Phenotypic and molecular characterization of <i>Streptococcus pneumoniae</i> serotype 3 isolates from blood and respiratory samples in Canada: CANWARD 2007–21
Bibliographic record
Abstract
BACKGROUND: Lower respiratory infections and invasive disease caused by Streptococcus pneumoniae serotype 3 remain major clinical challenges around the world, despite widespread availability of updated vaccines. METHODS: As part of CANWARD, antimicrobial susceptibility testing and serotyping were performed on all S. pneumoniae isolates from 2007 to 2021. A subset of 226/264 (85.6%) serotype 3 isolates were selected for WGS to determine sequence type (ST)/clonal cluster (CC) and correspondence of antimicrobial resistance determinants (erm, mefAE, tetM, cat, folA, folP) with resistance phenotype. RESULTS: Of the 3,039 S. pneumoniae isolates obtained from 2007 to 2021, 8.7% (n = 264) were serotype 3, with 64.0% of respiratory origin and 36.0% from blood. Of 226 sequenced serotype 3 isolates, 184 (81.4%) were ST180 (GPSC12). The proportion of ST8561 (single locus variant of ST180) increased from 7.2% to 16.6% during the study period. An increasing proportion of serotype 3 isolates had phenotypic resistance (P = 0.0007) and genetic resistance determinants (P = 0.004), comparing 2017-21 to 2007-11, largely due to a recently expanded ST180 clade with cat, tetM and mef determinants. CONCLUSIONS: S. pneumoniae serotype 3 from GPSC12 continues to dominate throughout Canada, with an increase in the proportion of ST8561. The proportion of serotype 3 isolates that are phenotypically resistant and with genetic resistance determinants is increasing over time, reflecting a global increase in GPSC12 genotypes with known resistance determinants. Phylogenomic characterization of isolates collected over time and from around the world may facilitate improved treatment and enhanced prevention strategies, including new vaccines with activity against S. pneumoniae serotype 3.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".