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ORIGINAL ARTICLE
Year : 2020  |  Volume : 17  |  Issue : 1  |  Page : 26-32

Study of risk factors, clinical spectrum, and outcome for head injury in pediatric age group in Western India


Department of General Surgery, Lokmanya Tilak Municipal General Hospital and Medical College, Mumbai, Maharashtra, India

Correspondence Address:
Dr. Gaurav Patel
Department of General Surgery, LTMMC and LTMGH, 1st Floor, College Building, Sion, Mumbai - 400 022, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ajps.AJPS_2_18

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Aim: To study various risk factors which leads to head injury, severity of head injury and to compare survival as predicted by the Revised Trauma Score (RTS) and Pediatric Trauma Score (PTS) in pediatric patients admitted in a tertiary care hospital. Methods: 300 consecutive pediatric patients below 12 years of age with head injury admitted in our institute were analysed as per a set proforma. Data pertaining to patient's demographic details, mode of injury, computed tomography (CT) findings, type of management, severity of head injury, and outcome were recorded. The results were tabulated and analyzed. RTS and PTS scores were calculated to predict the survival of an individual patient. Results: The most commonly affected age group was 1–5 years. Boys outnumbered girls in the incidence. Fall was the most common injury, with road traffic accident being the most common cause of mortality. Skull fracture was the most common CT scan finding. Most of the patients presented with mild head injury (Glasgow Coma Scale 13–15), and they improved with conservative management only. RTS and PTS scores were calculated and were equally effective in predicting the outcome for a particular patient. Conclusion: Head injury occurs more commonly in 1–5 years' age group due to fall from unprotected roof tops. The overall prognosis in majority of the cases is excellent. However, road traffic accident shows the highest mortality and hence, we propose to include mode of injury as a variable for designing future predictive outcome models.


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