External Validation of CRASH Prognostic Model in an Urban Tertiary Care Public University Hospital
Year: 2025
Type: article
Study design: Observational Study
Abstract: INTRODUCTION: Trauma represents 9% of global mortality, where traumatic brain injuries are the leading cause in low-middle income countries, most commonly due to road traffic injuries. The multicenter randomized controlled trial CRASH (corticosteroid randomization after significant head injury) published a prediction model to estimate prognosis in traumatic brain injury patients. This prediction model was derived based on data from high-, low-, and middle-income countries. The external validity of this prediction model was not assessed in low and middle-income countries. To fill this gap, we aim to external validate the CRASH prediction model in traumatic brain injury (TBI) patients in India, a lower-middle-income country. METHODS: We conducted a prospective observational study at the General Surgery department of an urban tertiary care hospital in India. We collected data on the 14-d mortality and 6-mo unfavorable outcomes in patients with TBI. Calibration and discrimination of the CRASH models (basic and computed tomography [CT] model) comparing the observed and predicted outcomes using logistic regression, and area under the curve was analyzed to validate the model. RESULTS: In this study, 417 patients with the median age of 40 y and age range of 18-95 y were evaluated. There was no significant difference between the calibration of the models in prediction of a 14-d mortality (basic P = 0.082, CT P = 0.067) and 6-mo unfavorable outcome (basic P = 0.688, CT P = 0.204). The area under the receiver operating characteristic curve in basic and CT models in prediction of 14-d mortality were 0.885 and 0.885 respectively. In addition, the area under the receiver operating characteristic curve in basic and CT models in prediction of 6-mo unfavorable outcome were 0.901 and 0.896, respectively. CONCLUSIONS: The results of this study showed that the CRASH basic and CT model both accurately predict 14 d mortality and 6 mo unfavorable outcomes of TBI patients in an urban tertiary care public university hospital in India.
Source: Journal of Surgical Research
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,590
OpenAlex ID: W4409672670
