to antivenom administration time > 6.5 h, systolic blood pressure < 100 mm Hg, urine output <20 mL/h in 24 h and female gender. The lowest possible VENOMS score of 0 predicted an in-hospital mortality risk of 0.06% while highest score of 12 predicted a mortality of 99.1%. The model had a concordance statistic of 0·86 (95% CI 0·79–0·94) in the validation cohort. Calibration plots indicated good agreement of predicted and observed outcomes.ConclusionsThe VENOMS score is a good predictor of the mortality in viper envenoming in southern India where Russell’s viper envenoming burden is high. The score may have potential applications in triaging patients and guiding management after further validation.     

The effect of traumatic brain injury on the health of homeless people

Background

We sought to determine the lifetime prevalence of traumatic brain injury and its association with current health conditions in a representative sample of homeless people in Toronto, Ontario.

Methods

We surveyed 601 men and 303 women at homeless shelters and meal programs in 2004–2005 (response rate 76%). We defined traumatic brain injury as any self-reported head injury that left the person dazed, confused, disoriented or unconscious. Injuries resulting in unconsciousness lasting 30 minutes or longer were defined as moderate or severe. We assessed mental health, alcohol and drug problems in the past 30 days using the Addiction Severity Index. Physical and mental health status was assessed using the SF-12 health survey. We examined associations between traumatic brain injury and health conditions.

Results

The lifetime prevalence among homeless participants was 53% for any traumatic brain injury and 12% for moderate or severe traumatic brain injury. For 70% of respondents, their first traumatic brain injury occurred before the onset of homelessness. After adjustment for demographic characteristics and lifetime duration of homelessness, a history of moderate or severe traumatic brain injury was associated with significantly increased likelihood of seizures (odds ratio [OR] 3.2, 95% confidence interval [CI] 1.8 to 5.6), mental health problems (OR 2.5, 95% CI 1.5 to 4.1), drug problems (OR 1.6, 95% CI 1.1 to 2.5), poorer physical health status (–8.3 points, 95% CI –11.1 to –5.5) and poorer mental health status (–6.0 points, 95% CI –8.3 to –3.7).

Interpretation

Prior traumatic brain injury is very common among homeless people and is associated with poorer health.Traumatic brain injury is caused by “a blow or jolt to the head or a penetrating head injury that disrupts the normal function of the brain” and most commonly results from falls, motor vehicle traffic crashes and assaults.¹ Traumatic brain injury is a leading cause of permanent disability in North America.¹ Traumatic brain injury may be common in the homeless population.² Exposure to physical abuse during childhood, which could result in traumatic brain injury, is a known risk factor for homelessness as an adult.³ Substance abuse increases the risk of homelessness⁴ and the risk of traumatic brain injury.⁵ Homeless people experience high rates of injury of all types and are frequently victims of assault.^6,7 Finally, traumatic brain injury could be a factor contributing to the 3%–8% prevalence of cognitive dysfunction among homeless adults.^8,9Providing health care for homeless patients can be challenging for various reasons, including difficult behavioural patterns. These behaviours may be related in part to unrecognized sequelae of traumatic brain injury and may include cognitive impairment, attention deficits, disinhibition, impulsivity and emotional lability.¹ Appropriate support services may be able to minimize the adverse impact of these behaviours.Two previous studies have reported the prevalence of traumatic brain injury among homeless people in London, England, and Milwaukee, Wisconsin. These studies were limited by small sample sizes, recruitment at a single shelter and a lack of data from women.^10,11 We conducted this study to determine the lifetime prevalence of traumatic brain injury in a representative sample of homeless men and women across an entire city, and to identify the temporal relation between traumatic brain injury and the onset of homelessness. We also sought to characterize the association between a history of traumatic brain injury and current health problems in this population. Our primary hypothesis was that a history of traumatic brain injury would be associated with poor current health.     

Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models

Detecting gene-gene interaction in complex diseases has become an important priority for common disease genetics, but most current approaches to detecting interaction start with disease-marker associations. These approaches are based on population allele frequency correlations, not genetic inheritance, and therefore cannot exploit the rich information about inheritance contained within families. They are also hampered by issues of rigorous phenotype definition, multiple test correction, and allelic and locus heterogeneity. We recently developed, tested, and published a powerful gene-gene interaction detection strategy based on conditioning family data on a known disease-causing allele or a disease-associated marker allele⁴. We successfully applied the method to disease data and used computer simulation to exhaustively test the method for some epistatic models. We knew that the statistic we developed to indicate interaction was less reliable when applied to more-complex interaction models. Here, we improve the statistic and expand the testing procedure. We computer-simulated multipoint linkage data for a disease caused by two interacting loci. We examined epistatic as well as additive models and compared them with heterogeneity models. In all our models, the at-risk genotypes are “major” in the sense that among affected individuals, a substantial proportion has a disease-related genotype. One of the loci (A) has a known disease-related allele (as would have been determined from a previous analysis). We removed (pruned) family members who did not carry this allele; the resultant dataset is referred to as “stratified.” This elimination step has the effect of raising the “penetrance” and detectability at the second locus (B). We used the lod scores for the stratified and unstratified data sets to calculate a statistic that either indicated the presence of interaction or indicated that no interaction was detectable. We show that the new method is robust and reliable for a wide range of parameters. Our statistic performs well both with the epistatic models (false negative rates, i.e., failing to detect interaction, ranging from 0 to 2.5%) and with the heterogeneity models (false positive rates, i.e., falsely detecting interaction, ≤1%). It works well with the additive model except when allele frequencies at the two loci differ widely. We explore those features of the additive model that make detecting interaction more difficult. All testing of this method suggests that it provides a reliable approach to detecting gene-gene interaction.     

Urinary Tissue Inhibitor of Metalloproteinase-2 (TIMP-2) ? Insulin-Like Growth Factor-Binding Protein 7 (IGFBP7) Predicts Adverse Outcome in Pediatric Acute Kidney Injury

Background

The G1 cell cycle inhibitors tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) have been identified as promising biomarkers for the prediction of adverse outcomes including renal replacement therapy (RRT) and mortality in critically ill adult patients who develop acute kidney injury (AKI). However, the prognostic value of urinary TIMP-2 and IGFBP7 in neonatal and pediatric AKI for adverse outcome has not been investigated yet.

Methods

The product of the urinary concentration of TIMP-2 and IGFBP7 ([TIMP-2]•[IGFBP7]) was assessed by a commercially available immunoassay (NephroCheck^™) in a prospective cohort study in 133 subjects aged 0–18 years including 46 patients with established AKI according to pRIFLE criteria, 27 patients without AKI (non-AKI group I) and 60 apparently healthy neonates and children (non-AKI group II). AKI etiologies were: dehydration/hypovolemia (n = 7), hemodynamic instability (n = 7), perinatal asphyxia (n = 9), septic shock (n = 7), typical hemolytic-uremic syndrome (HUS; n = 5), interstitial nephritis (n = 5), vasculitis (n = 4), nephrotoxic injury (n = 1) and renal vein thrombosis (n = 1).

Results

When AKI patients were classified into pRIFLE criteria, 6/46 (13%) patients fulfilled the criteria for the category “Risk”, 13/46 (28%) for “Injury”, 26/46 (57%) for “Failure” and 1/46 (2%) for “Loss”. Patients in the “Failure” stage had a median 3.7-fold higher urinary [TIMP-2]•[IGFBP7] compared to non-AKI subjects (P<0.001). When analyzed for AKI etiology, highest [TIMP-2]•[IGFBP7] values were found in patients with septic shock (P<0.001 vs. non-AKI I+II). Receiver operating characteristic (ROC) curve analyses in the AKI group revealed good performance of [TIMP-2]•[IGFBP7] in predicting 30-day (area under the curve (AUC) 0.79; 95% CI, 0.61–0.97) and 3-month mortality (AUC 0.84; 95% CI, 0.67–0.99) and moderate performance in predicting RRT (AUC 0.67; 95% CI, 0.50–0.84).

Conclusions

This study shows that urinary [TIMP-2]•[IGFBP7] has a good diagnostic performance in predicting adverse outcomes in neonatal and pediatric AKI of heterogeneous etiology.     

Can Playing the Computer Game “Tetris” Reduce the Build-Up of Flashbacks for Trauma? A Proposal from Cognitive Science

Background

Flashbacks are the hallmark symptom of Posttraumatic Stress Disorder (PTSD). Although we have successful treatments for full-blown PTSD, early interventions are lacking. We propose the utility of developing a ‘cognitive vaccine’ to prevent PTSD flashback development following exposure to trauma. Our theory is based on two key findings: 1) Cognitive science suggests that the brain has selective resources with limited capacity; 2) The neurobiology of memory suggests a 6-hr window to disrupt memory consolidation. The rationale for a ‘cognitive vaccine’ approach is as follows: Trauma flashbacks are sensory-perceptual, visuospatial mental images. Visuospatial cognitive tasks selectively compete for resources required to generate mental images. Thus, a visuospatial computer game (e.g. “Tetris”) will interfere with flashbacks. Visuospatial tasks post-trauma, performed within the time window for memory consolidation, will reduce subsequent flashbacks. We predicted that playing “Tetris” half an hour after viewing trauma would reduce flashback frequency over 1-week.

Methodology/Principal Findings

The Trauma Film paradigm was used as a well-established experimental analog for Post-traumatic Stress. All participants viewed a traumatic film consisting of scenes of real injury and death followed by a 30-min structured break. Participants were then randomly allocated to either a no-task or visuospatial (“Tetris”) condition which they undertook for 10-min. Flashbacks were monitored for 1-week. Results indicated that compared to the no-task condition, the “Tetris” condition produced a significant reduction in flashback frequency over 1-week. Convergent results were found on a clinical measure of PTSD symptomatology at 1-week. Recognition memory between groups did not differ significantly.

Conclusions/Significance

Playing “Tetris” after viewing traumatic material reduces unwanted, involuntary memory flashbacks to that traumatic film, leaving deliberate memory recall of the event intact. Pathological aspects of human memory in the aftermath of trauma may be malleable using non-invasive, cognitive interventions. This has implications for a novel avenue of preventative treatment development, much-needed as a crisis intervention for the aftermath of traumatic events.     

Predicting Survival of De Novo Metastatic Breast Cancer in Asian Women: Systematic Review and Validation Study

Background

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia.

Materials and Methods

We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic).

Results

We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48–0.53) to 0.63 (95% CI, 0.60–0.66).

Conclusion

The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.     

CT follow-up and clinical outcome in severe traumatic brain injury patients

Determining a patient's prognosis after severe traumatic brain injury remains difficult and complex. The purpose of the present study was following up patients with severe traumatic brain injury by correlating their clinical outcome and sequential computer tomography (CT) findings. We investigated 51 patients who survived the first year following an accident. All patients underwent successive CT examinations within a maximum period of 2 years. The patients' outcomes depended on the underlying brain damage and are presented by the Glasgow Outcome Scale. Based on the investigated data we concluded that the worst outcomes were experienced by patients with initial massive cerebral edema, extensive subdural hematoma and intraventricular hemorrhage, followed by stroke as subacute CT finding and cerebral atrophy as chronic finding visible at follow-up CT scans. The majority of lesions identified by CT scan were found in the frontal lobes, basal ganglia, and temporal lobes. We suggest that CT examination still represents a simple and useful tool in attempting to predict the clinical outcome in patients with severe traumatic brain injury.