Worldwide incidence, molecular epidemiology and mutations implicated in fluoroquinolone-resistant Streptococcus pneumoniae: data from the global PROTEKT surveillance programme
Bibliographic record
Abstract
OBJECTIVES: To analyse the mutations and epidemiology associated with fluoroquinolone-resistant pneumococci collected as part of the PROTEKT global surveillance programme during 1999-2000. METHODS: Sixty-nine centres in 25 countries submitted a total of 3362 Streptococcus pneumoniae isolates, for which the MICs of antimicrobial agents were determined using NCCLS methodology. RESULTS: Levofloxacin resistance was low overall (1% worldwide), with higher rates in: Hong Kong (14.3%), South Korea (2.9%), USA (1.8%), Mexico (1.5%), Canada (1.4%) and Japan (1.3%). Levofloxacin resistance was very low or absent in European countries, and absent in Australia. Worldwide, there was a total of 35 levofloxacin-resistant isolates, of which 22 (63%) were resistant and 10 (29%) were intermediate to moxifloxacin. All levofloxacin-resistant isolates were susceptible to telithromycin (< or =0.5 mg/L), linezolid (< or =2 mg/L) and quinupristin/dalfopristin (< or =1 mg/L). One or more mutations in the topoisomerase genes were identified in all levofloxacin-resistant isolates; most of these isolates (33/35) had a mutation in one of the DNA gyrase encoding genes (gyrA, gyrB) and one of the topoisomerase IV encoding genes (parC, parE). Eighteen (51%) isolates carried the same combination of amino acid substitutions: Ser-81-->Phe in GyrA and Ser-79-->Phe in ParC. Isolates displaying a levofloxacin MIC of 2-4 mg/L generally had no mutation or one mutation in either a DNA gyrase or a topoisomerase IV gene, although most mutations were in parC. CONCLUSIONS: Most levofloxacin-resistant isolates possess two mutations (one in DNA gyrase and one in topoisomerase IV). Although multilocus sequence typing demonstrated that most of these isolates were unrelated, 12 (34%) were the Spain23F-1 clone: 10 from Hong Kong and one each from Saskatchewan, Canada and Sao Paulo, Brazil.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".