Macrolide and Clindamycin Resistance in<i>Streptococcus milleri</i>Group Isolates from the Airways of Cystic Fibrosis Patients
Bibliographic record
Abstract
Organisms belonging to the Streptococcus milleri group (SMG) are known for their role in pyogenic infections but have recently been implicated as etiological agents of pulmonary exacerbation in adult patients with cystic fibrosis (CF). The prolonged exposure of CF patients to antibiotics prompted us to investigate the susceptibility profiles of 118 SMG isolates from the airways of CF patients to 12 antibiotics compared to 43 SMG isolates from patients with invasive infections. We found that approximately 60% of all isolates failed to grow using the standard medium for disc diffusion, Mueller-Hinton blood agar (MHBA), so we explored the usefulness of brain heart infusion (BHI) agar for susceptibility testing. Zone-of-inhibition comparisons between BHI and MHBA showed strong correlations for six antibiotics, and interpretations were similar for both medium types. For ceftriaxone and cefepime, both groups of isolates were highly susceptible. Tetracycline resistance levels were comparable between the two groups (22% in CF isolates and 17.4% in invasive isolates). However, more than half of the CF isolates were not susceptible to azithromycin, erythromycin, and clindamycin, compared to 11%, 13%, and 6.5% of invasive isolates, respectively. There were 5-fold and 8-fold increased risks of azithromycin and clindamycin resistance, respectively, for the isolates from the airways of CF patients relative to the invasive isolates. Macrolide resistance was strongly linked to chronic azithromycin therapy in CF patients. This study shows that BHI agar is a suitable alternative for antimicrobial susceptibility testing for the SMG and that SMG isolates from the airways of CF patients are more resistant to macrolides and clindamycin than strains isolated from patients with invasive infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".