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Predicting outcome in traumatic brain injury: Sharing experience of pilot traumatic brain injury registry
Ranabir Pal1, Ashok Munivenkatappa2, Amit Agrawal3, Geetha R Menon4, Sagar Galwankar5, P Rama Mohan6, S Satish Kumar7, BV Subrahmanyam8
1 Department of Community Medicine, Andaman and Nicobar Islands Institute of Medical Sciences, Port Blair, India
2 VDRL Project, National Institute of Epidemiology, ICMR, Chennai, Tamil Nadu, India
3 Department of Neurosurgery, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
4 Department of Health Research (Ministry of Health and Family Welfare), Division of Non-Communicable Diseases, n Council of Medical Research, New Delhi, India
5 Department of Emergency Medicine, University of Florida, Jacksonville, Florida, USA
6 Department of Pharmacology, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
7 Department of Emergency Medicine, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
8 Department of Forensic Medicine, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
Correspondence Address:
Amit Agrawal
Department of Neurosurgery, Narayana Medical College Hospital, Chinthareddypalem, Nellore - 524 003, Andhra Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2229-5151.190650
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Background: A reliable prediction of outcome for the victims of traumatic brain injury (TBI) on admission is possible from concurrent data analysis from any systematic real-time registry.
Objective: To determine the clinical relevance of the findings from our TBI registry to develop prognostic futuristic models with readily available traditional and novel predictors.
Materials and Methods: Prospectively collected data using predesigned pro forma were analyzed from the first phase of a trauma registry from a South Indian Trauma Centre, compatible with computerized management system at electronic data entry and web data entry interface on demographics, clinical, management, and discharge status.
Statistical Analysis: On univariate analysis, the variables with P < 0.15 were chosen for binary logistic model. On regression model, variables were selected with test of coefficient 0.001 and with Nagelkerke R 2 with alpha error of 5%.
Results: From 337 cases, predominantly males from rural areas in their productive age, road traffic injuries accounted for two-thirds cases, one-fourths occurred during postmonsoon while two-wheeler was the most common prerequisite. Fifty percent of patients had moderate to severe brain injury; the most common finding was unconsciousness followed by vomiting, ear bleed, seizures, and traumatic amnesia. Fifteen percent required intracranial surgery. Patients with severe Glasgow coma scale score were 4.5 times likely to have the fatal outcome (P = 0.003). Other important clinical variables accountable for fatal outcomes were oral bleeds and cervical spine injury while imperative socio-demographic risk correlates were age and seasons.
Conclusion: TBI registry helped us finding predictors of clinical relevance for the outcomes in victims of TBI in search of prognostic futuristic models in TBI victims. |
