The prevalence of CMY-2, OXA-48 and KPC-2 genes in clinical isolates of Klebsiella spp.
Bibliographic record
Abstract
Klebsiella pneumoniae is a Gram-negative bacterium which causes several human infections. Treatment of infections related to K. pneumoniae has become problematic, because of increasing trend of extended spectrum β-lactamases producing (ESBLs) strains. The present study was aimed to detect the prevalence of ESBL-producing Klebsiella spp. and KPC-2, CMY-2 and OXA-48 β-lactamase encoding genes in clinical isolates of Klebsiella spp. isolated from hospitalized patients. In this cross-sectional study carried out from February to August 2014, 144 isolates of Klebsiella spp. were collected from different clinical specimens in hospitals in the North of Iran. Klebsiella isolates were identified using standard microbiological procedure. Antimicrobial susceptibility patterns were determined using disk diffusion method in accordance with CLSI recommendation. The presence of antibiotic resistance genes were investigated by PCR method. Among 144 Klebsiella spp., 118 isolates were identified as K. pneumoniae and 26 isolates as Klebsiella oxytoca. Antibiotic susceptibility test showed the most resistance rates were against amoxicillin (96.5%) and ampicillin (95.8%). On the other hand, the most effective antibiotic was revealed to be imipenem with resistance rate of 4.9% (Table 2). Among 144 isolated Klebsiella strains, 57 cases (39.6%) were ESBL producers. The OXA-48 and KPC-2 genes were not detected among Klebsiella spp. during the present study, but 21.1% of isolates contained CMY-2 gene. This is the first report of CMY-2 gene detection in Klebsiella spp. in Iran. The homology between CMY-2 genes identified in isolates from Northern Iran and in other countries showed the wide dispersion of this gene around the world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".