Objective: The coronavirus disease (COVID-19) pandemic has disrupted healthcare systems worldwide, resulting in decreased and delayed hospital visits of patients with non-COVID-19-related acute emergencies. We evaluated the impact of the COVID-19 pandemic on the presentation and outcomes of patients with non-COVID-19-related medical and surgical emergencies. Method: All non-COVID-19-related patients hospitalized through emergency departments in three tertiary care hospitals in Saudi Arabia and Bahrain in June and July 2020 were enrolled and categorized into delayed and non-delayed groups (presentation ≥/=24 or <24 h after onset of symptom). Primary outcome was the prevalence and cause of delayed presentation; secondary outcomes included comparative 28-day clinical outcomes (i.e., 28-day mortality, intensive care unit (ICU) admission, invasive mechanical ventilation, and acute surgical interventions). Mean, median, and IQR were used to calculate the primary outcomes and inferential statistics including chi-square/Fisher exact test, t-test where appropriate were used for comparisons. Stepwise multivariate regression analysis was performed to identify the factors associated with delay in seeking medical attention. Results: In total, 24,129 patients visited emergency departments during the study period, compared to 48,734 patients in the year 2019. Of the 256 hospitalized patients with non-COVID-19-related diagnoses, 134 (52%) had delayed presentation. Fear of COVID-19 and curfew-related restrictions represented 46 (34%) and 25 (19%) of the reasons for delay. The 28-day mortality rates were significantly higher among delayed patients vs. non-delayed patients (n = 14, 10.4% vs. n = 3, 2.5%, OR: 4.628 (CI: 1.296–16.520), p = 0.038). Conclusion: More than half of hospitalized patients with non-COVID-19-related diagnoses had delayed presentation to the ED where mortality was found to be significantly higher in this group. Fear of COVID-19 and curfew restrictions were the main reasons for delaying hospital visit.

Introduction: Epinephrine is recommended for patients with out-of-hospital cardiac arrest (OHCA). However, whether epinephrine improves or adversely affects OHCA outcomes is controversial. Objectives: This study aims to determine whether the frequency of epinephrine administration impacts OHCA patient survival. Methods: We conducted a retrospective analysis of OHCA cases registered in the Emergency Department at King Fahd University Hospital, Saudi Arabia between 2005 and 2015. The primary outcomes were mortality and survival rates until discharge. The impact of epinephrine administration timing and frequency on patient survival was analyzed. Results: Data from 300 OHCA cases were analyzed. Among them, 66.3% were men, and the overall mean age of 50.4 ± 20.6 years. The overall survival rate until hospital discharge was 12%. There was no statistically significant difference between in gender, age, or time interval to the first epinephrine dose in the survival and non-survival groups. Only the number of epinephrine doses was related to the survival outcome. Conclusion: Non-survivors received significantly more epinephrine doses compared with survivors. However, a causal relationship between OHCA patient survival and epinephrine dose and time cannot be confirmed. Further studies are needed to investigate whether the long-term outcomes in OHCA patients are influenced by the timing and frequency of epinephrine administration.

Background/Objectives: Mortality from COVID-19 in intensive care units (ICUs) was not clearly reported in many regions during the first wave. We aimed to assess the characteristics and outcomes of ICU patients with COVID-19 in Saudi Arabia. Methods: This was a secondary data analysis of the Convalescent Plasma Trial. All patients who were recruited from King Fahad Hospital of the University (KFHU) in the Eastern Region of Saudi Arabia between 13 March 2020 and 13 September 2020 were included. Characteristics and outcomes, differences in characteristics and outcomes between Saudi and non-Saudi populations, and predictors of mortality were assessed. Results: The KFHU recruited 185 ICU patients with COVID-19. Of those, 90 (48.6%) were Saudi, and 95 (51.4%) were non-Saudi. The overall mean age was 56.7 years, and 71.9% were males. Compared with Saudis, non-Saudis were younger, with a mean age of 54.4 years, were more likely to be males (81.1%), and had a higher median respiratory rate (28.0 breaths/min vs. 24.0), a lower percentage of blood-oxygen saturation (86.0% vs. 91.0%), and higher median levels of ferritin per µg/L (820 vs. 550). The overall mortality rate was 33.0% (n = 61). The mortality rate in non-Saudis (42.1%) was higher than that in Saudis (23.3%). The variables associated with increased mortality included non-Saudi status (odds ratio [OR] 2.66; 95% CI: 1.05, 6.72), ferritin (OR 1.01; 95% CI: 1.00, 1.02), and intubation (OR 8.55; 95% CI: 2.92, 24.97). Conclusions: Since the mortality rate in non-Saudis was greater than that in Saudis, more efforts should be made to improve social determinants of health across non-Saudis in our region.

Background: Epilepsy, characterized by recurrent unprovoked seizures, poses a significant global burden on individuals and healthcare systems. Accurate identification of underlying causes is vital for optimal intervention. However, studies reveal a lack of standardized approaches, potentially resulting in unnecessary investigations. Objective: We aimed to highlight the importance of avoiding unnecessary testing to minimize healthcare costs and resource waste. Methods: In the Emergency Department of King Fahd Hospital of the University (KFUH) in Alkhobar, a retrospective cross-sectional study encompassed 190 patients presenting with seizures from January 1, 2020, to December 31, 2022. The study aimed to elucidate the epidemiological profile and distinguish clinical and demographic factors between new onset seizures and known cases. Results: The study included 190 epilepsy cases, with 51.1% known and 48.9% new onset. Generalized tonic-clonic seizures were prominent (43.2%), and non-compliance (24.2%) was a leading cause. New onset seizures were associated with abnormal CT findings (p=0.025), drug use (74.2%), and intoxication (6.5%). Demographically, Saudis showed higher new onset prevalence (82.8%, p=0.001). Conclusion: The average length of stay was 5.93 hours, and the distribution of new vs. known cases was nearly equal among the 190 patients. Laboratory findings showed no significant associations with either group, mostly falling within the normal range. To optimize care further, we recommend continued refinement of protocols, emphasis on medication compliance.

Background: Triage is a critical component of Emergency department care. Erroneous patient classification and mis-triaging are common in present triage systems worldwide. Therefore, several institutes worldwide have developed artificial intelligence-based algorithms that use machine learning approaches to sort and triage patients effectively. Objective: This study aims were to propose a machine learning model to predict the triage level for emergency medicine department patients and compare its performance to the standard nursing triage system. Methods: This retrospective pilot study collected the dataset of emergency department records from King Fahad Hospital of the University in khobar, between January 1, 2020, and December 31, 2022. A sample of 998 randomly selected patients was included in this cohort. The machine learning model was trained using 10-fold cross-validation. Two experiments were conducted, including five triage levels, and the second combing triage levels 2, 3, 4, and 5. Results: The machine learning model achieved an accuracy of 84% in experiment 1 and 64% in experiment 2. The mis-triage rates of the machine learning model were significantly lower than those of the standard nursing triage system. Conclusion: The machine learning model achieved higher accuracy and lower mis-triage rates than the standard nursing triage system. Thus, the proposed machine learning model can be a helpful tool for emergency department triage, enabling more efficient and accurate patient management.

This study aims to analyze healthcare workers' perception of ED crowding, its economic burden, insurance challenges, and infrastructure restrictions, while analyzing role-based variances in these perspectives. A cross-sectional online survey was conducted among 889 healthcare professionals throughout all 13 administrative regions of Saudi Arabia. Participants included nurses, physicians, pharmacists, administrative workers, and allied health professionals. Descriptive and inferential statistics (chi-square tests) were employed to examine and identify differences based on professional roles. Key findings highlighted broad concerns regarding ED crowding, with 72.5% of respondents observing high patient volumes waiting for diagnostic results. Significant economic challenges were observed, including high out-of-pocket expenditures (48.2% agreement) and inadequate insurance coverage for routine care (41.8%). Infrastructure challenges, such as bed shortages (65.0%) and insufficient staff (69.3% for nurses, 74.0% for physicians), were important problems. Statistically significant differences found across roles: nurses encountered staffing and resource shortages more acutely, whereas physicians underlined financial pressures on patients. The study underlined systemic misalignments in Saudi Arabia’s healthcare financing and infrastructure, contributing to ED crowding. Targeted actions, such as expanding insurance coverage, boosting primary care access, and addressing workforce shortages, are urgently needed. These findings align with Vision 2030 goals and give actionable insights for policymakers to promote emergency care efficiency and equity.