Introduction
Bloodstream infection (BSI) represents a major cause of death worldwide, contributing to increased healthcare costs, length of hospital stay, and in-hospital morbidity (McNamara, et al., 2018). Timely and accurate pathogen identification is critical to guide antimicrobial treatment for patients in the early stage of BSI. Blood culture remains the gold standard for identifying the pathogens in BSI (Blevins and Bronze, 2010). However, it is limited by the low sensitivity and the long turnaround time (Riedel and Carroll, 2016, Tabak, et al., 2018). In septic patients within the first 6 h of documented hypotension, every 1-h delay in appropriate antibiotic therapy leads to an average increase of mortality rate by 7.6% (Kumar, et al., 2006). For hospitalized patients with bacterial infections, inappropriate initial antimicrobial treatment almost doubles the risk of 30-day mortality (Fraser, et al., 2006). Thus, it is necessary to develop a rapid and accurate method to identify the causal pathogens in BSI.
Recently, the culture-independent, real-time PCR-based or microarray-based methods, such as SeptiFast (Roche, Switzerland), Magicplex (Seegene, Korea), and TaqMan array card assay (Academy of Military Medical Science, China), have shown promising performance in rapidly identifying the pathogens and initiating early targeted antibiotic therapy in BSI. However, the low sensitivities ranging from 29% to 79.4% may limit the clinical application of these methods (Warhurst, et al., 2015, Buehler, et al., 2016, Riedel and Carroll, 2016, Zhang, et al., 2018, Zboromyrska, et al., 2019). Droplet digital polymerase chain reaction (ddPCR) is a novel molecular method to detect and quantify nucleic acids. In ddPCR, the template is partitioned into thousands of nanoliter-sized droplets and amplified. After amplification, the numbers of positive and negative reactions are counted, and the copy number of the template is calculated using Poisson statistics (Huggett, et al., 2015, Kuypers and Jerome, 2017). As an emerging versatile tool with high sensitivity, accuracy, and precision, ddPCR has been increasingly applied in multiple clinical scenarios, including oncology (Gevensleben, et al., 2013, Taly, et al., 2013, Jennings, et al., 2014, Postel, et al., 2018, Galimberti, et al., 2019), non-invasive prenatal testing (Barrett, et al., 2012, Tan, et al., 2019), and infectious diseases (Kelley, et al., 2013, Pholwat, et al., 2013, Sedlak, et al., 2014, Sedlak, et al., 2014, Whale, et al., 2016, Wouters, et al., 2019).
Acinetobacter baumannii and Klebsiella pneumoniae are two major Gram-negative bacteria involved in BSI, with high capabilities to develop antibiotic resistance. BSIs due to multidrug-resistant A. baumannii and K. pneumoniae significantly contribute to the mortality in the intensive care unit (ICU), with a mortality rate over 50% (Balkhair, et al., 2019, Brink, 2019). In this study, we developed and validated a ddPCR-based method to detect A.baumannii andK. pneumonia in blood samples of patients with suspected BSI. Our results provide ddPCR as a promising method to accurately and rapidly diagnose BSIs caused by A. baumannii and K. pneumoniae.