Application of ddPCR in the rapid diagnosis of bloodstream infections: detection of Staphylococcus, Enterococcus spp, Streptococcus spp and Candida spp

Background The current gold standard for the detection of bloodstream infections has several limitations, including a low positivity rate, a high contamination rate, and a lengthy flow cycle. Droplet digital polymerase chain reaction (ddPCR), a novel technique offering high sensitivity and specificity and the ability to provide absolute quantification, has not been extensively investigated in the context of bloodstream infections. Methods A prospective study was conducted on 77 patients with suspected bloodstream infections, with blood cultures and ddPCR used to investigate the presence of four pathogens. Additionally, the general characteristics of the patients and relevant routine tests were collected and analysed to assess the diagnostic efficacy of ddPCR for bloodstream infections. Results 77 patients from intensive care medicine, respiratory medicine, and other departments considering BSIs were enrolled. Blood cultures identified 24 positive samples, including 8 Staphylococcus aureus, 12 Enterococcus species, 1 Streptococcus species, and 3 Candida species.. The ddPCR assay demonstrated 100% sensitivity for all four pathogen categories and specificities of 94.20%, 92.31%, 93.42%, and 94.59%, respectively. In addition, the ddPCR assay simultaneously detected 4 cases of polymicrobial infections and 14 cases of negative blood cultures, which was verified by Sanger sequencing. The ddPCR assay's detection time was significantly shorter than that of blood cultures, with an average of 4.31 ± 0.94 hours compared to 68.40 ± 2.50 hours ( p  < 0.01). Conclusion The present study demonstrates that droplet digital polymerase chain reaction (ddPCR) significantly reduces the turnaround time of positive blood culture specimens. Furthermore, it has high sensitivity, specificity and negative predictive value, and enables early diagnosis of bloodstream infections. A larger number of samples is required to validate the correlation between absolute ddPCR quantification and patient severity and prognosis.