Demographic analysis of antimicrobial resistance among Streptococcus pneumoniae: worldwide results from PROTEKT 1999–2000
Bibliographic record
Abstract
DESIGN: The influence of demographic factors upon antimicrobial resistance among 3362 isolates of Streptococcus pneumoniae from 25 countries was investigated, using univariate comparison and multivariate logistic regression. RESULTS: Eleven countries had significantly higher rates (Odds ratios [OR]: 2.50-64.79) of penicillin and/or erythromycin resistance than the UK. After taking country effects into account, rates of penicillin resistance (OR 1.98) and erythromycin resistance (OR 1.89) were significantly higher among infants than adults. Fewer (OR 0.69) erythromycin-resistant isolates were collected from male than female patients. There was no difference in the incidence of penicillin or erythromycin resistance among inpatients or outpatients. Penicillin resistance was more prevalent among ear swabs than blood cultures (OR 2.07). Erm(B), the predominant macrolide resistance mechanism across all age groups, was particularly prevalent among bronchoalveolar lavage (69.1%) and sinus (68.8%) isolates. Isolates possessing both erm(B) and mef(A) were generally collected from South Korea and were most common among infants and children (10.3%) and ear samples (17.3%). Telithromycin susceptibility was >99.5%, irrespective of demography. CONCLUSIONS: Although demography had a significant impact on antimicrobial resistance of pneumococci, telithromycin remained highly active across all demographic groups.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".