Validation of CRASH Model in Prediction of 14-day Mortality and 6-month Unfavorable Outcome of Head Trauma Patients
Archives of Academic Emergency Medicine,
Vol. 4 No. 4 (2016),
1 November 2016
,
Page 196-201
https://doi.org/10.22037/aaem.v4i4.250
Abstract
Introduction: To date, many prognostic models have been proposed to predict the outcome of patients withtraumatic brain injuries. External validation of these models in different populations is of great importance
for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic
model in prediction of 14-day mortality (14-DM) and 6-month unfavorable outcome (6-MUO) of patients with
traumatic brain injury. Methods: In the present prospective diagnostic test study, calibration and discrimination
of CRASH model were evaluated in head trauma patients referred to the emergency department. Variables
required for calculating CRASH expected risks (ER), and observed 14-DM and 6-MUO were gathered. Then ER
of 14-DM and 6-MUO were calculated. The patients were followed for 6 months and their 14-DM and 6-MUO
were recorded. Finally, the correlation of CRASH ER and the observed outcome of the patients was evaluated.
The data were analyzed using STATA version 11.0. Results: In this study, 323 patients with the mean age of 34.0
´s 19.4 years were evaluated (87.3% male). Calibration of the basic and CT models in prediction of 14-day and
6-month outcome were in the desirable range (P Ç 0.05). Area under the curve in the basic model for prediction
of 14-DM and 6-MUO were 0.92 (95% CI: 0.89–0.96) and 0.92 (95% CI: 0.90–0.95), respectively. In addition,
area under the curve in the CT model for prediction of 14-DM and 6-MUO were 0.93 (95% CI: 0.91–0.97) and
0.93 (95% CI: 0.91–0.96), respectively. There was no significant difference between the discriminations of the
two models in prediction of 14-DM (p Æ 0.11) and 6-MUO (p Æ 0.1). Conclusion: The results of the present
study showed that CRASH prediction model has proper discrimination and calibration in predicting 14-DMand
6-MUO of head trauma patients. Since there was no difference between the values of the basic and CT models,
using the basic model is recommended to simplify the risk calculations.
- Prognosis
- head injuries
- closed
- multiple trauma
- patient outcome assessment
- decision support techniques
How to Cite
References
Bruns J, Hauser WA. The epidemiology of traumatic brain injury: a review. Epilepsia. 2003;44(s10):2-10.
Kumar A, Lalwani S, Agrawal D, Rautji R, Dogra T. Fatal road traffic accidents and their relationship with head injuries: An epidemiological survey of five years. The Indian Journal of Neurotrauma. 2008;5(2):63-7.
Montazeri A. Road-traffic-related mortality in Iran: a descriptive study. Public health. 2004;118(2):110-3.
Majdzadeh R, Khalagi K, Naraghi K, Motevalian A, Eshraghian MR. Determinants of traffic injuries in drivers and motorcyclists involved in an accident. Accident Analysis & Prevention. 2008;40(1):17-23.
Bigler ED, Weiner M, Lipton A. Traumatic brain injury. Textbook of Alzheimer Disease and Other Dementias. 2009:229-46.
Ghajar J. Traumatic brain injury. The Lancet. 2000;356(9233):923-9.
Maegele M, Engel D, Bouillon B, Lefering R, Fach H, Raum M, et al. Incidence and outcome of traumatic brain injury in an urban area in Western Europe over 10 years. European Surgical Research. 2007;39(6):372-9.
Thurman DJ, Alverson C, Dunn KA, Guerrero J, Sniezek JE. Traumatic brain injury in the United States: a public health perspective. The Journal of head trauma rehabilitation. 1999;14(6):602-15.
Kövesdi E, Lückl J, Bukovics P, Farkas O, Pál J, Czeiter E, et al. Update on protein biomarkers in traumatic brain injury with emphasis on clinical use in adults and pediatrics. Acta neurochirurgica. 2010;152(1):1-17.
Maas AI, Marmarou A, Murray GD, Teasdale SGM, Steyerberg EW. Prognosis and clinical trial design in traumatic brain injury: the IMPACT study. Journal of neurotrauma. 2007;24(2):232-8.
Menon D, Harrison D. Prognostic modelling in traumatic brain injury. BMJ. 2008;336(7641):397-8.
Steyerberg EW, Mushkudiani N, Perel P, Butcher I, Lu J, McHugh GS, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS medicine. 2008;5(8):e165.
Young NH, Andrews PJ. Developing a prognostic model for traumatic brain injury—a missed opportunity? PLoS medicine. 2008;5(8):e168.
Collaborators MCT, Perel P, Arango M, Clayton T, Edwards P, Komolafe E, et al. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. Bmj. 2008;336(7641):425-9.
Honeybul S, Ho KM, Lind CR, Gillett GR. Observed versus predicted outcome for decompressive craniectomy: a population-based study. Journal of neurotrauma. 2010;27(7):1225-32.
Lingsma H, Andriessen TM, Haitsema I, Horn J, van der Naalt J, Franschman G, et al. Prognosis in moderate and severe traumatic brain injury: external validation of the IMPACT models and the role of extracranial injuries. Journal of trauma and acute care surgery. 2013;74(2):639-46.
Majdan M, Lingsma HF, Nieboer D, Mauritz W, Rusnak M, Steyerberg EW. Performance of IMPACT, CRASH and Nijmegen models in predicting six month outcome of patients with severe or moderate TBI: an external validation study. Scandinavian journal of trauma, resuscitation and emergency medicine. 2014;22(1):68.
Roozenbeek B, Lingsma HF, Lecky FE, Lu J, Weir J, Butcher I, et al. Prediction of outcome after moderate and severe traumatic brain injury: external validation of the IMPACT and CRASH prognostic models. Critical care medicine. 2012;40(5):1609-17.
Wong GKC, Teoh J, Yeung J, Chan E, Siu E, Woo P, et al. Outcomes of traumatic brain injury in Hong Kong: Validation with the TRISS, CRASH, and IMPACT models. Journal of Clinical Neuroscience. 2013;20(12):1693-6.
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