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

Han, Julian Xinguang; King, Nicolas Kon Kam; Neilson, Samuel; Gandhi, Mihir; Ng, Ivan

doi:10.1089/neu.2013.3003

Cited by 89 publications

(65 citation statements)

References 22 publications

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“…[8] It has been established as a prognostic model of choice by a number of external validation studies[124142] (including a study on a population which was used for this study),[11] which justifies its use as a gold standard in this paper.…”

Section: Discussionmentioning

confidence: 99%

Outcome Prediction after Traumatic Brain Injury: Comparison of the Performance of Routinely Used Severity Scores and Multivariable Prognostic Models

Majdán

Bražinová

Rusňák

et al. 2017

Journal of Neurosciences in Rural Practice

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Objectives:Prognosis of outcome after traumatic brain injury (TBI) is important in the assessment of quality of care and can help improve treatment and outcome. The aim of this study was to compare the prognostic value of relatively simple injury severity scores between each other and against a gold standard model – the IMPACT-extended (IMP-E) multivariable prognostic model.Materials and Methods:For this study, 866 patients with moderate/severe TBI from Austria were analyzed. The prognostic performances of the Glasgow coma scale (GCS), GCS motor (GCSM) score, abbreviated injury scale for the head region, Marshall computed tomographic (CT) classification, and Rotterdam CT score were compared side-by-side and against the IMP-E score. The area under the receiver operating characteristics curve (AUC) and Nagelkerke's R2 were used to assess the prognostic performance. Outcomes at the Intensive Care Unit, at hospital discharge, and at 6 months (mortality and unfavorable outcome) were used as end-points.Results:Comparing AUCs and R2s of the same model across four outcomes, only little variation was apparent. A similar pattern is observed when comparing the models between each other: Variation of AUCs <±0.09 and R2s by up to ±0.17 points suggest that all scores perform similarly in predicting outcomes at various points (AUCs: 0.65–0.77; R2s: 0.09–0.27). All scores performed significantly worse than the IMP-E model (with AUC > 0.83 and R2 > 0.42 for all outcomes): AUCs were worse by 0.10–0.22 (P < 0.05) and R2s were worse by 0.22–0.39 points.Conclusions:All tested simple scores can provide reasonably valid prognosis. However, it is confirmed that well-developed multivariable prognostic models outperform these scores significantly and should be used for prognosis in patients after TBI wherever possible.

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Section: Discussionmentioning

confidence: 99%

Outcome Prediction after Traumatic Brain Injury: Comparison of the Performance of Routinely Used Severity Scores and Multivariable Prognostic Models

Majdán

Bražinová

Rusňák

et al. 2017

Journal of Neurosciences in Rural Practice

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“…Population variability and the diversity of injury in various clinical studies have prevented clear conclusions about the use of antioxidant therapies with TBI patients (Rapp, Cellucci, Keyser, Gilpin, & Darmon, 2013). The two major studies related to TBI prognosis (the Corticosteroid Randomization After Significant Head Injury and the International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury) have not addressed the underlying TBI causality or pathophysiology (Han, King, Neilson, Gandhi, & Ng, 2014;Roozenbeek et al, 2012). Promising TBI research has identified neuron inflammation and oxidative stress as major factors involved with secondary injury, raising the possibility that antioxidants could alter the clinical progression (Bains & Hall, 2012).…”

Section: Discussionmentioning

confidence: 99%

Systematic Review of Traumatic Brain Injury and the Impact of Antioxidant Therapy on Clinical Outcomes

Shen

Hiebert

Hartwell

et al. 2016

Worldviews Ev Based Nurs

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Background: Traumatic brain injury (TBI) is an acquired brain injury that occurs when there is sudden trauma that leads to brain damage. This acute complex event can happen when the head is violently or suddenly struck or an object pierces the skull or brain. The current principal treatment of TBI includes various pharmaceutical agents, hyperbaric oxygen, and hypothermia. There is evidence that secondary injury from a TBI is specifically related to oxidative stress. However, the clinical management of TBI often does not include antioxidants to reduce oxidative stress and prevent secondary injury.

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“…18 Th ird, several previous studies have shown similar predictive ability of IMPACT and CRASH. 9,10,164,165 Th us, it is highly presumable that CRASH and IMPACT would have equaled in predictive value in the present datasets as well. Fourth, CRASH was not designed to predict 6-month mortality, which may limit its use in observational studies where the possibility of assessing neurological outcome is oft en limited.…”

Section: Trauma C Brain Injury Modelsmentioning

confidence: 60%

Prognostic models in traumatic brain injury

Raj

2015

Acta Anaesthesiol Scand

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Background Prognostic models are important tools for heterogeneity adjustment in traumatic brain injury (TBI). Prognoses after TBI have been particularly challenging to predict, with limited availability of robust prognostic models. TBI patients are by definition trauma patients, and often treated in the intensive care unit (ICU). Several prognostic models for ICU and trauma patients have been developed, although their applicability in patients with TBI is uncertain. Recently, however, some new prognostic models specifically designed for patients with TBI were introduced. Still, the optimal type of prognostic model in TBI remains unknown. Aim This aims to investigate the applicability of different types of prognostic models in patients with TBI and to develop novel models with enhanced performance to previous models, focusing on long‐ term outcome prediction. Methods Four patient databases of patients with TBI treated in the ICU were used to validate three TBI specific models, two computerized tomography (CT) scoring systems, one trauma scoring system, and three intensive care scoring systems. Models were validated by assessing their discrimination using area under the curve (AUC), calibration, and explanatory variation. Logistic regression was used for model customization and development. Models were internally validated using a resample bootstrap technique or a split‐sample technique. Primary outcome was 6‐month mortality and unfavorable neurological outcome by the Glasgow Outcome Scale. 30‐day in‐hospital mortality was used for the trauma scoring system. Results Study populations ranged from 342 to 9915 patients. The TBI models showed the best performance with AUCs between 0.80 and 0.85, followed by the intensive care scoring systems and the CT scores with AUCs between 0.68 to 0.80 and 0.63 to 0.70, respectively. Most models showed poor calibration, although good calibration was achieved following customization. The trauma scoring system exhibited modest to good discrimination (AUC 0.76–0.89) for short‐term mortality prediction but poor calibration. Several new prognostic models, with statistically significant superior performance to previous models were created, among them a combined TBI‐ICU model (‘IMPACT‐APACHE’) and a novel CT scoring system (‘The Helsinki CT score’). Using a TBI‐specific model, based on admission characteristics, up to 40% of the patient's final long‐term outcome could be predicted. Conclusion The TBI models showed superior predictive performance to the intensive care and trauma scoring systems, showing that TBI patients are a highly specific population in the trauma and ICU setting. Thus, the use of a TBI‐specific model is advocated in the setting of TBI. The newly proposed models were found to be significant improvements over previous models, but require external validation to show generalizability.

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

Cited by 89 publications

References 22 publications

Outcome Prediction after Traumatic Brain Injury: Comparison of the Performance of Routinely Used Severity Scores and Multivariable Prognostic Models

Outcome Prediction after Traumatic Brain Injury: Comparison of the Performance of Routinely Used Severity Scores and Multivariable Prognostic Models

Systematic Review of Traumatic Brain Injury and the Impact of Antioxidant Therapy on Clinical Outcomes

Prognostic models in traumatic brain injury

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