Genomic Characterization of NDM‐1 Harboring Extensively‐Drug Resistance <i>Klebsiella pneumoniae</i> Isolate From ICU‐Admitted Patient With COVID‐19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, carbapenem‐resistant Klebsiella pneumoniae (CR‐KP) strains, particularly those producing New Delhi metallo‐beta‐lactamase (NDM), are increasingly recognized as a significant threat to global health. The present study aimed to conduct a genomic analysis of an NDM‐1‐producing CR‐KP strain isolated from patients with coronavirus disease of 2019 (COVID‐19) admitted to the intensive care unit (ICU). The K. pneumoniae isolate was obtained from the bronchoalveolar lavage fluid of a 68 year‐old male patient hospitalized in the ICU with COVID‐19 at Besat Hospital in Sanandaj, Iran. The minimum inhibitory concentrations (MICs) for 15 antibiotics were determined using the VITEK 2 system. Genomic analysis of the isolate was performed using whole genome sequencing. The CRKP‐51 strain was identified as an extensively drug‐resistant (XDR) strain, exhibiting resistance to all tested antibiotics except tigecycline (MIC = 2 μg/mL). The highest resistance values were recorded against sulfamethoxazole‐trimethoprim (SXT), nitrofurantoin (NIT), and piperacillin‐tazobactam (TZP), with MICs of ≥ 320, 256 μg/mL, and ≥ 128 μg/mL, respectively. Multilocus sequence typing revealed that CRKP‐51 belonged to sequence type 15 (ST15). The IncHI1B replicon type associated with this strain harbored several resistance genes, including b l a N D M −1 , armA , msrE , mphE , BRP (MBL), b l a O X A −1 , aadA 2, dfrA 12, qnrB 1, b l a C T X − M −15 , and cat 1. High‐risk K. pneumoniae clones, such as ST15, are increasingly associated with antimicrobial resistance and the emergence of XDR strains in ICUs. Additionally, the global dissemination of the NDM enzyme occurs through various plasmid replicon types. Therefore, monitoring local epidemiology is essential for the effectiveness of antimicrobial stewardship programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it