The global battle to contain the novel coronavirus disease 2019 (COVID-19) pandemic rages on. Previous studies described the clinical characteristics of COVID-19, but knowledge gaps remain in the Middle East region. Identifying these features will help in mapping the disease and guiding pandemic management. A multi-center, retrospective cross-sectional study was initiated to describe the demographic data, clinical characteristics, and outcomes of COVID-19 cases across all the regions of Saudi Arabia. The analysis included all laboratory-confirmed positive COVID-19 patients from the 1st of March 2020 to 31st of March 2020 across all regions of Saudi Arabia. Demographic data, clinical characteristics, incubation periods, laboratory findings, and patient outcomes data were retrieved from 1519 cases in the Health Electronic Surveillance Network Database. The median age was 36 years and 54.3% (n = 825) of the patients were men. Patients working in health care facilities represented 12.5% of the cases (n = 190) and 9.3% of cases were asymptomatic. The median incubation period was 6 days. The most common symptoms were cough (89.4%), fever (85.6%), and sore throat (81.6%); 20.1% of the patients had underlying comorbidities. Hypertension was seen in 8.8% and diabetes in 7.6% of all the cases. The percentage of cases with temperatures >38֯C was 20.3% (n = 129), and 1.6% of patients had heart rates ≥125 beats/min and 4.7% of them had respiratory rates of >24 breaths/min. Lymphocytopenia occurred in 37.5% of cases. Overall, 71.6% of patients were admitted to hospitals and 4.7% required ICU treatment. We could not completely assess the clinical courses or final outcomes of COVID-19 patients. In this multi-center retrospective study, fever and cough were common symptoms. Special attention should be addressed toward asymptomatic carriers and workers in health care facilities as they play a key role in disease transmission.

Background: With the spread of coronavirus disease 2019 (COVID-19), most countries rushed to take early measures to control this disease. Aims: This paper describes and evaluates the Saudi Arabian strategic preparedness and response plan on COVID-19 up to 31 December 2020. Methods: Saudi Arabia adopted the World Health Organization’s guidelines on response to COVID-19, which are based on nine pillars of public health preparedness and response. The measures Saudi Arabia took are assessed against these pillars. Results: In response to COVID-19, Saudi Arabia prepared public and private institutions to deal with the pandemic. Saudi authorities established a governance system comprised of responsible committees to continuously monitor national and international updates, trace contacts, screen the population, raise awareness and take proper actions to contain the spread of this disease. After the announcement of the first case in Saudi Arabia, all schools, social events, sports activities, domestic travel and international flights were suspended. Restrictions on social movement, social and religious gatherings, travel and businesses were imposed ahead of the first 100 confirmed COVID-19 cases. The Hajj pilgrimage for 2020 was scaled down to limit participants and no cases of COVID-19 were detected among pilgrims. The country maintained all basic health services and immunization programmes and supported all proposals for COVID-19 drugs and vaccines. The country is working to develop its capacity to produce these products and achieve self-sufficiency. Conclusion: Saudi Arabia took extreme measures to respond to COVID-19 which contributed to limiting the spread and effect of the disease.

Objectives: Assess the survival of hospitalized coronavirus disease 2019 (COVID-19) patients across age groups, sex, use of mechanical ventilators (MVs), nationality, and intensive care unit (ICU) admission in the Kingdom of Saudi Arabia. Methods: Data were retrieved from the Saudi Ministry of Health (MoH) between 1 March and 29 May 2020. Kaplan–Meier (KM) analyses and multiple Cox proportional-hazards regression were conducted to assess the survival of hospitalized COVID-19 patients from hospital admission to discharge (censored) or death. Micro-costing was used to estimate the direct medical costs associated with hospitalization per patient. Results: The number of included patients with complete status (discharge or death) was 1422. The overall 14-day survival was 0.699 (95%CI: 0.652–0.741). Older adults (>70 years) (HR = 5.00, 95%CI = 2.83–8.91), patients on MVs (5.39, 3.83–7.64), non-Saudi patients (1.37, 1.01–1.89), and ICU admission (2.09, 1.49–2.93) were associated with a high risk of mortality. The mean cost per patient (in SAR) for those admitted to the general Medical Ward (GMW) and ICU was 42,704.49 ± 29,811.25 and 79,418.30 ± 55,647.69, respectively. Conclusion: The high hospitalization costs for COVID-19 patients represents a significant public health challenge. Efficient allocation of healthcare resources cannot be emphasized enough.

The rapid emergence of the novel coronavirus disease 2019 (COVID-19) has resulted in millions of infected patients and hundreds of thousands of deaths worldwide. Health care services delivery is being compromised due to the surge in the number of infected patients during this pandemic. This study aimed to assess the risk factors associated with poor prognosis among COVID-19 patients in Saudi Arabia. This was a multi-centre retrospective cohort study that included all laboratory-confirmed COVID-19 cases with definitive outcomes in Saudi Arabia during March 2020. Demographic, clinical history, comorbidity and outcomes data were retrieved from the National Health Electronic Surveillance Network (HESN) database. We used logistic regression models to calculate crude and adjusted odds ratios (OR) to explore risk factors for critical outcomes (intensive care unit admission or death) among COVID-19 cases. We included 648 COVID-19-positive patients with a median age of 34 years. Of these, 11.9% were in the critical group. Risk factors associated with worse outcomes included males (OR=1.92), age >60 years (OR=3.65), cardiac diseases (OR=3.05), chronic respiratory diseases (OR=2.29), and cases with two or more comorbidities (OR=2.57) after adjusting for age and sex; all had significant P-values <0.05. Independent risk factors for critical outcomes among COVID-19 cases include old age, males, cardiac patients, chronic respiratory diseases, and the presence of two or more comorbidities. We recommend designing a unique multi-item scale system to prognosticate COVID-19 patients.

Fever is one of the common conditions encountered in the emergency department, which related to a spectrum of diseases severity. Identifying sepsis patients from uncomplicated febrile patients is challenging in the emergency triage areas and pre-hospital settings. Assess the triage shock index (SI) and modified shock index (MSI) in febrile patients as predictors for sepsis and sepsis-related outcomes. A retrospective cohort study. Patients presented to the Emergency Department of King Khalid University Hospital. The analysis included all febrile adult patients triaged with a temperature of 38 °C or more from January 2016 to December 2017. Based on triage vital sign we calculate the SI with cut-off levels of ≥0.7 and ≥1 and MSI with cut-off levels of ≥1 and ≥1.3. We report the Relative Risk, Sensitivity, Specificity, Positive and Negative Predictive Values of the predictors. Sepsis and sepsis-related outcomes such as hyperlactatemia, ICU admission, and 28 days mortality. 274 patients. 274 patients met our inclusion/exclusion criteria. Of the 274 patients, 252 patient (92%) were septic, 62 patients (22%) had hyperlactatemia, 20 patients admitted to the ICU, and 5 patient died within 28 days. An MSI of ≥1 had a sensitivity of 90% for sepsis predication, 85% for ICU admission and 100% for 28 days mortality. MSI of ≥1.3 showed a specificity (59%-100%) for all the outcomes of interest. Non-significant statistical trends of greater accuracy of MSI over SI. MSI and SI were found to be promising predictors in triaging febrile patients. However no single cut-off values of MSI or SI were found to have an optimal accuracy for prediction of sepsis and sepsis-related outcomes. Further studies are required to assess the incorporation of MSI in a multi-item scaling system for the prediction of sepsis and its related outcomes. Small single center study and the results may not be generalizable.