Traumatic brain injury (TBI) represents a growing global public health issue, particularly in rapidly industrializing and urbanizing countries where the frequency of road traffic accidents (RTAs) continues to rise making them a principal cause of head trauma. As Hippocrates once observed, “No head injury is so minor as to be neglected, nor so serious as to be disregarded.” The majority of TBI cases occur among young adults in their most productive years, resulting in substantial social and economic consequences for families and society at large [1]. TBI is defined as an alteration in brain function or evidence of brain pathology due to an external mechanical force, such as a direct impact or acceleration–deceleration injury. It is broadly categorized into primary injury, which occurs at the moment of impact, and secondary injury, which develops subsequently from processes like cerebral edema, intracranial hemorrhage, or ischemia [3]. Despite significant progress in trauma and critical care, TBI remains one of the foremost causes of mortality and long-term disability among individuals below 40 years of age, and it is anticipated to become one of the top contributors to global disease burden by 2030 [4,5]. According to the World Health Organization, nearly 90% of injury-related deaths are reported from low- and middle-income countries (LAMICs), where prehospital care and rehabilitation facilities are often limited [6,7]. In India alone, an estimated 1.5–2 million people sustain TBI annually, leading to approximately one million deaths each year [8,9]. Over the past decade, the advent of rapid neuroimaging has transformed the diagnosis and management of craniocerebral trauma. Computed Tomography (CT) plays a central role in the early evaluation of TBI, enabling timely diagnosis, assessment of injury severity, and detection of life-threatening complications [10,11]. While the Glasgow Coma Scale (GCS) remains a cornerstone for clinical evaluation, it may not adequately reveal subtle or evolving intracranial injuries, highlighting the importance of adjunctive neuroimaging [12–14]. Owing to its rapid acquisition, widespread availability, and ability to detect acute hemorrhages, fractures, and space-occupying lesions, CT continues to serve as the gold standard for acute head trauma assessment [15]. Although CT has inherent limitations in visualizing diffuse axonal injuries and early ischemic changes, advances in scanner technology have improved image quality and speed, greatly enhancing emergency neurotrauma care [16-18]. The present study is designed to assess the diagnostic and prognostic utility of CT in patients with acute head injuries, examine its correlation with GCS scores, and evaluate its influence on clinical and surgical decision-making.

Following approval from the Institutional Ethics Committee, this cross-sectional observational study was carried out in the Department of Radiodiagnosis at Sri Rawatpur Sarkar Institute of Medical Sciences, Naya Raipur over a period of 15-months and included patients who presented with head trauma and underwent Computed Tomography (CT) evaluation. A total of 100 participants were recruited for the study. The sample size was determined using an effect size of 0.40, a confidence level of 95%, and a statistical power of 80%, ensuring adequate representation and analytical reliability. This sample size was practical given the department’s steady inflow of trauma cases, averaging 10–15 patients per month requiring CT head scans. Informed written consent was obtained from each patient or, when applicable, from their legally authorized representative before enrolment in the study. Inclusion Criteria • Patients presenting with craniocerebral trauma who underwent CT head examination during the study period. Exclusion Criteria • Individuals who declined to provide informed consent. • Patients in whom CT imaging was contraindicated. Imaging Methodology All eligible participants underwent non-contrast Computed Tomography (CT) of the head using a CT machine - CANON Aquilion Start 32 slice CT. Scans were acquired with the patient positioned supine and properly immobilized to prevent motion artifacts. Both bone and brain window settings were utilized to allow detailed assessment of: • Skull fractures • Intracranial hemorrhages (epidural, subdural, subarachnoid, and intracerebral) • Cerebral edema • Midline shift Clinical Assessment and Data Collection Each participant’s clinical information was documented at presentation using a predesigned proforma. The collected data included demographic details (age and sex), clinical history, Glasgow Coma Scale (GCS) score, and CT imaging findings. Special attention was directed toward identifying and quantifying midline shift on CT scans, which was subsequently correlated with GCS scores to evaluate the severity and prognosis of the injury. This systematic data collection provided a comprehensive clinical and radiological overview for each patient. Statistical Analysis Data were organized in Microsoft Excel 2010 and analyzed using IBM SPSS Statistics version 26.0. Descriptive statistics summarized the dataset, with mean and standard deviation (SD) calculated for continuous variables and frequencies with percentages for categorical variables. Inferential analysis was performed using the Chi-square test to determine associations between categorical variables. The correlation between continuous variables such as GCS score and midline shift was analyzed using Pearson’s or Spearman’s correlation coefficients, depending on the normality of data distribution. Results were illustrated through scatter plots, and a p-value of less than 0.05 was considered statistically significant.

The study included 100 patients diagnosed with craniocerebral trauma. The majority of cases (51%) were observed in the 31–50 years age range, accounting for about half of the study population. Males represented 80% of the total cases, reflecting their higher involvement in outdoor activities, occupational exposure, and road traffic. Among the clinical manifestations, headache (52%) and loss of consciousness (47%) were the most frequent symptoms, both indicative of significant neurological disturbance. Vomiting (20%), seizures (7%), and ear bleeding (2%) were also noted, though less commonly. Road traffic accidents (RTAs) were identified as the leading cause of injury, responsible for 60% of the cases, followed by falls from height (22%) and physical assaults (13%). These findings highlight the continued need for effective road safety measures and improved trauma management infrastructure. CT scan evaluation revealed that skull fractures (40%), cerebral edema (37%), and epidural hemorrhage (33%) were the most frequent findings. Other intracranial lesions such as subdural hematoma, contusions, and intracerebral hemorrhage were also present. Less frequent but severe pathologies included diffuse axonal injury (9%), intraventricular hemorrhage (8%), and cerebral infarction (3%), demonstrating the varied spectrum of TBI patterns. Regarding treatment, 24% of patients underwent surgical procedures, while the majority were managed conservatively. In terms of outcomes, 70% of patients made a complete recovery, 16% showed partial neurological improvement, and 14% succumbed to their injuries, underscoring the life-threatening nature of TBI. In summary, the results indicate that middle-aged males involved in RTAs represent the most vulnerable group for craniocerebral trauma. CT imaging remains indispensable for rapid diagnosis, determining injury severity, assessing prognosis, and guiding both surgical and conservative management strategies. [Table 1] Table 1: Distribution of Study Population Based on Demographic, Clinical, and Radiological Parameters (N = 100) Parameter Category Frequency Percentage (%) Age Group (Years) 1–10 2 2.0 11–20 5 5.0 21–30 22 22.0 31–40 25 25.0 41–50 26 26.0 51–60 10 10.0 61–70 8 8.0 71–80 2 2.0 Gender Male 80 80.0 Female 20 20.0 Complications Headache 51 51.0 Loss of Consciousness 49 49.0 Vomiting 21 21.0 Seizures 8 8.0 Ear Bleed 2 2.0 Mode of Injury Road Traffic Accident 60 60.0 Fall from Height 22 22.0 Blunt/Assault 14 14.0 Other 4 4.0 CT Findings Fracture 42 42.0 Edema 38 38.0 Epidural Hemorrhage (EDH) 35 35.0 Subdural Hemorrhage (SDH) 21 21.0 Contusion 21 21.0 Intracerebral Hemorrhage 20 20.0 Subarachnoid Hemorrhage 12 12.0 Diffuse Axonal Injury 9 9.0 Intraventricular Hemorrhage 9 9.0 Infarcts 3 3.0 Surgical Intervention Not Required 76 76.0 Required 24 24.0 Outcome Complete Recovery 69 69.0 Improved 17 17.0 Death 14 14.0 The correlation analysis showed a strong, statistically significant inverse relationship between the Glasgow Coma Scale (GCS) score and the degree of midline shift seen on CT imaging. A Pearson’s correlation coefficient of –0.800 indicated that patients with lower GCS scores (reflecting greater neurological impairment) had larger midline shifts, signifying more severe intracranial pathology. [Figure 1] Further analysis demonstrated that both age and GCS score were significantly associated with the severity of midline shift, whereas gender showed no significant relationship. Patients aged 60 years or older exhibited a markedly higher incidence of >5 mm midline shift, indicating more extensive brain injury than younger individuals (p = 0.000). Likewise, 70% of patients with severe GCS scores (3–8) had >5 mm shifts, reinforcing the correlation between neurological severity and radiological findings (p = 0.000). Gender differences were statistically insignificant (p = 0.310). [Table 2] Table 2: Association Between Midline Shift Grade and Demographic & Clinical Variables (N = 100) Variable Category No Shift ≤5 mm Shift >5 mm Shift Total p-value Age Group < 60 years 55 (61.0%) 22 (24.4%) 13 (14.6%) 90 0.000 (Sig) ≥ 60 years 1 (10.0%) 5 (50.0%) 4 (40.0%) 10 Total 56 (56.0%) 27 (27.0%) 17 (17.0%) 100 Gender Female 10 (50.0%) 7 (35.0%) 3 (15.0%) 20 0.310 (NS) Male 46 (57.5%) 20 (25.0%) 14 (17.5%) 80 Total 56 (56.0%) 27 (27.0%) 17 (17.0%) 100 GCS Score Mild (13–15) 49 (68.0%) 21 (29.0%) 2 (3.0%) 72 0.000 (Highly Sig) Moderate (9–12) 6 (35.0%) 3 (18.0%) 8 (47.0%) 17 Severe (3–8) 1 (7.0%) 3 (23.0%) 9 (70.0%) 13 Total 56 (56.0%) 27 (27.0%) 17 (17.0%) 100 *Chi square test; P value<0.05 was considered statistically significant The outcome analysis revealed that younger patients (<60 years), female gender, higher GCS scores, and absence of midline shift were all significantly associated with better recovery (p < 0.05). Patients with mild GCS (13–15) achieved a 90% recovery rate, while those with severe GCS (3–8) experienced an 83% mortality rate. A midline shift >5 mm was a strong predictor of poor prognosis, with 61% mortality observed in this group. Radiological findings such as fractures, contusions, subdural and epidural hemorrhage, subarachnoid hemorrhage, diffuse axonal injury, cerebral edema, intraventricular hemorrhage, and intracerebral hemorrhage were all significantly associated with higher mortality and poorer outcomes (p < 0.05). Cerebral infarcts, however, showed no significant correlation with outcome (p = 0.070). Table 3: Association Between Demographic, Clinical, and Radiological Variables and Outcomes (N = 100) Variable Category Complete Recovery (%) Improved (%) Death (%) p-value Age < 60 years 78.0 10.0 12.0 0.000 ≥ 60 years 0.0 68.0 32.0 0.000 Gender Female 82.0 3.0 15.0 0.023 Male 66.0 20.0 14.0 0.023 GCS Score Mild (13–15) 90.0 10.0 0.0 0.000 Moderate (9–12) 26.0 63.0 11.0 0.000 Severe (3–8) 3.0 14.0 83.0 0.000 Midline Shift No Shift 95.0 3.0 2.0 0.000 ≤5 mm 60.0 32.0 8.0 0.000 >5 mm 3.0 36.0 61.0 0.000 CT Findings Fracture – Absent 82.0 13.0 5.0 0.000 Fracture – Present 51.0 23.0 26.0 0.000 Contusion – Absent 78.0 12.0 10.0 0.000 Contusion – Present 36.0 36.0 28.0 0.000 SDH – Absent 78.0 13.0 9.0 0.000 SDH – Present 36.0 33.0 31.0 0.000 EDH – Absent 82.0 13.0 5.0 0.000 EDH – Present 46.0 24.0 30.0 0.000 SAH – Absent 74.0 12.0 14.0 0.000 SAH – Present 29.0 55.0 16.0 0.000 DAI – Absent 74.0 18.0 8.0 0.000 DAI – Present 22.0 6.0 72.0 0.000 IVH – Absent 72.0 15.0 13.0 0.031 IVH – Present 41.0 36.0 23.0 0.031 Edema – Absent 91.0 7.0 2.0 0.000 Edema – Present 33.0 34.0 33.0 0.000 ICH – Absent 77.0 11.0 12.0 0.000 ICH – Present 37.0 41.0 22.0 0.000 Infarcts – Absent 70.0 16.0 14.0 0.070 Infarcts – Present 50.0 50.0 0.0 0.070 Overall, the findings reinforce that increasing age, low GCS scores, and greater midline shift are powerful predictors of poor outcomes in traumatic brain injury. Radiological features, particularly diffuse axonal injury, cerebral edema, and intracranial hemorrhages, are strongly associated with mortality. These results highlight the critical value of early CT imaging and neurological assessment in prognostication and management planning for TBI patients.

Traumatic Brain Injury (TBI) remains a critical contributor to morbidity and mortality worldwide, particularly affecting young and middle-aged adults who form the most active and productive segment of the population. The current study, conducted in the Department of Radiodiagnosis at Sri Aurobindo Medical College & PG Institute, Indore, evaluated 100 patients with craniocerebral trauma, providing valuable insights into their clinical profile, CT imaging findings, and prognostic indicators, with special emphasis on the correlation between Glasgow Coma Scale (GCS) scores, midline shift, and outcomes. In this study, the mean age of patients was 38.54 ± 13.44 years, with the majority belonging to the 31–50-year age group (51%), confirming that TBI predominantly affects the working-age population. This observation parallels findings from Yattoo GH et al. [16], Kirankumar MR et al. [17], Bhole AM et al. [18], and Arvind K et al. [20], all of whom reported a peak TBI incidence between 20 and 50 years. The higher vulnerability of this group can be attributed to increased exposure to road travel, industrial work, and recreational risks. A marked male predominance (80%) was observed, consistent with the global trend that men are more frequently involved in accidents and outdoor occupations. Similar gender distributions were reported by Chaurasia AK et al. [21]. Agrawal D et al. [22] and Emejulu et al. [23], where males accounted for over 70% of TBI cases. The higher male involvement reflects riskier behavior patterns, including non-compliance with traffic laws, alcohol use, and occupational hazards. Clinically, headache (52%) and loss of consciousness (47%) were the most common presenting complaints, followed by vomiting (20%), seizures (7%), and ear bleeding (2%). These findings align with Kirankumar MR et al. [17], Bhole AM et al. [18] and Gupta P et al. [24], who reported similar trends in symptom distribution. The presence of headache and loss of consciousness as early manifestations underscores the need for prompt neurological assessment in all head injury patients, even in apparently mild cases. Road traffic accidents (RTAs) were the leading cause of injury (60%), followed by falls (22%) and assaults (13%). This pattern mirrors data from Yattoo GH et al. [16], Krishnakumar MR et al. [17], Rahman MA et al. [25], and Kumar NB et al. [26], who found RTAs—particularly involving two-wheelers—as the predominant mechanism of injury. The continued predominance of RTA-related TBI highlights the urgent need for improved road infrastructure, strict helmet and seatbelt enforcement, and public awareness campaigns on traffic safety. CT scan evaluation revealed that the most common findings were skull fractures (42%), cerebral edema (38%), and epidural hemorrhage (33%). Other intracranial lesions included subdural hematoma (21%), contusions (21%), and intracerebral hemorrhage (20%). Severe lesions such as diffuse axonal injury (9%), intraventricular hemorrhage (9%), and infarcts (3%) were less frequent but carried significant prognostic implications. These observations are consistent with the imaging findings reported by Yattoo GH et al. [17], Krishnakumar MR et al. [16] and Bhole AM et al. [18], where fractures, hemorrhages, and cerebral edema were the predominant CT abnormalities. In the present study, most patients (76%) were managed conservatively, while 24% required surgical intervention, mainly for space-occupying hematomas or mass effect. This proportion is comparable to that reported by Yattoo GH et al. [16] and Gupta P et al. [24], who emphasized conservative management for mild cases and surgery for moderate-to-severe injuries. Outcome assessment revealed that 70% of patients made a complete recovery, 16% showed partial improvement, and 14% succumbed to their injuries. These results indicate that despite advances in imaging and care, mortality in severe TBI remains substantial. The findings are comparable to those of Krishnakumar MR et al. [17], Bhole AM et al. [18], and Munakomi et al. [28], who demonstrated a clear correlation between mortality and injury severity. A significant inverse correlation was found between GCS scores and midline shift (r = –0.800, p < 0.001), indicating that patients with lower GCS values had greater midline shifts on CT. Furthermore, the analysis demonstrated that increasing age and worsening neurological status were strongly associated with more severe midline shift (p = 0.000), whereas gender showed no significant relationship (p = 0.310). Among patients aged ≥60 years, 40% exhibited a >5 mm midline shift, compared to only 14.6% in younger individuals. Similarly, 70% of severely injured patients (GCS 3–8) had a >5 mm shift, confirming the relationship between intracranial mass effect and neurological deterioration. Outcome analysis further revealed that younger age (<60 years), female gender, higher GCS scores, and absence of midline shift were significantly associated with favorable recovery (p < 0.05). Patients with mild TBI (GCS 13–15) had a 90% recovery rate, while 83% of patients with severe TBI (GCS 3–8) died. A midline shift >5 mm was the strongest radiological predictor of mortality, with 61% of patients in this group succumbing to their injuries. Similar findings were reported by Chaurasia AK et al. [21] and Chiewvit P et al. [29], who identified midline shift as a critical prognostic factor. Among CT parameters, diffuse axonal injury, cerebral edema, subdural hemorrhage, and intracerebral hemorrhage were significantly associated with poor outcomes (p < 0.05). In contrast, cerebral infarcts did not show a statistically significant association (p = 0.070). These observations underscore that both clinical severity (GCS) and radiological parameters (midline shift and lesion type) are vital for prognostication and management. Similar findings were reported by Chiewvit P et al. [29] and Ting HW et al. [30]. Overall, this study reinforces that middle-aged males involved in RTAs represent the most at-risk group for TBI, and that CT imaging combined with GCS evaluation provides an effective and rapid framework for assessing severity, predicting outcomes, and planning interventions. The findings also highlight the necessity for preventive strategies focused on road safety and early intervention protocols. However, limitations of this study include its single-center design, modest sample size, and lack of long-term follow-up. Furthermore, reliance on CT imaging alone may underestimate subtle diffuse injuries that are better detected by MRI. Future multicentric studies with larger samples, advanced imaging modalities, and longitudinal follow-up are warranted to validate these findings and enhance the prognostic accuracy in TBI management.

The study underscores the importance of integrating clinical and radiological assessment in the evaluation and management of traumatic brain injury. A strong negative correlation between GCS scores and midline shift confirms that combined assessment improves prognostic accuracy. Features such as diffuse axonal injury, cerebral edema, and midline shift >5 mm were powerful indicators of poor outcome, while mild injuries without shift showed excellent recovery. These results emphasize the need for early CT-based evaluation, prompt risk stratification, and individualized management to improve survival and neurological recovery in TBI patients.

1. Anil Kumar Bansal, Gupta AK. Utility of CT in Head Injury- A Prospective Study. AJMRR.2020;8(1):64-8. 2. Ahmed S, Venigalla H, Mekala HM, Dar S, Hassan M, Ayub S. Traumatic Brain Injury and Neuropsychiatric Complications. Indian J Psychol Med. 2017;39(2):114-121. 3. Shetty SP, Chandrappa A, Das SK, Sen KK, Kini DV. Evaluation of Sequential Head Computed Tomography in Traumatic Brain Injuries. Cureus. 2022 Aug 8;14(8):e27772. 4. Geneva: WHO; 2003. World Health Organization. World Health Report 2003-Shaping the Future. 5. Fleminger S, Ponsford J. Long term outcome after traumatic brain injury. BMJ. 2005;331:1419–20. 6. Murray CJ, Lopez AD. Cambridge (MA): Harvard University Press; 1996. Global health statistics: A compendium of incidence prevalence and mortality estimates for over 200 conditions. 7. Lopez AD, Murray CJ. Cambridge (MA): Harvard University Press; 1996. The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020. 8. Gururaj G. Epidemiology of traumatic brain injuries: Indian scenario. Neurol Res. 2002;24:24–8. 9. Gururaj G. New Delhi: National Commission on Macroeconomics and Health, Ministry of Health and Family Welfare, Government of India; 2005. Injuries in India: A National Perspective. Background Papers: Burden of Disease in India Equitable Development-Healthy Future; pp. 325–47. 10. Udstuen GJ, Claar JM. Imaging of acute head injury in the adult. Semin Ultrasound CT MR. 2001;22:135–147. 11. Lee B, Newberg A. Neuroimaging in traumatic brain imaging. NeuroRx. 2005 Apr;2(2):372-83. 12. Beatrice M. Magnusson, Emil Isaksson & Lars-Owe D. Koskinen , A prospective observational cohort study of traumatic brain injury in the northern region of Sweden, Brain Injury,2022; 36:2, 191-198. 13. Hyder AA, Wunderlich CA, Puvanachandra P, Gururaj G, Kobusingye OC. The impact of traumatic brain injuries: A global perspective. Neuro Rehabilitation. 2007;22(5):341–353. 14. Nayebaghayee H, Afsharian T. Correlation between Glasgow Coma Scale and brain computed tomography-scan findings in head trauma patients. Asian J Neurosurg. 2016;11(1):46–46. 15. Rathaur SK, UPADHYAY P et al. Role of computed tomography in traumatic head injury evaluation. IP Journal of Otorhinolaryngology and Allied Science 2022;5(1):7–9 16. Yattoo GH, Tabish SA, Afzal WM, Kirmani A. Factors influencing outcome of head injury patients at a tertiary care teaching hospital in India. Int J Health Sci (Qassim) 2009;3:59 62. 17. Kirankumar MR, Satri V, Satyanarayana V, Ramesh Chandra VV, Madhusudan M, Sowjanya J. Demographic profile, clinical features, imaging and outcomes in patients with traumatic brain injury presenting to emergency room. J Clin Sci Res 2019;8:132-6. 18. Bhole AM, Potode R, Agarwal A, Joharapurkar S. Demographic profile, clinical presentation, management options in cranio cerebral trauma: An experience of a rural hospital in central India. Pak J Med Sci 2007;23:5. 19. Shivakumar BC, Srivastava PC, Shantakumar HP. Pattern of head injuries in mortality due to road traffic accidents involving two wheelers. J Indian Acad Forensic Med 2010:32;239 42. 20. Arvind K, Sanjeev L, Deepak A, Ravi R, Dogra TD. Fatal road traffic accidents and their relationship with head injuries: An epidemiological survey of five years. Indian J Neurotrauma 2008;5:63 7. 21. Chaurasia AK, Dhurve L, Gaur R, Kori R, Ahmad AK. A study of correlation of degree of midline shift on computed tomography scan and Glasgow coma scale in patients of acute traumatic head injury. Int Surg J 2021;8:3075-80 22. Agrawal D, Ahmed S, Khan S, Gupta D, Sinha S, Satyarthee GD. Outcome in 2068 patients of head injury: Experience at a level 1 trauma centre in India. Asian J Neurosurg. 2016;11(2):143-5 23. Emejulu JKC, Isiguzo CM, Agbasoga CE, Ogbuagu CN. Traumatic Brain Injury in the Accident and Emergency Department of a Tertiary Hospital in Nigeria. East and Central Afr J Surg. 2010;15(2) 24. Gupta P, Singh J, Sharma A, Deen S, Chaudhary A, Bhansal N, et al. Epidemiological analysis and clinical characteristics of traumatic brain injuries in rural Jaipur: The first single centre experience. J Evid Based Med Healthc 2015;2:8686 91. 25. Rahman MA, Ramazan. Patterns of head injuries (cranio cerebral) in road traffic accidents in Riyadh region of KSA. Dinajpur Med Coll J 2015;8:195-9. 26. Kumar NB, Ghormade PS, Tingne CV, Keoliya AN. Trends of fatal road traffic accidents in central India. J Forensic Med Sci Law 2013;22:1 8. 27. Tandle RM, Keoliya AN. Patterns of head injuries in fatal road traffic accidents in a rural district of Maharashtra autopsy based study. JIndian Acad Forensic Med 2011;33:228 31. 28. Munakomi S. A comparative study between Marshall and Rotterdam CT scores in predicting early deaths in patients with traumatic brain injury in a major tertiary care hospital in Nepal. Chin J Traumatol 2016;19:25 7. 29. Chiewvit P, Tritakarn S, Nanta-aree S, Suthipongchai S. Degree of midline shift from CT scan predicted outcome in patients with head injuries. J Med Assoc Thailand. 2010;93(1):99-107 30. Ting HW, Chen MS, Hsieh YC, Chan CL. Good mortality prediction by Glasgow Coma Scale for neurosurgical patients. J Chin Med Assoc 2010;73:139 43.