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首页> 外文期刊>Journal of Clinical Microbiology >A Flowthrough Assay for Rapid Bedside Stratification of Bloodstream Bacterial Infection in Critically III Patients: a Pilot Study
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A Flowthrough Assay for Rapid Bedside Stratification of Bloodstream Bacterial Infection in Critically III Patients: a Pilot Study

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Bacterial infections affect more than 2 million people annually. Of these, systemic infections caused by bacteria in critically ill patients may lead to life-threatening conditions such as sepsis. We have developed a point-of-care (POC) device called Septiflo that can detect and stratify the Gram status of bloodstream bacterial infections in less than 10 min from a drop of human plasma. It works on the principle of identifying pathogen-associated molecular patterns (PAMPs), such as lipopolysaccharides (LPS) and lipoteichoic acid (LTA) that are released into the bloodstream at the onset of Gram-negative and Gram-positive bacterial infections, respectively. The biomarkers are captured on a membrane without a receptor, and the Gram status specificity is conferred by the ligands attached to gold nanoparticles (AuNPs) used as signal amplification probes. The ultrasensitive colorimetric results are read by eye down to a 100-fg/m1 detection limit without an instrument. No cross-interference between the PAMPs is seen during Gram stratification. Septiflo results also display better performance than commercial enzyme-linked immunosorbent assays (ELISA5). Tests performed on 60 clinical samples from patients showed a correlation accuracy of 70 against procalcitonin (PCT), an accepted surrogate biomarker for sepsis. A direct comparison with eubacterial PCR yielded up to 94 accuracy in 31 patients at a chosen cutoff level for LPS and LTA and area under the curve (AUC) values of 0.927 and 0.885, respectively, though blood culture was negative for most samples. The high sensitivity, low cost, and simple bedside utility of the assay may aid in better sepsis management apparently at the presymptomatic stage, lowering empirical therapy, medical costs, antimicrobial resistance, and mortality.

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