Comparison of ERIC carbapenem-resistant Enterobacteriaceae test, BD Phoenix CPO detect panel, and NG-test CARBA 5 for the detection of main carbapenemase types of carbapenem-resistant Enterobacterales.

BACKGROUND: This study aimed to assess the performance of three commercial panels, the ERIC Carbapenem-Resistant Enterobacteriaceae Test (ERIC CRE test), the NG-Test CARBA 5 (NG CARBA 5), and the BD Phoenix CPO Detect Panel (CPO panel), for the detection of main types of carbapenemases among carbapenem-resistant Enterobacterales (CRE). METHODS: We collected 502 isolates of carbapenem-resistant Enterobacterales (CRE) demonstrating intermediate or resistant profiles to at least one carbapenem antibiotic (ertapenem, imipenem, meropenem, or doripenem). Carbapenemase genes and their specific types were identified through multiplex PCR and sequencing methods. Subsequently, the ERIC CRE test, CPO panel, and NG CARBA 5 assay were conducted on these isolates, and the results were compared with those obtained from multiplex PCR. RESULTS: The results indicated that the ERIC CRE test exhibited an overall sensitivity and specificity of 98.1% and 93.6%, respectively, which were comparable to 99.1% and 90.6% for the NG CARBA 5. However, the CPO panel demonstrated a sensitivity of only 56.2% in identifying Ambler classes, exhibiting the poorest sensitivity for class A. Moreover, while the ERIC CRE test outperformed the NG CARBA 5 in identifying multi-gene isolates with multiple carbapenemase-encoding genes, the CPO panel failed to accurately classify these isolates. CONCLUSIONS: Our findings support the utilization of the ERIC CRE test as one of the methods for detecting carbapenemases in clinical laboratories. Nonetheless, further optimization is imperative for the CPO panel to enhance its accuracy in determining carbapenemase classification and address limitations in detecting multi-gene isolates.

Prediction of methicillin-resistant Staphylococcus aureus and carbapenem-resistant Klebsiella pneumoniae from flagged blood cultures by combining rapid Sepsityper MALDI-TOF mass spectrometry with machine learning.

This study investigated combination of the Rapid Sepsityper Kit and a machine learning (ML)-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) approach for rapid prediction of methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) from positive blood culture bottles. The study involved 461 patients with monomicrobial bloodstream infections. Species identification was performed using the conventional MALDI-TOF MS Biotyper system and the Rapid Sepsityper protocol. The data underwent preprocessing steps, and ML models were trained using preprocessed MALDI-TOF data and corresponding labels. The interpretability of the model was enhanced using SHapely Additive exPlanations values to identify significant features. In total, 44 S. aureus isolates comprising 406 MALDI-TOF MS files and 126 K. pneumoniae isolates comprising 1249 MALDI-TOF MS files were evaluated. This study demonstrated the feasibility of predicting MRSA among S. aureus and CRKP among K. pneumoniae isolates using MALDI-TOF MS and Sepsityper. Accuracy, area under the receiver operating characteristic curve, and F1 score for MRSA/methicillin-susceptible S. aureus were 0.875, 0.898 and 0.904, respectively; for CRKP/carbapenem-susceptible K. pneumoniae, these values were 0.766, 0.828 and 0.795, respectively. In conclusion, the novel ML-based MALDI-TOF MS approach enables rapid identification of MRSA and CRKP from flagged blood cultures within 1 h. This enables earlier initiation of targeted antimicrobial therapy, reducing deaths due to sepsis. The favourable performance and reduced turnaround time of this method suggest its potential as a rapid detection strategy in clinical microbiology laboratories, ultimately improving patient outcomes.

Geographic patterns of antimicrobial susceptibilities for Bacteroides spp. worldwide: Results from the Antimicrobial Testing Leadership and Surveillance (ATLAS) programme, 2007-2020.

Antimicrobial susceptibilities of 4973 Bacteroides spp. isolates recovered from various sources of patients from 12 countries (99.6% from European countries) in the Antimicrobial Testing Leadership and Surveillance (ATLAS) programme, 2007-2020, were investigated. The minimum inhibitory concentrations (MICs) of the isolates with six commonly used agents were determined using the agar dilution method. Among the isolates, 10 Bacteroides spp. were included: B. fragilis (n=3180, 64.0%) was encountered most frequently, followed by B. thetaiotaomicron (n=675) and B. ovatus (n=409). During the 14 years, the proportion of B. fragilis declined, but the proportion of non-fragilis Bacteroides spp. increased. More than 90% of the isolates tested were susceptible to piperacillin-tazobactam, meropenem and tigecycline. Significantly lower susceptibility rates to cefoxitin (P<0.001), clindamycin (P<0.001), piperacillin/tazobactam (P<0.001) and tigecycline (P=0.006) were observed among non-fragilis Bacteroides spp. isolates than among B. fragilis isolates. Moreover, the susceptibility rates to clindamycin (P=0.003) and tigecycline (P=0.044) decreased significantly among non-fragilis Bacteroides spp. over time. Clindamycin susceptibility rates >80% were found in Greece (100%), Sweden (86.3%) and the UK (80.7%), and the lowest susceptibility rates were found in the USA (42.9%) and Japan (53.9%). In conclusion, the susceptibility of Bacteroides spp. to commonly used antibiotics varied geographically. Empirical antibiotic therapy for suspected anaerobic infections with clindamycin and cefoxitin should be avoided due to high resistance rates. Piperacillin-tazobactam, meropenem, metronidazole and tigecycline could be considered favourable options for the treatment of infections caused by Bacteroides spp.

Direct prediction of carbapenem-resistant, carbapenemase-producing, and colistin-resistant Klebsiella pneumoniae isolates from routine MALDI-TOF mass spectra using machine learning and outcome evaluation.

The objective of this study was to develop a rapid prediction method for carbapenem-resistant Klebsiella pneumoniae (CRKP) and colistin-resistant K. pneumoniae (ColRKP) based on routine MALDI-TOF mass spectrometry (MS) results in order to formulate a suitable and rapid treatment strategy. A total of 830 CRKP and 1462 carbapenem-susceptible K. pneumoniae (CSKP) isolates were collected; 54 ColRKP isolates and 1592 colistin-intermediate K. pneumoniae (ColIKP) isolates were also included. Routine MALDI-TOF MS, antimicrobial susceptibility testing, NG-Test CARBA 5, and resistance gene detection were followed by machine learning (ML). Using the ML model, the accuracy and area under the curve for differentiating CRKP and CSKP were 0.8869 and 0.9551, respectively, and those for ColRKP and ColIKP were 0.8361 and 0.8447, respectively. The most important MS features of CRKP and ColRKP were m/z 4520-4529 and m/z 4170-4179, respectively. Of the CRKP isolates, MS m/z 4520-4529 was a potential biomarker for distinguishing KPC from OXA, NDM, IMP, and VIM. Of the 34 patients who received preliminary CRKP ML prediction results (by texting), 24 (70.6%) were confirmed to have CRKP infection. The mortality rate was lower in patients who received antibiotic regimen adjustment based on the preliminary ML prediction (4/14, 28.6%). In conclusion, the proposed model can provide rapid results for differentiating CRKP and CSKP, as well as ColRKP and ColIKP. The combination of ML-based CRKP with preliminary reporting of results can help physicians alter the regimen approximately 24 h earlier, resulting in improved survival of patients with timely antibiotic intervention.

Evaluation of the Rapid Sepsityper protocol and specific MBT-Sepsityper module for the identification of bacteremia and fungemia using Bruker Biotyper MALDI-TOF MS.

The rapid identification method, the Rapid Sepsityper protocol with a specific MBT-Sepsityper module (Bruker Daltonics), based on the MALDI Biotyper platform, accurately identified 93.5% (116/124) of microorganisms at the species level in the 124 flagged blood culture samples from patients with monomicrobial bloodstream infections. Gram-negative bacilli (95.6%, 43/45) had a higher identification rate than Gram-positive cocci (93.3%, 70/75) and yeasts (75%, 3/4). The Rapid Sepsityper protocol displayed poor identification performance for polymicrobial samples.