Assessment of the Susceptibility of<i>Streptococcus pneumoniae</i>to Cefaclor and Loracarbef in 13 Countries
Bibliographic record
Abstract
Between July 1998 and July 1999, 2,644 clinical isolates of Streptococcus pneumoniae were collected from 27 study centers in 13 countries and their susceptibilities to penicillin, cefaclor and loracarbef were determined by E-test" (AB BIODISK, Solna, Sweden). Overall, 96.3% of isolates were penicillin-susceptible (79.8%) or -intermediate (16.6%) (MIC, < or = 1 microg/ml). Rates of penicillin-resistant S. pneumoniae isolation varied widely and were highest in the study centers tested in New Zealand (10.9%), Canada (10.0%), Mexico (9.1%) and the United States (5.1%). Low rates of penicillin-resistance were found in the study centers tested in Russia (0%), Turkey (0%), Brazil (0.5%), Germany (0.6%), Philippines (1.6%), Italy (2.1%), United Kingdom (2.3%), Australia (3.0%) and Poland (3.1%). Using recently published NCCLS interpretative breakpoints (M100-S10, 2000), 87.2% (median) of all isolates tested were cefaclor-susceptible and 87.8% (median) of all isolates tested were loracarbef-susceptible. Of the penicillin-susceptible S. pneumoniae isolates, 99.5% were susceptible to both cefaclor and loracarbef. Susceptibility to cefaclor and loracarbef was also retained by 30.8% and 32.9% of penicillin-intermediate isolates, respectively. These findings are in contrast to recent publications reporting lower cefaclor and loracarbef activities using non-validated interpretative criteria. In conclusion, rates of penicillin resistance among recent clinical isolates of pneumococci remain low in many centers worldwide. Cefaclor and loracarbef demonstrated excellent in vitro activity against recent clinical isolates of penicillin-susceptible and many isolates of penicillin-intermediate S. pneumoniae.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".