Evaluation of bleeding risk in patients with renal impairment treated with Fondaparinux (Arixtra)

Background: Fondaparinux (Arixtra) a synthetic pentasaccharide that causes an antithrombin III-mediated selective inhibition of factor Xa. The clearance of fondaparinux reduces in patients with renal impairment, and there are no dosage adjustments provided in the manufacturer’s labeling. In patients with creatinine clearance rate (CrCl) >50 ml/min, total clearance is reduced by 25% while in case of CrCl 30–50 ml/min, the total clearance could be 40% lower when compared to patients with normal renal function. Aim of the Study: To evaluate the risk of bleeding in patients with renal impairment treated with fondaparinux. Materials and Methods: We performed a retrospective chart review study of patients 18 years of age and older who received fondaparinux between 11/10/2003 and 30/12/2009 during their hospital stays, and who had a CrCl of ≤80 ml/min. The patients were classified according to their degree of renal dysfunction as either stage A (CrCl: 80–50 ml/min; mild dysfunction) or stage B (CrCl: <50 ml/min; moderate or severe dysfunction). The HAS-BLED scoring system (HAS-BLED mnemonic stands for: hypertension, abnormal renal and liver function, stroke, bleeding, labile international normalized ratios, elderly, drugs or alcohol) was used to categorize the bleeding risk as mild, moderate, or high. Additionally, the bleeding severity was categorized as either major bleeding or minor bleeding. Results: A total of 165 patients were included in the study; of which 87 were men. In that 52.7% of the total were classified as stage A and the remainder as stage B. The patients classified as stage B were more frequently classified at high risk of bleeding than stage A patients (48.7%, n = 38 of stage B patients vs. 23.0%, n = 20 of stage A patients). Twenty-three percent (n = 38) of the patients experienced bleeding, and most of which were stage B patients (55.3%, n = 21). The majority of the patients who bled experienced major bleeding (71.0%, n = 27). Ten percent (n = 16) of the total number of patients, whose fondaparinux doses were adjusted as per the drug monograph, were documented to have had a bleeding event during their hospital stay. By contrast, 13% of the total number of patients (n = 22) who required dose adjustments and received fondaparinux without adjustments had bleeding events. Conclusion: Fondaparinux increases the risk of bleeding in patients with mild-to-moderate renal impairment even with appropriate dose adjustments. The risk of bleeding and the incidence of major bleeding are increased in patients with moderate and severe renal dysfunction

A Simulation Model for Forecasting COVID-19 Pandemic Spread: Analytical Results Based on the Current Saudi COVID-19 Data

The coronavirus pandemic (COVID-19) spreads worldwide during the first half of 2020. As is the case for all countries, the Kingdom of Saudi Arabia (KSA), where the number of reported cases reached more than 392 K in the first week of April 2021, was heavily affected by this pandemic. In this study, we introduce a new simulation model to examine the pandemic evolution in two major cities in KSA, namely, Riyadh (the capital city) and Jeddah (the second-largest city). Consequently, this study estimates and predicts the number of cases infected with COVID-19 in the upcoming months. The major advantage of this model is that it is based on real data for KSA, which makes it more realistic. Furthermore, this paper examines the parameters used to understand better and more accurately predict the shape of the infection curve, particularly in KSA. The obtained results show the importance of several parameters in reducing the pandemic spread: the infection rate, the social distance, and the walking distance of individuals. Through this work, we try to raise the awareness of the public and officials about the seriousness of future pandemic waves. In addition, we analyze the current data of the infected cases in KSA using a novel Gaussian curve fitting method. The results show that the expected pandemic curve is flattening, which is recorded in real data of infection. We also propose a new method to predict the new cases. The experimental results on KSA’s updated cases reveal that the proposed method outperforms some current prediction techniques, and therefore, it is more efficient in fighting possible future pandemics