Acute and fatal cephalosporin-induced autoimmune haemolytic anaemia

Efficacy and Safety of Rivaroxaban for Extremely Aged Patients with Venous Thromboembolism: A Retrospective, Cross-Sectional Real-World Study

Background

Rivaroxaban, a non-vitamin K antagonist oral anticoagulant, has become widely used for the management of venous thromboembolism (VTE) in adult patients. However, few trials have explored the efficacy and safety of rivaroxaban in VTE patients over 80 years of age. This necessitates further real-world studies of rivaroxaban across elderly populations.

Methods

We performed a retrospective single center study involving extremely aged VTE sufferers treated with rivaroxaban. The sample comprised 121 patients newly initiated on rivaroxaban diagnosed between January 2018 and January 2020. Patients were followed up for no less than 2 years. The effectiveness outcome was the disappearance of thromboembolism. The safety outcome was the incidence of major bleeding events. Comorbidities and complications were recorded throughout the entire study.

Results

The efficacy outcome occurred in 114 of 121 patients (94.21%) and the safety outcome occurred in 12 of 121 patients (9.91%). Increased hemorrhages were observed in patients with infection (15.15% vs 7.80%), but no significant difference was observed due to limited sample size (P=0.3053). Patients with an age-adjusted Charlson comorbidity index score higher than 6 points exhibited higher bleeding rates (14.08% vs 4.00%; P=0.0676) and lower thrombus cure rates (88.73% vs 100%; P=0.0203).

Key conclusions

Patients with infection should be more careful of bleeding events during rivaroxaban therapy. An age-adjusted Charlson comorbidity index score higher than 6, which predicted poor survival, indicated inferior safety and efficacy of rivaroxaban.

Aim

To investigate the efficacy and safety of Rivaroxaban in an aged venous thromboembolism patient population under real-world conditions.

Discovery of new TLR7 agonists by a combination of statistical learning-based QSAR, virtual screening, and molecular dynamics

Search for new antiviral medications has surged in the past two years due to the COVID-19 crisis. Toll-like receptor 7 (TLR7) is among one of the most important TLR proteins of innate immunity that is responsible for broad antiviral response and immune system control. TLR7 agonists, as both vaccine adjuvants and immune response modulators, are among the top drug candidates for not only our contemporary viral pandemic but also other diseases. The agonists of TLR7 have been utilized as vaccine adjuvants and antiviral agents. In this study, we hybridized a statistical learning-based QSAR model with molecular docking and molecular dynamics simulation to extract new antiviral drugs by drug repurposing of the DrugBank database. First, we manually curated a dataset consisting of TLR7 agonists. The molecular descriptors of these compounds were extracted, and feature engineering was done to restrict the number of features to 45. We applied a statistically inspired modification of the partial least squares (SIMPLS) method to build our QSAR model. In the next stage, the DrugBank database was virtually screened structurally using molecular docking, and the top compounds for the guanosine binding site of TLR were identified. The result of molecular docking was again screened by the ligand-based approach of QSAR to eliminate compounds that do not display strong EC₅₀ values by the previously trained model. We then subjected the final results to molecular dynamics simulation and compared our compounds with imiquimod (an FDA-approved TLR7 agonist) and compound 1 (the most active compound against TLR7 in vitro, EC₅₀ = 0.2 nM). Our results evidently demonstrate that cephalosporins and nucleotide analogues (especially acyclic nucleotide analogues such as adefovir and cidofovir) are computationally potent agonists of TLR7. We finally reviewed some publications about cephalosporins that, just like pieces of a puzzle, completed our conclusion.