Outcomes of Traumatic Brain Injury and External Validation of CRASH Prognostic Model in a Tertiary Care Public University Hospital

Introduction As per World Health Organization (WHO) 2015 report, road injury is the tenth cause of mortality in the world[1]. 90% of these occur in Low and Middle-Income countries (LMICs)[2]. The complex interaction of human, vehicle and environmental factors along with lack of sustainable preventive programs has contributed to this 'silent epidemic' of injuries. Amongst Injuries, Traumatic Brain Injuries is the leading cause of morbidity and mortality.

The young working men of age 20-40 years are the most vulnerable group to suffer a Traumatic Brain Injury[3]. Around 60% of those with TBI do not resume work[3]. A study done in Delhi, India showed that patients with severe TBI who were unconscious at discharge, 50% of them died at six months and another 30% remained in vegetative state[4].

Clinicians have to answer about the prognosis of the injured patient to the anxious near ones on arrival as well as throughout the course of treatment. Researches have shown prognostic models are statistical models that combine data from patients to predict outcome are likely to be more accurate than simple clinical predictions[5]. A multicenter randomized control trial published a prediction model for traumatic brain injury patients[6]. Unlike other prediction models this model was based on data from High Income and Low Middle-Income Countries. However, the external validation of this prediction model was not done in LMICs data[7]. Hence to fill this gap we aim to study the outcome of patients with Traumatic Brain Injury and also validate the CRASH trial prediction model in traumatic brain injury patient. e.g. A 45 year old male , came with road traffic accident leading to traumatic brain injury. His Glasgow Coma Scale was E4V4M5, both the pupils reacting to light and CT scan brain suggestive of Sub-dural hematoma of thickness approximately 3 mm along left basi-frontal superior and middle frontal convexities without significant underlying mass effect. These details inserted in CRASH PROGNOSTIC MODEL calculator as shown below. As per this the mortality at 14 day is 4.4% and morbidity at 6th month is 12.6% i.e. unfavorable outcome.

Data collection Data collection will be done by a resident and a medical student of the same hospital. Patients will be prospectively followed in the ward till discharge or death. Information will be entered in the case record form based on patients file. Written, valid informed consent will be taken to follow up patients on day 14th day and 6 months after the date of injury by telephonic conversation.

Outcomes: