Validation of the CRASH model in the prediction of 18-month mortality and unfavorable outcome in severe traumatic brain injury requiring decompressive craniectomy

2014 ◽  
Vol 120 (5) ◽  
pp. 1131-1137 ◽  
Author(s):  
Stephen Honeybul ◽  
Kwok M. Ho ◽  
Christopher R. P. Lind ◽  
Grant R. Gillett
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Prediction Model ◽  
Decompressive Craniectomy ◽  
Severe Traumatic Brain Injury ◽  
Operating Characteristic ◽  
Injury Severity ◽  
Characteristic Curve ◽  
Operating Characteristic Curve ◽  
Crash Model

Object The goal in this study was to assess the validity of the corticosteroid randomization after significant head injury (CRASH) collaborators prediction model in predicting mortality and unfavorable outcome at 18 months in patients with severe traumatic brain injury (TBI) requiring decompressive craniectomy. In addition, the authors aimed to assess whether this model was well calibrated in predicting outcome across a wide spectrum of severity of TBI requiring decompressive craniectomy. Methods This prospective observational cohort study included all patients who underwent a decompressive craniectomy following severe TBI at the two major trauma hospitals in Western Australia between 2004 and 2012 and for whom 18-month follow-up data were available. Clinical and radiological data on initial presentation were entered into the Web-based model and the predicted outcome was compared with the observed outcome. In validating the CRASH model, the authors used area under the receiver operating characteristic curve to assess the ability of the CRASH model to differentiate between favorable and unfavorable outcomes. Results The ability of the CRASH 6-month unfavorable prediction model to differentiate between unfavorable and favorable outcomes at 18 months after decompressive craniectomy was good (area under the receiver operating characteristic curve 0.85, 95% CI 0.80–0.90). However, the model's calibration was not perfect. The slope and the intercept of the calibration curve were 1.66 (SE 0.21) and −1.11 (SE 0.14), respectively, suggesting that the predicted risks of unfavorable outcomes were not sufficiently extreme or different across different risk strata and were systematically too high (or overly pessimistic), respectively. Conclusions The CRASH collaborators prediction model can be used as a surrogate index of injury severity to stratify patients according to injury severity. However, clinical decisions should not be based solely on the predicted risks derived from the model, because the number of patients in each predicted risk stratum was still relatively small and hence the results were relatively imprecise. Notwithstanding these limitations, the model may add to a clinician's ability to have better-informed conversations with colleagues and patients' relatives about prognosis.

scholarly journals Assessment of White Matter Injury and Outcome in Severe Brain Trauma

2012 ◽  
Vol 117 (6) ◽  
pp. 1300-1310 ◽  
Author(s):  
Damien Galanaud ◽  
Vincent Perlbarg ◽  
Rajiv Gupta ◽  
Robert D. Stevens ◽  
Paola Sanchez ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Clinical Trials ◽  
Brain Injury ◽  
White Matter ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Unfavorable Outcome ◽  
Operating Characteristic Curve

Background Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI). Methods In a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n=38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score. Results Using the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database. Conclusions White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score.

scholarly journals Disability Rating Scale in the First Few Weeks After a Severe Traumatic Brain Injury as a Predictor of 6-Month Functional Outcome

Neurosurgery ◽  
2020 ◽  
Author(s):  
Jose-Miguel Yamal ◽  
Imoigele P Aisiku ◽  
H Julia Hannay ◽  
Frances A Brito ◽  
Claudia S Robertson
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
Clinical Decision Making ◽  
Injury Severity ◽  
Rating Scale ◽  
Characteristic Curve ◽  
Disability Rating Scale ◽  
Severe Tbi ◽  
Disability Rating

Abstract BACKGROUND An early acute marker of long-term neurological outcome would be useful to help guide clinical decision making and therapeutic effectiveness after severe traumatic brain injury (TBI). We investigated the utility of the Disability Rating Scale (DRS) as early as 1 wk after TBI as a predictor of favorable 6-mo Glasgow Outcome Scale extended (GOS-E). OBJECTIVE To determine the predictability of a favorable 6-mo GOS-E using the DRS measured during weeks 1 to 4 of injury. METHODS The study is a sub analysis of patients enrolled in the Epo Severe TBI Trial (n = 200) to train and validate L1-regularized logistic regression models. DRS was collected at weeks 1 to 4 and GOS-E at 6 mo. RESULTS The average area under the receiver operating characteristic curve was 0.82 for the model with baseline demographic and injury severity variables and week 1 DRS and increased to 0.88 when including weekly DRS until week 4. CONCLUSION This study suggests that week 1 to 4 DRS may be predictors of favorable 6-mo outcome in severe TBI patients and thus useful both for clinical prognostication as well as surrogate endpoints for adaptive clinical trials.

Selection of children with ultra-severe traumatic brain injury for neurosurgical intervention

2019 ◽  
Vol 23 (6) ◽  
pp. 670-679
Author(s):  
Krista Greenan ◽  
Sandra L. Taylor ◽  
Daniel Fulkerson ◽  
Kiarash Shahlaie ◽  
Clayton Gerndt ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Decision Tree ◽  
Prediction Model ◽  
Severe Traumatic Brain Injury ◽  
Pupillary Response ◽  
Data Set ◽  
Robust Model ◽  
Gcs Score ◽  
Combined Data

OBJECTIVEA recent retrospective study of severe traumatic brain injury (TBI) in pediatric patients showed similar outcomes in those with a Glasgow Coma Scale (GCS) score of 3 and those with a score of 4 and reported a favorable long-term outcome in 11.9% of patients. Using decision tree analysis, authors of that study provided criteria to identify patients with a potentially favorable outcome. The authors of the present study sought to validate the previously described decision tree and further inform understanding of the outcomes of children with a GCS score 3 or 4 by using data from multiple institutions and machine learning methods to identify important predictors of outcome.METHODSClinical, radiographic, and outcome data on pediatric TBI patients (age < 18 years) were prospectively collected as part of an institutional TBI registry. Patients with a GCS score of 3 or 4 were selected, and the previously published prediction model was evaluated using this data set. Next, a combined data set that included data from two institutions was used to create a new, more statistically robust model using binomial recursive partitioning to create a decision tree.RESULTSForty-five patients from the institutional TBI registry were included in the present study, as were 67 patients from the previously published data set, for a total of 112 patients in the combined analysis. The previously published prediction model for survival was externally validated and performed only modestly (AUC 0.68, 95% CI 0.47, 0.89). In the combined data set, pupillary response and age were the only predictors retained in the decision tree. Ninety-six percent of patients with bilaterally nonreactive pupils had a poor outcome. If the pupillary response was normal in at least one eye, the outcome subsequently depended on age: 72% of children between 5 months and 6 years old had a favorable outcome, whereas 100% of children younger than 5 months old and 77% of those older than 6 years had poor outcomes. The overall accuracy of the combined prediction model was 90.2% with a sensitivity of 68.4% and specificity of 93.6%.CONCLUSIONSA previously published survival model for severe TBI in children with a low GCS score was externally validated. With a larger data set, however, a simplified and more robust model was developed, and the variables most predictive of outcome were age and pupillary response.

Self-awareness four years after severe traumatic brain injury: discordance between the patient’s and relative’s complaints. Results from the PariS-TBI study

2017 ◽  
Vol 32 (5) ◽  
pp. 692-704 ◽  
Author(s):  
Camille Chesnel ◽  
Claire Jourdan ◽  
Eleonore Bayen ◽  
Idir Ghout ◽  
Emmanuelle Darnoux ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
Significant Relationship ◽  
Injury Severity ◽  
Chronic Phase ◽  
Functional Independence ◽  
Severe Tbi

Objective: To evaluate the patient’s awareness of his or her difficulties in the chronic phase of severe traumatic brain injury (TBI) and to determine the factors related to poor awareness. Design/Setting/Subjects: This study was part of a larger prospective inception cohort study of patients with severe TBI in the Parisian region (PariS-TBI study). Intervention/Main measures: Evaluation was carried out at four years and included the Brain Injury Complaint Questionnaire (BICoQ) completed by the patient and his or her relative as well as the evaluation of impairments, disability and quality of life. Results: A total of 90 patient-relative pairs were included. Lack of awareness was measured using the unawareness index that corresponded to the number of discordant results between the patient and relative in the direction of under evaluation of difficulties by the patient. The only significant relationship found with lack of awareness was the subjective burden perceived by the relative (Zarit Burden Inventory) ( r = 0.5; P < 0.00001). There was no significant relationship between lack of awareness and injury severity, pre-injury socio-demographic data, cognitive impairments, mood disorders, functional independence (Barthel index), global disability (Glasgow Outcome Scale), return to work at four years or quality of life (Quality Of Life after Brain Injury scale (QOLIBRI)). Conclusion: Lack of awareness four years post severe TBI was not related to the severity of the initial trauma, sociodemographic data, the severity of impairments, limitations of activity and participation, or the patient’s quality of life. However, poor awareness did significantly influence the weight of the burden perceived by the relative.

Relationship of “dose” of intracranial hypertension to outcome in severe traumatic brain injury

2008 ◽  
Vol 109 (4) ◽  
pp. 678-684 ◽  
Author(s):  
Anne Vik ◽  
Torbjørn Nag ◽  
Oddrun Anita Fredriksli ◽  
Toril Skandsen ◽  
Kent Gøran Moen ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Intracranial Hypertension ◽  
Scale Score ◽  
Severe Traumatic Brain Injury ◽  
Injury Severity ◽  
Area Under The Curve ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Scale Scores

Object It has recently been suggested that the degree of intracranial pressure (ICP) above the treatment goal can be estimated by the area under the curve (AUC) of ICP versus time in patients with severe traumatic brain injury (TBI). The objective of this study was to determine whether the calculated “ICP dose”—the ICP AUC—is related to mortality rate, outcome, and Marshall CT classification. Methods Of 135 patients (age range 1–82 years) with severe TBI treated during a 5-year period at the authors' institution, 113 patients underwent ICP monitoring (84%). Ninety-three patients with a monitoring time > 24 hours were included for analysis of ICP AUC calculated using the trapezoidal method. Computed tomography scans were assessed according to the Marshall TBI classification. Patients with Glasgow Outcome Scale scores at 6 months and > 3 years were separated into 2 groups based on outcome. Results Sixty patients (65%) had ICP values > 20 mm Hg, and 12 (13%) developed severe intracranial hypertension and died secondary to herniation. A multiple regression analysis adjusting for Glasgow Coma Scale score, age, pupillary abnormalities and Injury Severity Scale score demonstrated that the ICP AUC was a significant predictor of poor outcome at 6 months (p = 0.034) and of death (p = 0.035). However, it did not predict long-term outcome (p = 0.157). The ICP AUC was significantly higher in patients with Marshall head injury Categories 3 and 4 (24 patients) than in those with Category 2 (23 patients, p = 0.025) and Category 5 (46 patients, p = 0.021) TBIs using the worst CT scan obtained. Conclusions The authors found a significant relationship between the dose of ICP, the worst Marshall CT score, and patient outcome, suggesting that the AUC method may be useful in refining and improving the treatment of ICP in patients with TBI.

Long-term Quality of Life After Decompressive Craniectomy in Severe Traumatic Brain Injury and Stroke

2021 ◽  
Author(s):  
Alex Vicino ◽  
Philippe Vuadens ◽  
Bertrand Léger ◽  
Charles Benaim
Keyword(s):  
Quality Of Life ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Acute Phase ◽  
Decompressive Craniectomy ◽  
Severe Traumatic Brain Injury ◽  
Full Time ◽  
Stroke Patients

Abstract PurposeDecompressive craniectomy (DC) can rapidly reduce intracranial pressure and save lives in the acute phase of severe traumatic brain injury (TBI) or stroke, but little is known about the long-term outcome after DC. We evaluated quality of life (QoL) a few years after DC for severe TBI/stroke.MethodsThe following data were collected for stroke/TBI patients hospitalized for neurorehabilitation after DC: 1) at discharge, motor and cognitive sub-scores of the Functional Independence Measure (motor-FIM [score 13-91] and cognitive-FIM [score 5-35]) and 2) more than 4 years after discharge, the QOLIBRI health-related QoL (HR-QoL) score (0-100; <60 representing low or impaired QoL) and the return to work (RTW: 0%, partial, 100%)ResultsWe included 88 patients (66 males, median age 38 [interquartile range 26.3-51.0], 65 with TBI/23 stroke); 46 responded to the HR-QoL questionnaire. Responders and non-responders had similar characteristics (age, sex, functional levels upon discharge). Median motor-FIM and cognitive-FIM scores were 85/91 and 27/35, with no significant difference between TBI and stroke patients. Long-term QoL was borderline low for TBI patients and within normal values for stroke patients (score 58.0[42.0-69.0] vs. 67.0[54.0-81.5], p=0.052). RTW was comparable between the groups (62% full time).ConclusionWe already knew that DC can save the lives of TBI or stroke patients in the acute phase and this study suggests that their long-term quality of life is generally quite acceptable.

Cerebral oxygenation, vascular reactivity, and neurochemistry following decompressive craniectomy for severe traumatic brain injury

2008 ◽  
Vol 108 (5) ◽  
pp. 943-949 ◽  
Author(s):  
Chi Long Ho ◽  
Chee Meng Wang ◽  
Kah Keow Lee ◽  
Ivan Ng ◽  
Beng Ti Ang
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Decompressive Craniectomy ◽  
Severe Traumatic Brain Injury ◽  
Reactivity Index ◽  
Outcome Group ◽  
The Mean ◽  
Group 2 ◽  
Biochemical Indices ◽  
Group 1

Object This study addresses the changes in brain oxygenation, cerebrovascular reactivity, and cerebral neurochemistry in patients following decompressive craniectomy for the control of elevated intracranial pressure (ICP) after severe traumatic brain injury (TBI). Methods Sixteen consecutive patients with isolated TBI and elevated ICP, who were refractory to maximal medical therapy, underwent decompressive craniectomy over a 1-year period. Thirteen patients were male and 3 were female. The mean age of the patients was 38 years and the median Glasgow Coma Scale score on admission was 5. Results Six months following TBI, 11 patients had a poor outcome (Group 1, Glasgow Outcome Scale [GOS] Score 1–3), whereas the remaining 5 patients had a favorable outcome (Group 2, GOS Score 4 or 5). Decompressive craniectomy resulted in a significant reduction (p < 0.001) in the mean ICP and cerebrovascular pressure reactivity index to autoregulatory values (< 0.3) in both groups of patients. There was a significant improvement in brain tissue oxygenation (PbtO2) in Group 2 patients from 3 to 17 mm Hg and an 85% reduction in episodes of cerebral ischemia. In addition, the durations of abnormal PbtO2 and biochemical indices were significantly reduced in Group 2 patients after decompressive craniectomy, but there was no improvement in the biochemical indices in Group 1 patients despite surgery. Conclusions Decompressive craniectomy, when used appropriately in protocol-driven intensive care regimens for the treatment of recalcitrant elevated ICP, is associated with a return of abnormal metabolic parameters to normal values in patients with eventually favorable outcomes.

scholarly journals A Novel Model for Predicting the Death Risk of Severe Traumatic Brain Injury during Hospitalization

2021 ◽  
Vol 2 (3) ◽  
pp. 01-06
Author(s):  
Yansong Xu ◽  
Zheng Liang
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Prediction Model ◽  
Severe Traumatic Brain Injury ◽  
Fatal Outcome ◽  
Occipital Lobe ◽  
Apache Ii Score ◽  
Net Benefit ◽  
Clinical Value ◽  
Novel Model

BACKGROUND: Patients with severe traumatic brain injury (sTBI) often presents with extracranial injuries, which may contribute to fatal outcome. The aim of this study was to construct the best death prediction model for sTBI and provide a feasible basis for early prognosis. METHODS: A retrospective study from the First Affiliated Hospital of Guangxi Medical University from January 2012 to September 2020 was performed. Relevant risk factors at admission and record survival were collected at discharge. Logistic regression was used to establish a death prediction model. The performance of the model was predicted by fitting goodness test and calculating the area under the ROC curve (AUC). The DCA curve was used to show the net benefit rate of patients. RESULTS: Of the 190 patients with sTBI, 91 died during hospitalization, with a mortality rate of 47.8 percent. Pupillary dilation, occipital lobe injury, SAH, cerebral hernia, and APACHE II score could predict the probability of death alone, with AUC of 0.636, 0.595, 0.611, 0.599 and 0.621 respectively. The AUC of death prediction for patients with sTBI was 0.860, and its sensitivity and specificity were 88.60% and 81.60%. The calibration and decision curve analysis (DCA) were conducted to validate the performance and clinical value of the novel model. CONCLUSIONS: The clinic-radiomic model incorporating both clinical factors and radiomic signature showed good performance for mortality risk prediction of sTBI. The predictive model can identify sTBI with high sensitivity and can be applied in patients with sTBI.

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