Plasma cell-free DNA Droplet Digital PCR provides rapid and efficient infectious microbiology diagnosis for febrile haematological patients

Background: Febrile haematological patients are at high risk for potential bloodstream infections, the rapid and accurate identification of pathogens is crucial for clinical diagnosis and treatment. Droplet Digital PCR (ddPCR) is a novel and ultra-sensitively molecular technique for the rapid detection of pathogens. We evaluated the ability of ddPCR to identify infectious etiologies to discuss the applicability of ddPCR in the diagnosis and treatment of infections for febrile haematological patients. Methods: This study enrolled and analyzed 89 ddPCR tests performed on 71 febrile haematological patients. We conducted a comparison between ddPCR results, blood culture (BC), and conventional microbiological testing (CMT). Additionally, we analyzed the correlation between ddPCR results and inflammatory factors, as well as their impact on antimicrobial therapy. Results: DdPCR detected 113 pathogens in 72 plasma samples, while CMT identified 39 pathogens in 32 plasma samples. The detection rate of bacteria and viruses using ddPCR was significantly higher than that of CMT (p <0.0001). The turnaround time (TAT) for pathogenic diagnosis was significantly shorter with ddPCR compared to CMT (p <0.0001). When we used the CMT as reference standard, the sensitivity and specificity of ddPCR were 93.8%, 26.3%, respectively. We observed a positive correlation between the ddPCR results and CRP, PCT and IL-6, and ddPCR (AUC=0.771) has better diagnostic performance. The anti-infective treatment strategies were adjusted for 30 patients based on the positive ddPCR results, with 86.7% (26/30) of these cases demonstrating effectiveness in the anti-infective treatment. Conclusion: DdPCR has the potential to enhance pathogen detection in febrile haematological patients by offering high sensitivity, rapid, precise results, it demonstrates better diagnostic performance compared to inflammatory factors and can contribute to the real-time clinical optimization of antimicrobial regimens, thereby enhancing the efficacy of anti-infective therapy.