BioFire FilmArray Pneumonia Panel enhances detection of pathogens and antimicrobial resistance in lower respiratory tract specimens

Performance of a hybrid capture-based target enrichment next-generation sequencing for the identification of respiratory pathogens and resistance-associated genes in patients with severe pneumonia

Severe pneumonia remains the leading infectious cause of death worldwide. The time-consuming nature and suboptimal sensitivity of sputum cultures hamper prompt pathogen detection for tailored treatments. Advanced techniques such as polymerase chain reaction (PCR) and next-generation sequencing (NGS) offer rapid genetic pathogen detection and identification of antimicrobial resistance (AMR) genes. However, the performance of hybrid capture-based target enrichment NGS, e.g., Respiratory Pathogen ID/AMR Enrichment Panel (RPIP), for pathogen detection in patients with severe pneumonia remains uncertain. A prospective study involving adults with severe pneumonia was conducted. Respiratory samples from the lower respiratory tract were collected via bronchoalveolar lavage, bronchial washing, or endotracheal tube suction. The performance of RPIP in pathogen and AMR-associated gene detection was compared to that of conventional culture methods and the multiplex PCR-based FilmArray Pneumonia Panel (FilmArray-PN). A total of 83 subjects were enrolled. The most prevalent pathogens detected by RPIP were Rothia mucilaginosa, Stenotrophomonas maltophilia, Pseudomonas aeruginosa; herpes simplex virus-1, cytomegalovirus, and Epstein-Barr virus, and Pneumocystis jirovecii. Overall, the positive and negative agreement rates for bacterial detection were 63.6% and 97.5% between RPIP and culture methods, respectively, and 55.8% and 99.4% between FilmArray-PN and culture methods, respectively. Compared to FilmArray-PN, RPIP exhibited significantly better detection rates for bacteria (P = 0.029), viruses (P < 0.001), and fungi (P < 0.001) and identified additional blaOXA, blaCMY as extended-spectrum β-lactamase genes and blaOXA, blaSHV as carbapenemase genes. In conclusion, RPIP can sensitively profile respiratory pathogens and is a promising tool for detecting multiple microorganisms and AMR-associated genes in patients with severe pneumonia.IMPORTANCESensitive pathogen detection is pivotal for timely treatment by tailoring adequate antimicrobial agents. Unlike conventional phenotypic approach, novel measures using molecular interrogation appear promising. This study aimed to elucidate the efficacy of a hybrid capture-based target enrichment next-generation sequencing technique (Respiratory Pathogen ID/AMR Enrichment Panel, RPIP) as exemplified in a cohort with severe pneumonia. Pathogen landscape in the population was illustrated by these three methodologies. As compared with multiplex polymerase chain reaction-based FilmArray Pneumonia Panel and conventional culture, RPIP demonstrated significantly improved sensitivity in identifying bacteria, viruses, and fungi. The RPIP also exhibited better performance in identifying different pathogens in patients co-infected with multiple microorganisms. Additionally, the genotypes contributing to antimicrobial resistance were determined by RPIP. The study facilitated the implementation of molecular diagnosis by presenting real-world data, whereas future studies are mandated to generalize such an approach toward different clinical settings.

Towards improved point-of-care (POC) testing for patients with suspected sepsis: POC tests for host biomarkers and possible microbial pathogens

INTRODUCTION

Sepsis is a heterogeneous syndrome often misdiagnosed. Point-of-care (POC) diagnostic tests are commonly used to guide decision and include host biomarkers and molecular diagnostics.

AREAS COVERED

The diagnostic and prognostic accuracy of established and emerging biomarkers for sepsis, including procalcitonin (PCT) soluble urokinase plasminogen activator receptor (suPAR), presepsin, TRAIL/IP-10/CRP, MxA, and MxA-CRP, are analyzed in this review. The clinical utility of the two prevalent molecular techniques for pathogens identification using polymerase chain reaction (PCR) assays is also presented: FILMARRAY and QIAstat-Dx RP.

EXPERT OPINION

The rising benefits of the combined use of POC biomarkers with molecular diagnostics in daily clinical routine appear to outperform conventional practices in terms of reduced turnaround time, timely diagnosis, and prompt administration of the appropriate treatment. Yet, this must be further demonstrated in future investigations. However, the cost-effectiveness of POC tests and the high rate of false positive and negative results, indicate the need for a comprehensive clinical evaluation.

Utility of a multiplex pathogen detection system directly from respiratory specimens for treatment and diagnostic stewardship

The availability of syndrome-based panels for various ailments has widened the scope of diagnostics in many clinical settings. These panels can detect a multitude of pathogens responsible for a particular condition, which can lead to a timely diagnosis and better treatment outcomes. In contrast to traditional identification methods based on pathogen growth on culture, syndrome-based panels offer a quicker diagnosis, which can be especially beneficial in situations requiring urgent care, such as intensive care units. One such panel is the Biofire Filmarray Pneumonia plus Panel (BFP), which we have compared against microbiological culture and identification. The lower respiratory samples from patients were tested with BFP, culture, and identification with culture considered the gold standard. The phenotypic antibiotic susceptibility results (Vitek 2) were compared with the antimicrobial resistance (AMR) genes detected in BFP. Statistical analysis was carried out using GraphPad 7.0 and MS Excel (Microsoft Inc.). The results showed a positive percent agreement of 100% and a negative percent agreement of 47.8% with an overall agreement of 76.72% compared to culture. BFP was better at identifying fastidious bacteria, and the agreement with culture was higher for high bacterial identification numbers (107 and 106). There was also a correlation between the number of pathogens detected and growth in culture. Carbapenemase genes were detected in around 80% of phenotypically resistant samples and correlated with in-house PCR 60% of the time. Hence, BFP results need to be interpreted with caution especially when multiple pathogens are detected. Similarly, the presence or absence of AMR genes should be used to guide the therapy while being watchful of unusual resistance or susceptibility. The cost constraints and low throughput call for patient selection criteria and prioritization in emergency or resource-limited conditions.IMPORTANCEApplication of syndrome-based panels in clinical microbiology is of huge support in infectious conditions requiring urgent interventions, such as pneumonia. Interpreting the results requires caution; hence, we have compared the results obtained from Biofire Filmarray Pneumonia plus Panel with standard microbiological methods.

Evaluation and clinical practice of pathogens and antimicrobial resistance genes of BioFire FilmArray Pneumonia panel in lower respiratory tract infections

BACKGROUND

Existing panels for lower respiratory tract infections (LRTIs) are slow and lack quantification of important pathogens and antimicrobial resistance, which are not solely responsible for their complex etiology and antibiotic resistance. BioFire FilmArray Pneumonia (PN) panels may provide rapid information on their etiology.

METHODS

The bronchoalveolar lavage fluid of 187 patients with LRTIs was simultaneously analyzed using a PN panel and cultivation, and the impact of the PN panel on clinical practice was assessed. The primary endpoint was to compare the consistency between the PN panel and conventional microbiology in terms of etiology and drug resistance, as well as to explore the clinical significance of the PN panel. The secondary endpoint was pathogen detection using the PN panel in patients with community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP).

RESULTS

Fifty-seven patients with HAP and 130 with CAP were included. The most common pathogens of HAP were Acinetobacter baumannii and Klebsiella pneumoniae, with the most prevalent antimicrobial resistance (AMR) genes being CTX-M and KPC. For CAP, the most common pathogens were Haemophilus influenzae and Staphylococcus aureus, with the most frequent AMR genes being CTX-M and VIM. Compared with routine bacterial culture, the PN panel demonstrated an 85% combined positive percent agreement (PPA) and 92% negative percent agreement (NPA) for the qualitative identification of 13 bacterial targets. PN detection of bacteria with higher levels of semi-quantitative bacteria was associated with more positive bacterial cultures. Positive concordance between phenotypic resistance and the presence of corresponding AMR determinants was 85%, with 90% positive agreement between CTX-M-type extended-spectrum beta-lactamase gene type and phenotype and 100% agreement for mecA/C and MREJ. The clinical benefit of the PN panel increased by 25.97% compared with traditional cultural tests.

CONCLUSION

The bacterial pathogens and AMR identified by the PN panel were in good agreement with conventional cultivation, and the clinical benefit of the PN panel increased by 25.97% compared with traditional detection. Therefore, the PN panel is recommended for patients with CAP or HAP who require prompt pathogen diagnosis and resistance identification.

Performance evaluation of a PCR panel (FilmArray® Pneumonia Plus) for detection of respiratory bacterial pathogens in respiratory specimens: A systematic review and meta-analysis

BACKGROUND

Accuracy and timing of antibiotic therapy remain a challenge for lower respiratory tract infections. New molecular techniques using Multiplex Polymerase Chain Reaction, including the FilmArray® Pneumonia Plus Panel [FAPP], have been developed to address this. The aim of this study is to evaluate the FAPP diagnostic performance for the detection of the 15 typical bacteria of the panel from respiratory samples in a meta-analysis from a systematic review.

METHODS

We searched PubMed and EMBASE from January 1, 2010, to December 31, 2022, and selected any study on the FAPP diagnostic performance on respiratory samples compared to the reference standard, bacterial culture. The main outcome was the overall diagnostic accuracy with sensitivity and specificity. We calculated the log Diagnostic Odds Ratio and analyzed performance for separate bacteria, antimicrobial resistance genes, and according to the sample type. We also reported the FAPP turnaround time and the out-of-panel bacteria number and species. This study is registered with PROSPERO (CRD42021226280).

RESULTS

From 10 317 records, we identified 30 studies including 8 968 samples. Twenty-one were related to intensive care. The overall sensitivity and specificity were 94% [95% Confidence Interval (CI) 91-95] and 98% [95%CI 97-98], respectively. The log Diagnostic Odds Ratio was 6.35 [95%CI 6.05-6.65]. 9.3% [95%CI 9.2-9.5] of bacteria detected in culture were not included in the FAPP panel.

CONCLUSION

This systematic review reporting the FAPP evaluation revealed a high accuracy. This test may represent an adjunct tool for pulmonary bacterial infection diagnostic and antimicrobial stewardship. Further evidence is needed to assess the impact on clinical outcome.

Diagnostic Performance of BD Phoenix CPO Detect Panels for Detection and Classification of Carbapenemase-Producing Gram-Negative Bacteria

BD Phoenix CPO Detect panels can identify and classify carbapenemase-producing organisms (CPOs) simultaneously with antimicrobial susceptibility testing (AST) for Gram-negative bacteria. Detection and classification of carbapenemase producers were performed using the BD Phoenix CPO Detect panels NMIC/ID-441 for Enterobacterales, NMIC/ID-442 for nonfermenting bacteria, and NMIC-440 for both. The results were compared with those obtained using comparator methods. A total of 133 strains (32 Klebsiella pneumoniae, 37 Enterobacter cloacae complex, 33 Pseudomonas aeruginosa, and 31 Acinetobacter baumannii complex strains), including 60 carbapenemase producers (54 imipenemases [IMPs] and 6 OXA type), were analyzed. Using panels NMIC-440 and NMIC/ID-441 or NMIC/ID-442, all 54 IMP producers were accurately identified as CPOs (positive percent agreement [PPA], 100.0%; 54/54). Among the 54 IMP producers identified as CPOs using panels NMIC-440 and NMIC/ID-441, 12 and 14 Enterobacterales were not resistant to carbapenem, respectively. Among all 54 IMP producers, 48 (88.9%; 48/54) were correctly classified as Ambler class B using panel NMIC-440. Using panels NMIC-440 and NMIC/ID-442, all four OXA-23-like carbapenemase-producing A. baumannii complex strains (100.0%, 4/4) were correctly identified as CPOs, and three (75.0%, 3/4) were precisely classified as class D using panel NMIC-440. Both carbapenemase producers harboring the blaISAba1-OXA-51-like gene were incorrectly identified as non-CPOs using panels NMIC-440 and NMIC/ID-442. For detecting carbapenemase producers, the overall PPA and negative percent agreement (NPA) between panel NMIC-440 and the comparator methods were 96.7% (58/60) and 71.2% (52/73), respectively, and the PPA and NPA between panels NMIC/ID-441 or NMIC/ID-442 and the comparator methods were 96.7% (58/60) and 74.0% (54/73), respectively. BD Phoenix CPO Detect panels can successfully screen carbapenemase producers, particularly IMP producers, regardless of the presence of carbapenem resistance and can be beneficial in routine AST workflows. IMPORTANCE Simple and efficient screening methods of detecting carbapenemase producers are required. BD Phoenix CPO Detect panels effectively screened carbapenemase producers, particularly IMP producers, with a high overall PPA. As the panels enable automatic screening for carbapenemase producers simultaneously with AST, the workflow from AST to confirmatory testing for carbapenemase production can be shortened. In addition, because carbapenem resistance varies among carbapenemase producers, the BD Phoenix CPO Detect panels, which can screen carbapenemase producers regardless of carbapenem susceptibility, can contribute to the accurate detection of carbapenemase producers. Our results report that these panels can help streamline the AST workflow before confirmatory testing for carbapenemase production in routine microbiological tests.

Usefulness of the FilmArray blood culture identification panel for identifying causative pathogens of bone and joint infections

As bone and joint infections (BJIs) require long-term treatment, identifying their causative pathogens is vital. However, the detection rate of conventional culturing remains inadequate. This study aimed to evaluate the usefulness of the FilmArray blood culture identification (BCID) panel for identifying causative pathogens in patients with BJIs. We tested a BCID panel using collected samples, in addition to conventional cultures. The primary outcome was to evaluate the diagnostic performance of the BCID panel, calculated using conventional culturing methods. A total of 44 patients who underwent BJI-related specimen collection were enrolled. Of the 44 patients, 22 were diagnosed with a BJI. Conventional culture identified 15 of 22 organisms (68.2%), whereas the BCID panel identified 14 of 22 organisms (63.4%). The overall sensitivity and specificity of the BCID panel were 73.3% and 57.1%, respectively, compared to those of the conventional culture. However, the sensitivity reached 100% when only pathogens included in the BCID panel were considered. In seven culture-negative cases, the BCID panel identified three organisms (42.9%). The BCID panel also indicated the appropriate therapy against a BJI caused by methicillin-resistant Staphylococcus aureus by detecting the mecA gene. This study demonstrated that the BCID panel has the potential for early and accurate diagnosis of the causative organism of BJI using specimens such as joint fluid and bone tissue. Our results suggest that BCID panels, in addition to routine culture, may improve our ability to diagnose the causative microorganisms of BJI in clinical practice, thereby contributing to the selection of appropriate antimicrobial agents.