Background
Bloodstream infections (BSIs) are a life-threatening acute medical condition and current diagnostics for BSIs suffer from long turnaround time (TAT). Here we show the validation of a rapid detection-analysis platform (RDAP) for the diagnosis of BSIs performed on clinical blood samples
Conclusions
This study shows the preliminary feasibility of using RDAP to rapidly diagnose BSIs, including AST. Limitations and potential mitigation strategies for clinical translation of the present RDAP prototype are discussed. The results of this clinical feasibility study indicate an approach to provide near real-time diagnostic information for clinicians to significantly enhance the treatment outcome of BSIs.
Methods
The validation was performed on a cohort of 59 clinical blood samples, including positive culture samples, which indicated confirmed bloodstream infections, and negative culture samples. The bacteria in the positive culture samples included Gram-positive and Gram-negative pathogenic species. RDAP is based on an electrochemical sandwich immunoassay with voltage-controlled signal amplification, which provides an ultra-low limit of detection (4 CFU/mL), allowing the platform to detect and identify bacteria without requiring culture and perform phenotypic antibiotic susceptibility testing (AST) with only 1-2 h of antibiotic exposure. The preliminary diagnostic performance of RDAP was compared with that of standard commercial diagnostic technologies.
Results
Using a typical clinical microbiology laboratory diagnostic workflow that involved sample culture, agar plating, bacteria identification using matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry, and AST using MicroScan as a clinical diagnostic reference, RDAP showed diagnostic accuracy of 93.3% and 95.4% for detection-identification and AST, respectively. However, RDAP provided results at least 15 h faster. Conclusions: This study shows the preliminary feasibility of using RDAP to rapidly diagnose BSIs, including AST. Limitations and potential mitigation strategies for clinical translation of the present RDAP prototype are discussed. The results of this clinical feasibility study indicate an approach to provide near real-time diagnostic information for clinicians to significantly enhance the treatment outcome of BSIs.