Prevalence and Mechanisms of Erythromycin Resistance in Group A and Group B <i>Streptococcus</i> : Implications for Reporting Susceptibility Results
Bibliographic record
Abstract
Increased rates of erythromycin resistance among group B Streptococcus (GBS) and group A Streptococcus (GAS) have been reported. Cross-resistance to clindamycin may be present, depending on the mechanism of resistance. We determined the prevalence of macrolide-resistant determinants in GBS and GAS isolates to guide the laboratory reporting of erythromycin and clindamycin susceptibility. Susceptibilities were determined by the disk diffusion and broth microdilution methods. Inducible and constitutive resistance to clindamycin was determined by the double-disk diffusion method. The presence of the ermTR, ermB, and mefA genes was confirmed by PCR. Of the 338 GBS isolates, 55 (17%) were resistant to erythromycin, whereas 26 (8%) were resistant to clindamycin. The erm methylase gene was identified in 48 isolates, 22 of which had inducible resistance to clindamycin and 26 of which had constitutive resistance to clindamycin. The remaining seven resistant isolates had mefA. Of the 593 GAS isolates, 49 (8%) and 6 (1%) isolates were resistant to erythromycin and clindamycin, respectively. Erythromycin resistance was due to mefA in 33 isolates, whereas 14 isolates had erm-mediated resistance (9 isolates had inducible resistance and 5 isolates had constitutive resistance). In our population, erythromycin resistance in GAS was predominantly mediated by mefA and erythromycin resistance in GBS was predominantly mediated by erm. Regional differences in mechanisms of resistance need to be taken into consideration when deciding whether to report clindamycin susceptibility results on the basis of in vitro test results. Testing by the double-disk diffusion method would be an approach that could be used to address this issue, especially for GAS.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".