Background and Objectives: While trauma is currently the second leading cause of death in Saudi Arabia, little statistical information is available about injury rates and related patient outcomes. There is a need to understand trauma epidemiology to determine strategies that can be put in place to prevent and treat such trauma. We aimed to describe trauma rates, types of injuries, demographic distribution of injury and body regions affected by trauma in King Fahad Hospital in the city of Medina. Methods: The study was undertaken in King Fahad Hospital, the first multi-speciality reference hospital in the Medina region and the only trauma centre in the city. We collected retrospective data on all the trauma victims who visited the Emergency Department from 1st January to 31st December 2018. Simple descriptive statistics were calculated. Trauma mortality was compared with trauma scores with Receiver Operator Curves. Results: During the study period, 8793 patients were evaluated, 5846 (66.5%) males. The mean age was 27.5 years. 5608 (64%) were admitted in one of the in-hospital departments and rest were referred to OPD. Traffic-related injuries (4086; 46.5%) and falls (2993; 34%) were the most common causes of injury. Extremities injury (5929; 67.5%) was recorded as the most common body part. From the in-hospital patients, 5077 (90.5%) were discharged home and 167 (3%) died. Considering the mortality prediction accuracy of RTS and NTS. The RTS score of ≤9 had sensitivity and specificity of 90.2% and 90.4%, respectively, in predicting mortality in >5-year-old patients. NTS score of ≤13 had 90% sensitivity and 97.3% specificity in predicting mortality in the age group of 0-5 year-old. Conclusion: This descriptive study is a crucial step in addressing the burden of trauma in Saudi Arabia. Information related to the characteristics of injuries and relevant patient 2 outcomes may assist in further research into possible causal factors. It may contribute to the creation of new protocols in preventing and managing injuries more efficiently.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/32911 |
| Date | 20 February 2021 |
| Creators | Patel, Mohammed Aasfi |
| Contributors | wallis, Lee |
| Publisher | Faculty of Health Sciences, Division of Emergency Medicine |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MPhil |
| Format | application/pdf |
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