Antimicrobial susceptibility testing reveals reduced susceptibility to azithromycin and other antibiotics in Legionella pneumophila serogroup 1 isolates from Portugal
Bibliographic record
Abstract
BACKGROUD: Although not fully investigated, studies show that Legionella pneumophila can develop antibiotic resistance. As there is limited data available for Portugal, we determined the antibiotic susceptibility profile of Portuguese L. pneumophila serogroup 1 (LpnSg1) isolates against antibiotics used in the clinical practice in Portugal. METHODS: Minimum inhibitory concentrations (MICs) were determined for LpnSg1 clinical (n = 100) and related environmental (n = 7) isolates, collected between 2006-2022 in the context of the National Legionnaire´s Disease Surveillance Programme, against azithromycin, clarithromycin, erythromycin, levofloxacin, ciprofloxacin, moxifloxacin, rifampicin, doxycycline, tigecycline, and amoxicillin/clavulanic acid, using three different assays. Isolates were also PCR-screened for the presence of the lpeAB gene. RESULTS: Twelve isolates had azithromycin MICs above the EUCAST tentative highest WT MIC, 9 of which were lpeAB negative; for erythromycin and clarithromycin, all isolates tested within the susceptible range. The number of isolates with MICs above the tentative highest WT MIC for the remaining antibiotics was: ciprofloxacin: 7; levofloxacin: 17; moxifloxacin: 8; rifampicin: 11; doxycycline: 82; tigecycline: 4. EUCAST breakpoints are not available for amoxicillin/clavulanic acid. We estimated the ECOFFs and one isolate had a MIC eightfold higher than the E-test ECOFF. Additionally, a clinical isolate generated three colonies growing on the E-test inhibition zone that resulted in MICs fourfold higher than for the parental isolate. CONCLUSIONS: We report, for the first time, elevated MICs against first-line and other antibiotics (including azithromycin, fluoroquinolones and amoxicillin/clavulanic acid commonly used to treat pneumonia patients in Portugal) in Portuguese L. pneumophila strains. Results point towards decreased susceptibility in circulating strains, justifying further investigation.
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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 | 0.001 | 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".