Analysis of multidrug resistance in the predominant Streptococcus pneumoniae serotypes in Canada: the SAVE study, 2011–15
Bibliographic record
Abstract
Objectives: This study assessed MDR invasive isolates of Streptococcus pneumoniae, in relation to serotype evolution in Canada between 2011 and 2015 as part of the annual SAVE study. Methods: As part of a collaboration between the Canadian Antimicrobial Resistance Alliance and Public Health Agency of Canada-National Microbiology Laboratory, 6207 invasive isolates of S. pneumoniae were evaluated. All isolates were serotyped and had antimicrobial susceptibility testing performed, in accordance with CLSI guidelines (M07-A10, 2015). Complete susceptibility profiles were available for 6001 isolates. MDR was defined as resistance to three or more classes of antimicrobial agents (with penicillin MIC ≥2 mg/L defined as resistant). Results: The overall rate of MDR S. pneumoniae was 6.2% (372/6001) in SAVE, decreasing significantly from 8.5% in 2011 to 5.6% in 2015 (P = 0.0041). MDR was observed in 32 serotypes, with serotypes 15A and 19A predominating (26.6% and 41.7% of the MDR isolates, respectively). The overall proportion of serotypes 19A, 7F and 33A decreased significantly (P < 0.0001) throughout the study. The annual proportion of serotypes 7C, 8, 9N, 10A, 20, 24F, 29, 31, 33F, 35B and 38 increased throughout the study; however, among these increasing serotypes, MDR was only notable (>5%) for 24F and 33F. Conclusions: In 2015, 56.3% of invasive MDR S. pneumoniae were serotypes included in the PCV-13 vaccine. PCV-13 includes the most commonly identified serotype, 19A; however, other increasingly important MDR serotypes, such as 15A, 24F and 33F, are notably not in the currently used vaccines.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".