Klebsiella pneumoniae ST307 with OXA-181: threat of a high-risk clone and promiscuous plasmid in a resource-constrained healthcare setting
Bibliographic record
Abstract
INTRODUCTION: Klebsiella pneumoniae with OXA-48-like enzymes were introduced into Tshwane Tertiary Hospital (TTH) (Pretoria, South Africa) during September 2015, causing nosocomial outbreaks. METHODS: PCR methodologies and WGS were used to characterize K. pneumoniae with carbapenemases (n = 124) from TTH (July 2015-December 2016). RESULTS: PCR was used to track K. pneumoniae ST307 with OXA-181 among 60% of carbapenemase-positive isolates in different wards/units over time and showed the transmission of IncX3 plasmids to other K. pneumoniae clones. WGS identified different ST307 clades: 307_OXA181 (consisting of two lineages, A and B) with OXA-181 on IncX3 plasmids (named p72_X3_OXA181) and clade 307_VIM with VIM-1 on IncFII plasmids. Clade 307_OXA181 lineage B was responsible for the rapid increase and transmission of OXA-181 K. pneumoniae in various wards/units throughout TTH, while the numbers of clade 307_OXA181 lineage A and clade 307_VIM remained low. Separate outbreaks were due to K. pneumoniae ST17 and ST29 with p72_X3_OXA181 plasmids. CONCLUSIONS: The high-risk clone K. pneumoniae ST307 with OXA-181 rapidly spread to different wards/units despite infection and prevention measures. ST307 clades and lineages seemingly acted differently in outbreak situations. This study also highlighted the threat of promiscuous plasmids such as p72_X3_OXA181.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".