External Validation of the CRASH and IMPACT Prognostic Models in Severe Traumatic Brain Injury

2014 ◽  
Vol 31 (13) ◽  
pp. 1146-1152 ◽  
Author(s):  
Julian Han ◽  
Nicolas K.K. King ◽  
Sam J. Neilson ◽  
Mihir P. Gandhi ◽  
Ivan Ng
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
External Validation ◽  
Prognostic Models

scholarly journals External validation of the TRISS, CRASH, and IMPACT prognostic models in severe traumatic brain injury in Japan

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0221791 ◽  
Author(s):  
Yukihiro Maeda ◽  
Rie Ichikawa ◽  
Jimpei Misawa ◽  
Akiko Shibuya ◽  
Teruyoshi Hishiki ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
External Validation ◽  
Prognostic Models

scholarly journals Outcome Prediction after Moderate and Severe Traumatic Brain Injury: External Validation of Two Established Prognostic Models in 1742 European Patients

2020 ◽  
Author(s):  
Simone A. Dijkland ◽  
Isabel R.A. Retel Helmrich ◽  
Daan Nieboer ◽  
Mathieu van der Jagt ◽  
Diederik W.J. Dippel ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Severe Traumatic Brain Injury ◽  
Outcome Prediction ◽  
External Validation ◽  
Prognostic Models

scholarly journals External validation of the rotterdam computed tomography score in the prediction of mortality in severe traumatic brain injury

2017 ◽  
Vol 08 (S 01) ◽  
pp. S023-S026 ◽  
Author(s):  
Jose D. Charry ◽  
Jesus D. Falla ◽  
Juan D. Ochoa ◽  
Miguel A. Pinzón ◽  
Jorman H. Tejada ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Injury Severity ◽  
External Validation ◽  
Public Health Problem ◽  
University Hospital ◽  
Prognostic Models ◽  
Prediction Of Mortality ◽  
Severe Tbi

ABSTRACT Introduction: Traumatic brain injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability in Colombia. Different calculators and prognostic models have been developed to predict the neurological outcomes of these patients. The Rotterdam computed tomography (CT) score was developed for prognostic purposes in TBI. We aimed to examine the accuracy of the prognostic discrimination and prediction of mortality of the Rotterdam CT score in a cohort of trauma patients with severe TBI in a university hospital in Colombia. Materials and Methods: We analyzed 127 patients with severe TBI treated in a regional trauma center in Colombia over a 2-year period. Bivariate and multivariate analyses were used. The discriminatory power of the score, its accuracy, and precision were assessed by logistic regression and as the area under the receiver operating characteristic curve. Shapiro–Wilk, Chi-square, and Wilcoxon tests were used to compare the real outcomes in the cohort against the predicted outcomes. Results: The median age of the patient cohort was 33 years, and 84.25% were male. The median injury severity score was 25, the median Glasgow Coma Scale motor score was 3, the basal cisterns were closed in 46.46% of the patients, and a midline shift of >5 mm was seen in 50.39%. The 6-month mortality was 29.13%, and the Rotterdam CT score predicted a mortality of 26% (P < 0.0001) (area under the curve: 0.825; 95% confidence interval: 0.745–0.903). Conclusions: The Rotterdam CT score predicted mortality at 6 months in patients with severe head trauma in a university hospital in Colombia. The Rotterdam CT score is useful for predicting early death and the prognosis of patients with TBI.

Predicting Outcomes after Severe and Moderate Traumatic Brain Injury: An External Validation of Impact and Crash Prognostic Models in a Large Spanish Cohort

2016 ◽  
Vol 33 (17) ◽  
pp. 1598-1606 ◽  
Author(s):  
Ana M. Castaño-Leon ◽  
David Lora ◽  
Pablo M. Munarriz ◽  
Santiago Cepeda ◽  
Igor Paredes ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
External Validation ◽  
Prognostic Models ◽  
Moderate Traumatic Brain Injury ◽  
Spanish Cohort

scholarly journals Prediction of outcome based on trauma and injury severity score, IMPACT and CRASH prognostic models in moderate-to-severe traumatic brain injury in the elderly

2021 ◽  
Vol 16 (3) ◽  
pp. 500
Author(s):  
DhoniGanesh Siva Rama Krishna Moorthy ◽  
Krishnappa Rajesh ◽  
SarathyManju Priya ◽  
Thaminaina Abhinov ◽  
KalavaguntaJyothiswarapillai Devendra Prasad
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Injury Severity Score ◽  
Severe Traumatic Brain Injury ◽  
Severity Score ◽  
Injury Severity ◽  
The Elderly ◽  
Prognostic Models ◽  
Prediction Of Outcome ◽  
Trauma And Injury

scholarly journals Prognostic Models of Mortality from Accidental Severe Traumatic Brain Injury in Children and Adolescents: A Systematic Review

2021 ◽  
Vol 3 (3(September-December)) ◽  
Author(s):  
Jose Roberto Tude Melo ◽  
Marcelo Liberato Coelho Mendes de Carvalho
Keyword(s):  
Systematic Review ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Children And Adolescents ◽  
Severe Traumatic Brain Injury ◽  
Scientific Evidence ◽  
Prognostic Models ◽  
Evidence Based ◽  
Level Of Evidence ◽  
Severe Tbi

Introduction: Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcomes. Objective: Identify prognostic models of mortality developed and published in the medical literature for possible applicability in children and adolescents victims of severe traumatic brain injury (TBI). Methods: Systematic review in the Medline electronic database (PubMed platform) of scientific articles published from 2006 (year of publication of the last systematic review on prognostic models for TBI before 2017) until July 29, 2017. Results: Ten studies on prognostic models of mortality in children and adolescents victims of severe TBI were identified for final inclusion in the review. There were eight development and two validation studies conducted in different countries. Conclusion: The analysis of this systematic review makes it possible to conclude that the ten prognostic models included in the final sample provide health professionals with a scientific evidence-based understanding of the severity of pediatric victims of severe TBI. This systematic review is classified as presenting 2A and 1 level of evidence (systematic review of homogeneous cohorts), according to the 2009 and 2011 classifications, respectively, of the Oxford Center for Evidence-Based Medicine

IMPACT and CRASH prognostic models for traumatic brain injury: external validation in a South-American cohort

2020 ◽  
Vol 26 (6) ◽  
pp. 546-554
Author(s):  
Kwankaew Wongchareon ◽  
Hilaire J Thompson ◽  
Pamela H Mitchell ◽  
Jason Barber ◽  
Nancy Temkin
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Low Income ◽  
Characteristic Curve ◽  
External Validation ◽  
Prognostic Models ◽  
South American ◽  
Unfavourable Outcome ◽  
Middle Income ◽  
The Impact

ObjectiveTo develop a robust prognostic model, the more diverse the settings in which the system is tested and found to be accurate, the more likely it will be generalisable to untested settings. This study aimed to externally validate the International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization after Significant Head Injury (CRASH) models for low-income and middle-income countries using a dataset of patients with severe traumatic brain injury (TBI) from the Benchmark Evidence from South American Trials: Treatment of Intracranial Pressure study and a simultaneously conducted observational study.MethodA total of 550 patients with severe TBI were enrolled in the study, and 466 of those were included in the analysis. Patient admission characteristics were extracted to predict unfavourable outcome (Glasgow Outcome Scale: GOS<3) and mortality (GOS 1) at 14 days or 6 months.ResultsThere were 48% of the participants who had unfavourable outcome at 6 months and these included 38% who had died. The area under the receiver operating characteristic curve (AUC) values were 0.683–0.775 and 0.640–0.731 for the IMPACT and CRASH models respectively. The IMPACT CT model had the highest AUC for predicting unfavourable outcomes, and the IMPACT Lab model had the best discrimination for predicting 6-month mortality. The discrimination for both the IMPACT and CRASH models improved with increasing complexity of the models. Calibration revealed that there were disagreement between observed and predicted outcomes in the IMPACT and CRASH models.ConclusionThe overall performance of all IMPACT and CRASH models was adequate when used to predict outcomes in the dataset. However, some disagreement in calibration suggests the necessity for updating prognostic models to maintain currency and generalisability.

Sign in / Sign up

Export Citation Format

Share Document