Analysis of MDR in the predominant <i>Streptococcus pneumoniae</i> serotypes in Canada: the SAVE study, 2011–2020
Bibliographic record
Abstract
OBJECTIVES: To investigate the levels of MDR in the predominant serotypes of invasive Streptococcus pneumoniae isolated in Canada over a 10 year period. METHODS: All isolates were serotyped and had antimicrobial susceptibility testing performed, in accordance with CLSI guidelines (M07-11 Ed., 2018). Complete susceptibility profiles were available for 13 712 isolates. MDR was defined as resistance to three or more classes of antimicrobial agents (penicillin MIC ≥2 mg/L defined as resistant). Serotypes were determined by Quellung reaction. RESULTS: In total, 14 138 invasive isolates of S. pneumoniae were tested in the SAVE study (S. pneumoniae Serotyping and Antimicrobial Susceptibility: Assessment for Vaccine Efficacy in Canada), a collaboration between the Canadian Antimicrobial Resistance Alliance and Public Health Agency of Canada-National Microbiology Laboratory. The rate of MDR S. pneumoniae in SAVE was 6.6% (902/13 712). Annual rates of MDR S. pneumoniae decreased between 2011 and 2015 (8.5% to 5.7%) and increased between 2016 and 2020 (3.9% to 9.4%). Serotypes 19A and 15A were the most common serotypes demonstrating MDR (25.4% and 23.5% of the MDR isolates, respectively); however, the serotype diversity index increased from 0.7 in 2011 to 0.9 in 2020 with a statistically significant linear increasing trend (P < 0.001). In 2020, MDR isolates were frequently serotypes 4 and 12F in addition to serotypes 15A and 19A. In 2020, 27.3%, 45.5%, 50.5%, 65.7% and 68.7% of invasive MDR S. pneumoniae were serotypes included in the PCV10, PCV13, PCV15, PCV20 and PPSV23 vaccines, respectively. CONCLUSIONS: Although current vaccine coverage of MDR S. pneumoniae in Canada is high, the increasing diversity of serotypes observed among the MDR isolates highlights the ability of S. pneumoniae to rapidly evolve.
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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 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".