菌血症
分辨率(逻辑)
计算机科学
医学
遥感
地质学
生物
人工智能
微生物学
抗生素
作者
April Aralar,Tyler Goshia,Nanda Ramchandar,Shelley M. Lawrence,Aparajita Karmakar,Ankit Sharma,Manish Kumar Sinha,David T. Pride,Peiting Kuo,Khrissa Lecrone,Megan Chiu,Karen K. Mestan,Enikö Sajti,Michelle K Vanderpool,Sarah Lazar,Melanie Crabtree,Yordanos Tesfai,Stephanie I. Fraley
标识
DOI:10.1016/j.jmoldx.2024.01.013
摘要
Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.
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