Longitudinal genomic surveillance of multidrug-resistant <i>Escherichia coli</i> carriage in critical care patients
Bibliographic record
Abstract
Abstract Background Colonization with multidrug resistant E. coli strains causes a substantial health burden in hospitalized patients. We performed a longitudinal genomics study to investigate the colonization of resistant E. coli strains in critically ill patients, and to identify evolutionary changes and strain replacement events within patients. Methods Patients were admitted to the intensive care unit and haematology wards at a major hospital in Lebanon. Perianal swabs were collected from participants on admission and during hospitalization, which were screened for extended-spectrum beta-lactamases and carbapenem-resistant Enterobacterales. We performed whole-genome sequencing and analysis on E. coli strains isolated from patients at multiple time points. Results The E. coli isolates were genetically diverse, with 13 sequence types (STs) identified among 21 isolates sequenced. Five patients were colonized by ST131 encoding CTX-M-27, a type of beta-lactamase gene not previously been observed in Lebanon. Among the eight patients whose resident E. coli strains were tracked over time, five harbored the same E. coli strain with relatively few mutations over the 5 to 10 days of hospitalization. The other three patients were colonized by different E. coli strains over time. Conclusion Our study provides evidence of strain diversity within patients during their hospitalization. While strains varied in their antimicrobial resistance profiles, the number of resistance genes did not increase over time. We also show that ST131 encoding CTX-M-27, which appears to be emerging as a globally important multidrug resistant E. coli strain, is also prevalent among critical care patients and deserves further monitoring.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".