Publications by authors named "Daniel Rhoads"

Automated continuous monitoring blood culture instruments identify metabolism byproducts and flag blood culture bottles as "positive." A Gram stain is used to visualize and characterize the microbial growth in the broth and initiate additional testing. When no organisms are seen (NOS) on Gram stain, in our laboratory, bottles are reevaluated with a Wayson stain, a rapid one-step stain that provides contrast between organisms and the background, especially in Gram-negative organisms.

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Objective: To develop, externally validate, and test a series of computer algorithms to accurately predict antibiotic susceptibility test (AST) results at the time of clinical diagnosis, up to 3 days before standard urine culture results become available, with the goal of improving antibiotic stewardship and patient outcomes.

Patients And Methods: Machine learning algorithms were developed and trained to predict susceptibility or resistance using over 4.7 million discrete AST classifications from urine cultures in a cohort of adult patients from outpatient and inpatient settings from 2012 to 2022.

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Ledaborbactam (formerly VNRX-5236), a bicyclic boronate β-lactamase inhibitor with activity against class A, C, and D β-lactamases, is under development as an orally bioavailable etzadroxil prodrug (VNRX-7145) in combination with ceftibuten for the treatment of urinary tract infections. At ceftibuten breakpoints of ≤1 mg/L (EUCAST) and ≤8 mg/L (CLSI), 92.5% and 99.

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We characterized the molecular determinants of meropenem-vaborbactam (MV) non-susceptibility among non-metallo-β-lactamase-producing KPC- (KPC-). Whole-genome sequencing was performed to identify mutations associated with MV non-susceptibility. Isolates with elevated MV MICs were found to have mutations encoding truncated or altered OmpK36 porins and increased copy numbers.

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Taniborbactam, a bicyclic boronate β-lactamase inhibitor with activity against carbapenemase (KPC), Verona integron-encoded metallo-β-lactamase (VIM), New Delhi metallo-β-lactamase (NDM), extended-spectrum beta-lactamases (ESBLs), OXA-48, and AmpC β-lactamases, is under clinical development in combination with cefepime. Susceptibility of 200 previously characterized carbapenem-resistant and 197 multidrug-resistant (MDR) to cefepime-taniborbactam and comparators was determined by broth microdilution. For (192 KPC; 7 OXA-48-related), MIC values of β-lactam components for cefepime-taniborbactam, ceftazidime-avibactam, and meropenem-vaborbactam were 2, 2, and 1 mg/L, respectively.

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Context.—: Laboratory testing practices for diagnosis of Clostridioides difficile infection (CDI) have evolved in response to published guidelines, availability of highly sensitive nucleic acid amplification tests (NAATs), perceived problems with the specificity of NAATs, and CDI reporting requirements.

Objective.

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Objectives: To determine accuracy of negative urinalysis (UA) for predicting negative urine culture and the absence of urinary tract infection (UTI), and optimal urine culture growth cutoff for UTI diagnosis in men with and without urinary catheters.

Subjects And Methods: UAs with urine cultures within 1 week from adult men were identified and evaluated. Predictive values for the absence of UTI (absence of ≥1 of the following criteria: documentation of UTI diagnosis, antibiotic prescription, uropathogen presence on culture) were calculated.

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The virulence of methicillin-resistant (MRSA) and its potentially fatal outcome necessitate rapid and accurate detection of patients colonized with MRSA in healthcare settings. Using the BD Kiestra Total Lab Automation (TLA) System in conjunction with the MRSA Application (MRSA App), an imaging application that uses artificial intelligence to interpret colorimetric information (mauve-colored colonies) indicative of MRSA pathogen presence on CHROMagar chromogenic media, anterior nares specimens from three sites were evaluated for the presence of mauve-colored colonies. Results obtained with the MRSA App were compared to manual reading of agar plate images by proficient laboratory technologists.

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Article Synopsis
  • - The frequent renaming of medically significant fungi is complicating the work of clinical labs and healthcare providers, highlighting the need for better communication and resources in this area.
  • - Different factors drive name changes at the species and genus levels, prompting the authors to suggest maintaining larger genera and providing diagnostic markers for new classifications to help simplify identification.
  • - The authors call for an open-access online database to track these changes, recommending a committee to regularly review new names so that clinicians can access consistent and validated information about fungal species.
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The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial intelligence (AI) approaches such as machine learning (ML) are being integrated into clinical microbiology practice. These image analysis AI (IAAI) tools are beginning to penetrate routine clinical microbiology practice, and their scope and impact on routine clinical microbiology practice will continue to grow.

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Background: Congenital cytomegalovirus (CMV) infection is a significant cause of childhood hearing loss and developmental delay. Congenital CMV screening was implemented at two large hospital-affiliated laboratories using the FDA-approved Alethia CMV Assay Test System. In July 2022, an increase in suspected false-positive results was noted, leading to implementation of prospective quality management strategies.

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SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations.

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Diagnostic tools that can rapidly identify and characterize microbes growing in blood cultures are important components of clinical microbiology practice because they help to provide timely information that can be used to optimize patient management. This publication describes the bioMérieux BIOFIRE Blood Culture Identification 2 (BCID2) Panel clinical study that was submitted to the U.S.

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Objective: To assess predictive value of urinalysis for negative urine culture and absence of urinary tract infection, re-evaluate the microbial growth threshold for positive urine culture result, and describe antimicrobial resistance features. Urine culture is associated with 27% of U.S.

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Introduction: Increasing antimicrobial resistance with Helicobacter pylori infection has focused efforts to tailor eradication therapy based on identifying genetic markers of resistance to predict antimicrobial susceptibility.

Methods: In this retrospective study, we report the effect of routine inclusion of antimicrobial susceptibility testing and recommendations for eradication therapy with gastric specimens with H. pylori .

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In 2020, the U.S. Food and Drug Administration (FDA) enabled manufacturers to request emergency use authorization (EUA) to facilitate the rapid authorization of diagnostic (IVD) platforms for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

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Article Synopsis
  • Machine learning (ML) can enhance the analysis of complex clinical data, potentially improving laboratory medicine efficiency, but there are risks of biased models leading to incorrect clinical interpretations.
  • The process of creating effective ML models involves critical steps like data collection, preprocessing, development, and evaluation, while also addressing challenges that may mislead clinical insights.
  • Educating clinicians and laboratorians on high-quality data collection, handling missing values, selecting appropriate ML models, and evaluating their performance is essential for successful implementation of ML in clinical practice.
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Background: Four severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants predominated in the United States since 2021. Understanding disease severity related to different SARS-CoV-2 variants remains limited.

Method: Viral genome analysis was performed on SARS-CoV-2 clinical isolates circulating March 2021 through March 2022 in Cleveland, Ohio.

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The urine culture, the cornerstone for laboratory diagnosis of urinary tract infection (UTI), is associated with a high frequency of false-positive and false-negative results, and its diagnostic threshold is debated. Urine culture takes days to result, and antibiotics are often initiated while awaiting final culture readings. Further, asymptomatic bacteriuria-the presence of bacteria in urine in the absence of UTI symptoms-generally does not warrant treatment.

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Neisseria meningitidis is a common commensal bacterium found in the respiratory tract, but it can also cause severe, invasive disease. Vaccines have been employed which have been successful in helping to prevent invasive disease caused by encapsulated N. meningitidis from the A, C, W, Y, and B serogroups.

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The COVID-19 pandemic has caused more than 448 million cases and 6 million deaths worldwide to date. Omicron is now the dominant SARS-CoV-2 variant, making up more than 90% of cases in countries reporting sequencing data. As the pandemic continues into its third year, continued testing is a strategic and necessary tool for transitioning to an endemic state of COVID-19.

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