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Rapid Molecular Panels for the Identification of Bloodstream Pathogens

Exciting advancements have been made in the clinical microbiology laboratory in the last several years, especially regarding the rapid molecular identification of pathogenic organisms and workflow automation. One of the most promising recent developments is the availability of rapid identification of organisms in positive blood cultures from septic patients. As sepsis has been shown to have an increased mortality rate of 8% with every hour of delay in appropriate antibiotic administration1 rapid identification of organisms can potentially have a profound impact of patient mortality and morbidity. Additionally, rapid diagnosis may decrease a length of stay and increase antibiotic stewardship as well. Of course, such exciting technological developments come at a price, and molecular assays for rapid diagnosis of bloodstream infections are considerably more expensive than traditional culture-based techniques. More well-designed clinical trials are necessary to more fully understand the impact of rapid diagnostics on patient care and healthcare economics in the microbiology laboratory. In this overview, I will describe some of the more recent technological breakthroughs in the rapid diagnosis of bloodstream infections. When applicable, I include impact on patient care and financial considerations. For my article, the emphasis is placed on two FDA-approved molecular panels based on polymerase chain reaction (PCR) technology.

Current Methodologies

The two primary methods for rapid diagnosis recently introduced are PCR-based methods, including large multiplexed panels, and protein-based methods, primarily MS-MALDI-TOF. Additionally, there are several other technologies available such as PCR/ESI-MS, PNA-FISH, 16S RNA sequencing, and magnetic resonance-based detection.

Traditionally, microbes that cause bloodstream infections are identified first by Gram stain of a positive blood culture bottle. This is followed by sub-culturing to agar plates to obtain isolated colonies to perform growth-based biochemical identification in an automated system. The entire process of species identification starting from the positive bottle can take 1-2 days or longer with slow-growing organisms. In fact, a few organisms are very difficult to identify at all with traditional methods due to their poor growth characteristics in culture. With the newer nucleic acid and protein-based identification methods, results can be provided in as little as one hour after the blood culture bottle turns positive, even with fastidious organisms, which can potentially have great impact on patient care. However, although the detection of some antibiotic resistance genes (e.g., mecA) is built into some rapid tests, the greatest limitation thus far of rapid diagnostic procedures is the inability to provide complete antibiotic susceptibility results to help guide tailored therapies. Presently, this limitation is an area of intense research.

PCR-based technologies

The most commonly employed molecular-based technologies for rapid identification of causative organisms of bloodstream infections are the FilmArray system (BioFire Diagnostics, Salt Lake City, UT) and the Verigene system (Luminex, Austin, TX), both of which are FDA-approved for this purpose.

FilmArray

The BioFire FilmAray Blood Culture Identification (BCID) system employs a multiplex nested PCR with detection of amplicons on a microarray using melt curve analysis as a means of ensuring specificity. There are a total of 27 targets detected by the system (Table 1): 8 gram-positive and 11 gram-negative bacteria, 5 Candida species, and 3 resistance genes (mecA, blaKPC, and Van A/VanB). The approved specimen type is a positive blood culture with organisms observed on Gram stain. The time on machine is approximately one hour.

Banerjee et al2 performed a prospective randomized trial on the impact of the FilmArray on antimicrobial therapy duration as a primary outcome and antibiotic (de)escalation, LOS, mortality and costs as secondary outcomes. There were three arms to the study – standard of care blood culture pathogen ID via MALDI-TOF, FilmArray, and FilmArray along with active antimicrobial stewardship involving an infectious disease specialist or pharmacist. The FilmArray was able to ID 81% of organisms due to inclusion on the panel. Duration of vancomycin therapy was not different among the groups, but when organisms not requiring vancomycin were identified, the median duration of vancomycin administration was shorter in both FilmArray arms compared to the standard arm. For infections caused by vancomycin-susceptible enterococci, vancomycin duration was longer in the FilmArray arms. Duration of narrow spectrum -lactam use was also greater in the FilmArray arms, whereas the duration of piperacillin-tazobactam was shorter in the FilmArray arms. There were no differences in clinical or microbiologic outcomes among the groups. Total costs were not significantly different between intervention and control groups. The authors conclude that antimicrobial stewardship is improved with the rapid multiplex ID panels.

Salimnia et al3 reported on the clinical performance of the FilmArray system as part of the data from a large multi-center clinical trial submitted to the FDA for approval. The comparator results for bacterial and fungal infections were obtained by the standard phenotypic identification procedure used in each laboratory. For the resistance markers, molecular detection methods were used as the comparator. For gram-positive organisms, the FilmArray system showed a sensitivity of 97.3% and a specificity of 99.8%. For gram-negative organisms, sensitivity and specificity were 98.1% and 99.9%, respectively. For Candida species, sensitivity/specificity was 99.2%/99.9%, respectively. For detection of resistance markers, sensitivity/specificity was 98.4%/98.3% for mecA, and 100%/100% for both vanA/B and blaKPC. Overall, repeat testing was necessary in 1.9% of specimens, and 5.2% showed polymicrobial infections. Approximately 12% of the blood cultures contained organisms not included in the FilmArray panel and thus were not detected. Almost half of the organisms that could not be identified by the FilmArray panel were considered skin contaminants and thus not clinically relevant.

Verigene

The Verigene blood culture ID system differs from FilmArray in that there are two separate panels – one for gram-negative and one for gram-positive bacteria, and that there are no targets for yeast on these panels. One advantage of this approach is that analysis of more resistance genes can be performed in the multiplex reactions. The gram-negative panel includes nine common causative organisms of bloodstream infections along with 6 resistance markers (Table 2). The gram-positive panel includes 4 genera, 9 species and 3 resistance markers (Table 3). The turnaround time is about 2.5 hours for the Verigene system.

The Verigene gram-positive blood culture panel has been evaluated in several studies. Rapid ID of gram-positive organisms is especially important since most contaminants are gram positive, and the distinction between a pathogen and a contaminant can be made much faster.

Dodemont et al4 identified 95.6% of gram-positive organisms isolated from positive blood cultures, with those not identified not included on the panel. There was an 87.6% agreement between the Verigene result and identification with MALDI-TOF and a 97.7% agreement with mecA gene detection and culture-based resistance testing. Identification with the Verigene system was higher for monomicrobial cultures (92.6%) than for polymicrobial ones (74.3%).

The performance of the Verigene gram-negative panel has also been reported. Dodemont et al5 reported that agreement of the Verigene gram-negative panel in monomicrobial infections was greater (99.0%) than in polymicrobial infections (83.3%). Overall, the panel was able to ID 90% of the positive blood cultures.

Ledeboer et al6 also evaluated the Verigene gram-negative panel in comparison to standard culture methods and biochemical identification. The positive percent agreement ranged from 92.9% to 100% depending on the species, and negative percent agreement was >99.5% overall. Agreement for the resistance markers ranged from 94.3% to 100%. For polymicrobial samples, the Verigene identified at least one of the organisms in 95.4% of the specimens and all of the organisms in 54.5%.

Comparing FilmArray and Verigene

Bhatti et al7 reported on the performance of both the FilmArray and Verigene systems simultaneously and compared their results to ID using MALDI-TOF and conventional automated susceptibility testing. The time to identification of monomicrobial blood cultures was significantly shorter for both platforms compared to conventional ID, with the FilmArray system providing an ID in less time than the Verigene. Both platforms were able to correctly ID 92% of the monomicrobial cultures studies, with the 8% not identified due to the fact that the organisms were not included in the panels. The authors concluded that while both systems provide reliable and rapid detection of most bloodstream pathogens, subculturing is still required to detect organisms not included on the panels and to provide phenotypic susceptibility results.

Clinical Outcome and Economic-based Studies

Several studies have examined the impact of rapid blood culture ID on antibiotic stewardship and health care economics. Bork et al8 combined antibiotic stewardship intervention with the performance of the Verigene gram-negative panel. In addition to showing both sensitivity and specificity greater than 95%, the authors demonstrated significantly decreased time to both effective and optimal antibiotic therapy in the Verigene group compared to the control group. Pardo et al9 reported on the impact of the BioFire system on clinical decision making in real time in a pre-post intervention quasi-experimental study. Only gram-positive organisms and yeasts were included as they did not expect rapid ID of gram-negative organisms to have an impact on empiric therapy at their institution. The BioFire panel correctly identified 100% of the isolates in the study compared to conventional ID. For gram-positive organisms, results were available 24.7 hours earlier than conventional ID and 47.4 hours earlier than susceptibility results. For Candida, results were available 24.7 hours before conventional ID and 95.9 hours before susceptibility. The authors found that length of stay (LOS) was reduced in the post-implementation (i.e., BioFire) group (2.3 vs. 2.9 days) resulting in an estimated overall cost avoidance of $30,000 per 100 patients tested. Total ICU costs, ICU LOS, and mortality were also statistically significantly reduced post-implementation. Additionally, patients found to have methicillin-susceptible Staphylococcus aureus (MSSA) infections received shorter courses of vancomycin. However, the proportion of patients with enterococcal infections receiving empiric therapy for vancomycin resistance was not reduced post-implementation, nor was the time to active therapy improved for patients with MRSA bacteremia or candidemia.

Table 1 – Organisms and resistance genes detected by BioFire FilmArray blood culture panel

Gram+ Bacteria Gram– Bacteria
Enterococcus
Listeria monocytogenes
Staphylococcus
Staphylococcus aureus
Streptococcus
Streptococcus agalactiae
Streptococcus pyogenes
Streptococcus pneumoniae
Acinetobacter baumannii
Haemophilus influenzae
Neisseria meningitidis
Pseudomonas aeruginosa
Enterobacteriaceae
Enterobacter cloacae complex
Escherichia coli
Klebsiella oxytoca
Klebsiella pneumoniae
Proteus
Serratia marcescens
Yeast Antibiotic Resistance
Candida albicans
Candida glabrata
Candida krusei
Candida parapsilosis
Candida tropicalis
mecA - methicillin resistant
vanA/B - vancomycin resistant
KPC - carbapenem resistant

Table 2- Organisms and resistance genes detected by Verigene Gram negative blood culture panel

Organisms
Escherichia coli
Klebsiella pneumoniae
Klebsiella oxytoca
Pseudomonas aeruginosa
Serratia marcescens
Acinetobacter spp.
Citrobacter spp.
Enterobacter spp.
Proteus spp.
Resistance
CTX-M
IMP
KPC
NDM
OXA
VIM

Table 3 - Organisms and resistance genes detected by Verigene Gram positive blood culture panel

Organisms
Staphylococcus aureus
Staphylococcus epidermidis
Staphylococcus lugdunensis
Streptococcus anginosis group
Streptococcus agalactiae
Streptococcus pneumoniae
Streptococcus pyogenes
Enterococcus faecalis
Enterococcus faecium
Staphylococcus spp.
Streptococcus spp.
Micrococcus spp.
Listeria spp.
Resistance
mecA
vanA
vanB
References
  1. Kumar et al. 2006. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. 34(6):1589-96.
  2. Banerjee et al. 2015. Of rapid multiplex poltmerase chain reaction-based blood culture identificiation and susceptibility testing. Clin Infect Dis 61:1071-1080.
  3. Salimnia et al. 2016. Evaluation of the FilmArray blood culture identification panel:results of a multicenter controlled trial. J Clin Microbiol 54:687-698.
  4. Dodemont et al. 2014. Performance of the Verigene gram-negative blood culture assay for rapid detection of bacteria and resistance determinants. J Clin Microbiol 52:3085-3087.
  5. Dodemont et al. 2015. Evaluation of Verigene gram positive blood culture assay performance for bacteremic patients. Eur J Clin Microbiol Infect Dis 34:473-477.
  6. Ledeboer et al. 2015. Identification of gram-negative bacteria and genetic resistance determinants from positive blood culture broths by use of the Verigene gram-negative blood culture multiplex microarray-based molecular assay. J Clin Microbiol 53:2460-2472.
  7. Bhatti et al. 2014. Evaluation of the FilmArray and Verigene systems for rapid identification of positive blood cultures. J Clin Microbiol 52:3433-3436.
  8. Bork et al. 2015. Rapid testing using the Verigene gram negative blood culture nucleic acid test in combination with antimicrobial stewardship intervention against gram negative bacteremia. Antimicrob Agents and Chemother 59:1588-1595.
  9. Pardo et al. 2016. Clinical and economic impact of antimicrobial stewardship interventions with the FilmArray blood culture identification panel. Diag Microbiol and Infect Dis 84:159-164.
  10. Buchan et al. 2012. Comparison of the MALDI biotyper system using Sepsityper specimen processing to routine microbiological methods for identification of bacteria from positive blood culture bottles. J Clin Microbiol 50:346-352.
  11. Harris, D.M. and D.J. Hata. 2013. Rapid identification of bacteria and candida using pna-fish from blood and peritoneal fluid cultures:a retrospective clinical study. Ann Clin Microbiol and Antimicrob 12:2.
  12. Metzgar et al. 2016. The IRIDICA BAC BSI assay: rapid, sensitive and culture-independent identification of bacteria and candida in blood. PLOS ONE July 6, 2016.
  13. Pancholi et al. 2018. Multicenter Evaluation of the Accelerate PhenoTest™ BC Kit for Rapid Identification and Phenotypic Antimicrobial Susceptibility Testing Using Morphokinetic Cellular Analysis. J Clin Microbiol Jan 5. pii: JCM.01329-17.
  14. Grumaz et al. 2016. Next generation sequencing diagnostics of bacteremia in septic patients. Genome Medicine 8:73.

Franklin R. Moore, MD, PhD, FCAP, D(ABMM), is currently the associate chief of clinical pathology and medical director of the molecular and microbiology laboratories at the University of Massachusetts Medical School-Baystate.

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