Extensive epidemiological study of Traumatic Pneumothorax in Saudi Arabian's population
Objectives: Traumatic Pneumothorax is one of the causes of trauma mortality and morbidity. It is a problem for developing countries as many accidents can be avoided and there are few epidemiological data to support programs injury prevention. The main objective of the current study was to determine demographic characteristics, patterns and severity of the injury, thoracic, and extra-thoracic related injuries in a level 1 trauma center, Riyadh, Saudi Arabia.
Methods: This retrospective observational study used the King Abdulaziz Medical City Trauma Center's trauma registry to review the data of Traumatic Pneumothorax patients admitted to the hospital from January 2001 to December 2018. Demographic characteristics, admission date and time, type and mechanism of injury, involved body area, and severity rates were analyzed.
Results: This study contained a total of 708 patients of whom 92.3% were males. Blunt trauma (75.8%), thoracic stab injury (21.6%) and thoracic gunshot injury (1.9%) were the most common cause of injury. Motor Vehicle Accidents were the most common cause (57%) of Traumatic Pneumothorax followed by pedestrian injury (11.3%), homicide and death intentionally caused by other persons (23.8%), fall from heights (4.8%), suicide and self-inflicted injury (0.1%), motorcycle injury (1%), and other injuries not mentioned above (1.9%) patients. Rib fractures (36.5%), lung contusions (31.5%), haemothorax (23.5%) and cardiac contusions (0.3%) were the most common clinical forms of chest injury associated with Traumatic Pneumothorax. In the other hand, the head injury (34.8 %) was the commonest extra thoracic part associated. The mean of Injury Severity Score in current study was found to be 20.1.
Conclusion: This study showed the trends of Traumatic Pneumothorax injuries in a level 1 trauma center, Riyadh, Saudi Arabia, showing motor vehicle accidents are the leading cause of Traumatic Pneumothorax in our region. These demographic data will be crucial for local healthcare systems to be optimally resourced.
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