Diversity among 2481 Escherichia coli from women with community-acquired lower urinary tract infections in 17 countries
Bibliographic record
Abstract
OBJECTIVES: In the recently published ECO.SENS survey, the antimicrobial susceptibility of Escherichia coli from urinary tract infections in women in 16 European countries and Canada was investigated. This study reports the diversity among these E. coli. METHODS: The 2481 E. coli, typed with the PhenePlate (PhP) System utilizing the dynamics and end result of 11 biochemical reactions in a microplate system, were clustered and the Simpson's index of diversity calculated. RESULTS: Seventy-four Common PhP Types (CT) comprising 2067 isolates and 414 Single Types (Si) were identified. Of these, 916 isolates (37%) belonged to one of the four most frequent CT (arbitrarily numbered CT48, 10, 26 and 20). CT48 with 400 isolates and 11 different susceptibility patterns, was widely disseminated across Europe and Canada and was the most frequent type in 13 countries and the second most frequent in the remaining four countries. Sixty-four per cent of the E. coli were susceptible to all eight investigated antimicrobials (CT48: 73%, CT10: 77%, CT26: 62% and CT20: 37%). Forty-six different susceptibility patterns were seen, the three most common being isolated resistance to ampicillin, resistance to ampicillin and trimethoprim, and isolated resistance to trimethoprim. Multiresistance, here defined as resistance to four or more of the investigated antibiotics, was distributed among E. coli belonging to several PhP types. CONCLUSIONS: There was no obvious correlation between the phenotypes identified with the PhP System and the susceptibility pattern. The data did not indicate clonal dissemination within or between countries as a major reason for differences in antimicrobial resistance rates.
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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 | 0.000 |
| 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".