High prevalence of metallo-β-lactamase among carbapenem-resistant <i>Klebsiella pneumoniae</i> in a teaching hospital in China
Bibliographic record
Abstract
The aim of this study was to characterize the carbapenemases in carbapenem-resistant Klebsiella pneumoniae (CR-KP) from a Chinese teaching hospital. A total of 40 CR-KPs were screened for the presence of carbapenemases. Minimum inhibitory concentrations were determined by agar dilution. The modified Hodge test was used for the detection of carbapenemase production. Carbapenemase, extended-spectrum β-lactamase, and AmpC genes were detected using polymerase chain reaction (PCR) and sequencing. A conjugation test was performed using a broth culture mating method, transferred plasmids were typed by PCR-based replicon typing, and clonal relatedness was investigated by enterobacterial repetitive intergenic consensus sequences PCR (ERIC-PCR) and multilocus sequence typing (MLST). The results revealed that modified Hodge test was positive for 28 CR-KPs, and CR-KPs exhibited high resistance rates against various antibiotics, except colistin (5.0%) and tigecycline (22.5%). ERIC and MLST profiles showed no clonal outbreak. PCR demonstrated a high prevalence rate (55.0%, 22/40) of metallo-β-lactamases (MBLs) in CR-KPs. IMP-4, IMP-8, NDM-1, and KPC-2 were identified in 14 (35.0%), 7 (17.5%), 2 (5.0%), and 7 (17.5%) isolates, respectively. Notably, 2 CR-KPs coproduced 2 carbapenemases simultaneously (IMP-8/NDM-1 and IMP-4/KPC-2). In vitro transfer of carbapenem resistance was successful for 11 MBL-producing CR-KPs. The extended spectrum β-lactamase genes were detected in 30 (75.0%) of these CR-KPs. To the best of our knowledge, this is the first report focusing on carbapenem resistance in K. pneumoniae due to metalloenzymes in China. Screening and surveillance of MBLs in Enterobacteriaceae is urgently needed in this region to control and prevent the spread of these resistance determinants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".