Pharmacodynamic Modeling of Clarithromycin against Macrolide-Resistant [PCR-Positive <i>mef</i> (A) or <i>erm</i> (B)] <i>Streptococcus pneumoniae</i> Simulating Clinically Achievable Serum and Epithelial Lining Fluid Free-Drug Concentrations
Bibliographic record
Abstract
The association between macrolide resistance mechanisms and clinical outcomes remains understudied. The present study, using an in vitro pharmacodynamic model, assessed clarithromycin (CLR) activity against mef(A)-positive and erm(B)-negative Streptococcus pneumoniae isolates by simulating free-drug concentrations in serum and both total (protein-bound and free) and free drug in epithelial lining fluid (ELF). Five mef(A)-positive and erm(B)-negative strains, one mef(A)-negative and erm(B)-positive strain, and a control [mef(A)-negative and erm(B)-negative] strain of S. pneumoniae were tested. CLR was modeled using a one-compartment model, simulating a dosage of 500 mg, per os, twice a day (in serum, free-drug C(p) maximum of 2 micro g/ml, t(1/2) of 6 h; in ELF, C(ELF(total)) maximum of 35 micro g/ml, t(1/2) of 6 h; C(ELF(free)) maximum of 14 micro g/ml, t(1/2) of 6 h). Starting inocula were 10(6) CFU/ml in Mueller-Hinton broth with 2% lysed horse blood. With sampling at 0, 4, 8, 12, 20, and 24 h, the extent of bacterial killing was assessed. Achieving CLR T/MIC values of > or =90% (AUC(0-24)/MIC ratio, > or =61) resulted in bacterial eradication, while T>MIC values of 40 to 56% (AUC(0-24)/MIC ratios of > or =30.5 to 38) resulted in a 1.2 to 2.0 log(10) CFU/ml decrease at 24 h compared to that for the initial inoculum. CLR T/MIC values of < or =8% (AUC(0-24)/MIC ratio, < or =17.3) resulted in a static effect or bacterial regrowth. The high drug concentrations in ELF that were obtained clinically with CLR may explain the lack of clinical failures with mef(A)-producing S. pneumoniae strains, with MICs up to 8 micro g/ml. However, mef(A) isolates for which MICs are > or =16 micro g/ml along with erm(B) may result in bacteriological failures.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".