RESUMO
Introduction Road traffic injuries (RTIs) have a significant impact on the healthcare system as well as the global economy. RTIs involving ambulance crashes not only cause delays in patient transfers but also endanger ambulance occupants and other road users. Due to the rising numbers of RTIs in the Kingdom of Saudi Arabia (KSA), the country's primary provider of prehospital services the Saudi Red Crescent Authority (SRCA) has established a new Trauma Epidemiology Center (TEC) following the KSA 2030 vision. Objective This current study was conducted to determine the causes and management-related aspects of RTIs involving ambulance crashes in KSA. We aim to highlight the current status and guide further efforts to fill gaps in knowledge and on-ground changes to prevent ambulance crashes, enhance patient care, and reduce morbidity and mortality. Method This is a descriptive, retrospective cross-sectional observational study of ambulance crashes in Saudi Arabia between January 2020 and July 2022. The data was extracted from the SRCA electronic database platform. Results One hundred and sixty accidents were recorded between 2020 and 2022 with the highest proportion of accidents recorded in Riyadh 44.29%; followed by the Eastern Province and Makkah, 15% and 12%, respectively. Ninety percent of ambulance crashes were due to direct collisions and caused by other parties in 58% of cases. It is worth mentioning that ambulance drivers fastened their seat belts in 99% of crashes. Conclusion This study highlights the epidemiology and distribution of prehospital ambulance crashes in the KSA. Most crashes occurred in urban areas with a reasonable contribution of the public in such crashes. Understanding contributing factors related to the vector, driver behaviors, and the surrounding environment is crucial to guide national preventive measures and help decision-makers to implement proper corrective actions.
RESUMO
COVID-19 infection has a spectrum of variable clinical severity between populations because of their characteristic demographic features, co-morbidities, and immune system reactions. This pandemic tested the healthcare system's preparedness, which depends on predictors of severity and factors related to the duration of hospital stays. Therefore, we carried out a single-center, retrospective cohort study in a tertiary academic hospital to investigate these clinical features and predictors of severe disease and study the different factors that affect hospital stay. We utilized medical records from March 2020 to July 2021, which included 443 confirmed (positive RT-PCR) cases. The data were explained using descriptive statistics and analyzed via multivariate models. Among the patients, 65.4% were female and 34.5% were male, with a mean age of 45.7 years (SD ± 17.2). We presented seven age groups with ranges of 10 years and noticed that patients aged 30-39 years old comprised 23.02% of the records, while patients aged 70 and above comprised 10%. Nearly 47% were diagnosed as having mild, 25% as moderate, 18% as asymptomatic, and 11% as having a severe case of COVID-19 disease. Diabetes was the most common co-morbidity factor in 27.6% of patients, followed by hypertension (26.4%). Our population's predictors of severity included pneumonia, identified on a chest X-ray, and co-morbid conditions such as cardiovascular disease, stroke, ICU stay, and mechanical ventilation. The median length of hospital stay was six days. It was significantly longer in patients with a severe disease and who were administered systemic intravenous steroids. An empirical assessment of various clinical parameters could assist in effectively measuring the disease progression and follow-up with patients.