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Sodium Polyacrylate-Based Diapers for PCR Detection of Uropathogens Data

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DataCite Commons2024-10-30 更新2025-04-15 收录
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/XFNVUX
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This dataset contains comprehensive results from a study validating the use of sodium polyacrylate-based diapers for non-invasive urine collection and subsequent molecular diagnostics via quantitative PCR (qPCR). The study investigates the efficacy of this method for detecting 22 uropathogens, 6 fungal species, and 18 antimicrobial resistance genes in urine samples collected from both diapers and standard midstream urine. The data includes qPCR results from diaper-recovered and midstream urine samples spiked with clinically relevant uropathogens, alongside controls for evaluating matrix effects and potential PCR inhibition. The dataset encompasses: Cycle threshold (Ct) values from qPCR assays. Comparative detection outcomes between diaper-derived urine and midstream urine. Sensitivity and specificity metrics for pathogen detection. Analysis of potential matrix effects, including the impact of diaper materials on PCR sensitivity. Details of antimicrobial resistance gene detection, enabling insights into pathogen resistance profiles. This data provides crucial evidence supporting the feasibility of using sodium polyacrylate-based diapers as a non-invasive medium for urine collection, particularly in populations where traditional collection methods are impractical (e.g., infants, elderly individuals, and patients with incontinence). The validated method offers a robust diagnostic approach with high sensitivity and specificity, underscoring its potential for use in clinical settings. Use Cases: This dataset can be used by researchers and clinicians interested in: Advancing non-invasive diagnostic methods for urinary tract infections (UTIs). Investigating the utility of molecular diagnostics in diverse patient populations. Evaluating the impact of absorbent materials on diagnostic sensitivity. Exploring pathogen resistance profiles in clinical microbiology.
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Harvard Dataverse
创建时间:
2024-09-26
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