Efficacy and safety of delafloxacin, ceftaroline, ceftobiprole, and tigecycline for the empiric treatment of acute bacterial skin and skin structure infections: A network meta-analysis of randomized controlled trials

Background: This review aimed to conduct an indirect comparison using a Bayesian network meta-analysis of randomized controlled trials (RCTs) to compare the efficacy and safety of delafloxacin versus other single antibiotic regimens for the empiric treatment of Acute Bacterial Skin and Skin Structure Infections. Method: A systematic search with no start date restrictions was conducted. The Cochrane Risk of Bias tool was used to assess the quality of included RCTs. Results: Of the 577 studies initially identified, nine RCTs were included in the review. The network meta-analysis showed that ceftaroline, ceftobiprole, delafloxacin and tigecycline had similar efficacy in the indirect comparisons [Ceftaroline Odds Ratio (OR) = 1.2, 95% Crl = 0.46–3.6), ceftobiprole (OR = 1.3, 95% Crl = 0.34–3.0) and tigecycline (OR = 0.96, 95% Crl = 0.30–2.9)]. However, the ranking plot for the intention to treat (ITT) population showed that delafloxacin had a probability of 80.8% to be ranked first followed by ceftobiprole (13.1%). The analysis of the overall adverse events showed that ceftaroline (OR = 0.88, 95% Crl = 0.65–1.2), ceftobiprole (OR = 1.1, 95% Crl = 0.69–2.0), delafloxacin (OR = 0.88, 95% Crl = 0.57–1.3) and tigecycline (OR = 1.4, 95% Crl = 0.88–2.2) had similar safety profiles. Conclusion: Delafloxacin did not show any statistically significant differences when compared to ceftaroline, ceftobiprole, and tigecycline in terms of efficacy and safety. However, the surface under the cumulative ranking curve (SUCRA) probability ranked delafloxacin as the first option for the ITT population. © 2022 The AuthorsOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Use of repurposed and adjuvant drugs in hospital patients with covid-19: Multinational network cohort study

Objective To investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents. Design Multinational network cohort study. Setting Hospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea. Participants 303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020. Main outcome measures Prescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19. Results Of the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from <5 (<2%) patients in China to 2165 (85.1%) in Spain), azithromycin (from 15 (4.9%) in China to 1473 (57.9%) in Spain), combined lopinavir and ritonavir (from 156 (<2%) in the VA-OMOP US to 2,652 (34.9%) in South Korea and 1285 (50.5%) in Spain), and umifenovir (0% in the US, South Korea, and Spain and 238 (78.3%) in China). Use of adjunctive drugs varied greatly, with the five most used treatments being enoxaparin, fluoroquinolones, ceftriaxone, vitamin D, and corticosteroids. Hydroxychloroquine use increased rapidly from March to April 2020 but declined steeply in May to June and remained low for the rest of the year. The use of dexamethasone and corticosteroids increased steadily during 2020. Conclusions Multiple drugs were used in the first few months of the covid-19 pandemic, with substantial geographical and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed drugs. Antithrombotics, antibiotics, H2 receptor antagonists, and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of covid-19. ©Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Purpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three nonmutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: More women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance. © 2022 Kostka et al.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]