Blood culture negative endocarditis (BCNE) accounts for up to 20% of infective endocarditis. While the most common cause of BCNE remains the initiation of antibiotics prior to culture, intracellular organisms such as Coxiella and Bartonella spp account for a significant proportion of cases. Identifying the infecting organism remains important to ensure optimal antimicrobial treatment. However, these organisms can be difficult to diagnose. We outline a systematic approach to BCNE. Over half of patients with infective endocarditis now undergo early surgery and 16S ribosomal ribonucleic acid (rRNA) polymerase chain reaction (PCR) of excised tissue can be vitally important to secure a diagnosis. Molecular testing is likely to become a key tool in improving outcomes from BCNE and contribute to an improved understanding of the aetiology. We advocate modifying the Duke criteria to incorporate organisms identified on molecular testing, including 16S rRNA PCR, in particular from explanted tissue.
Background: There is no generally accepted methodology for in vivo assessment of antiviral activity in SARS-CoV-2 infections. Ivermectin has been recommended widely as a treatment of COVID-19, but whether it has clinically significant antiviral activity in vivo is uncertain.Methods: In a multicentre open label, randomized, controlled adaptive platform trial, adult patients with early symptomatic COVID-19 were randomized to one of six treatment arms including high dose oral ivermectin (600µg/kg daily for seven days), the monoclonal antibodies casirivimab and imdevimab (600mg/600mg), and no study drug. The primary outcome was the comparison of viral clearance rates in the modified intention-to-treat population (mITT). This was derived from daily log10 viral densities in standardized duplicate oropharyngeal swab eluates. This ongoing trial is registered at ClinicalTrials.gov (NCT05041907).Results: Randomization to the ivermectin arm was stopped after enrolling 205 patients into all arms, as the prespecified futility threshold was reached. Following ivermectin the mean estimated rate of SARS-CoV-2 viral clearance was 9.1% slower [95%CI -27.2% to +11.8%; n=45] than in the no drug arm [n=41], whereas in a preliminary analysis of the casirivimab/imdevimab arm it was 52.3% faster [95%CI +7.0% to +115.1%; n=10 (Delta variant) versus n=41].Conclusions: High dose ivermectin did not have measurable antiviral activity in early symptomatic COVID-19. Pharmacometric evaluation of viral clearance rate from frequent serial oropharyngeal qPCR viral density estimates is a highly efficient and well tolerated method of assessing SARS CoV-2 antiviral therapeutics in vivo.Funding: 'Finding treatments for COVID-19: A phase 2 multi-centre adaptive platform trial to assess antiviral pharmacodynamics in early symptomatic COVID-19 (PLAT-COV)' is supported by the Wellcome Trust Grant ref: 223195/Z/21/Z through the COVID-19 Therapeutics Accelerator.Clinical trial number: ClinicalTrials.gov (NCT05041907).
Background Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel. Objective This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly. Methods An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People’s Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam. Results We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.website/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository. Conclusions The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.
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