Open AccessPatterns of trauma injuries and predictors of in-hospital mortality in patients admitted to a tertiary care setting in Saudi Arabia
Author(s) -
Mostafa A. Abolfotouh,
Alanoud Al-Marzoug,
Suliman Al-Teriqi,
Abeer Al-Suwailem,
Ra’ed Hijazi
Publication year - 2016
Publication title -
journal of emergency medicine, trauma and acute care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.27
H-Index - 5
eISSN - 1999-7094
pISSN - 1999-7086
DOI - 10.5339/jemtac.2016.icepq.24
Subject(s) - medicine , emergency medicine , injury severity score , retrospective cohort study , logistic regression , blunt trauma , injury prevention , blunt , mortality rate , poison control , major trauma , pediatrics , medical emergency , surgery
Background: Trauma is a major cause of death worldwide that can result death or permanent disability. Globally, 6–10% of all deaths are attributed to traumatic injuries. In Saudi Arabia, trauma is a public burden as a result of its socioeconomic impact. Our aim is to describe the pattern of traumatic injuries and predictors of in-hospital mortality among patients admitted through the ED of King Abdulaziz Medical City. Methods: A retrospective cohort study was conducted on 3786 trauma-injured patients admitted from 2012 to 2014. Data on: patient characteristics, trauma characteristics and outcome characteristics, were extracted from a prospectively collected database. Logistic regression analysis and ROC curve were applied. Results: Of 3786, (77.5%) of victims were males, (29.8%) injuries occurred in the age group (15–25 years). Blunt injuries constituted (87.1%), followed by burns (7%), intentional injuries (5%) and drowning & foreign body (1%). Data showed seasonal variation with two main peaks in March and August (p < 0.001). In-hospital mortality rate was (4.7%. Significant predictors of in-hospital mortality were age (p < 0.001), intubation need (p = 0.009), ISS (p < 0.001), RTS (p = 0.007), GCS (p = .004) and road traffic accidents (p = 0.001). The cut-off points for prediction of in-hospital mortality: were as follows: ISS = 22, AUC = 93%, ATS = 9, AUC = 78% and GCS = 8, AUC = 83%. Conclusions: Our recommendation is targeted to ED policy makers to recognize the patterns of injury and the seasonal variation to structure and distribute the facilities and staff in a cost-effective manner. Also, enforcing trauma preventative measures should be encouraged. Secondly, for ED physicians to enhance the use of in-hospital predictors of mortality. Finally, educational programs targeting the general population are essential to cover all aspects.