Antibiotic susceptibility and molecular analysis of invasive<i>Haemophilus influenzae</i>in Canada, 2007 to 2014
Bibliographic record
Abstract
Background: Previously we studied the antibiotic susceptibility of invasive Haemophilus influenzae collected in Canada from 1990 to 2006 and characterized isolates by serotype, MLST and ftsI gene sequencing for significant PBP3 mutations. Objectives: To provide an update based on isolates collected from 2007 to 2014. Methods: A total of 882 case isolates were characterized by serotype using slide agglutination and PCR. MLST was carried out to determine ST. Isolates were tested for β-lactamase production, presence of significant PBP3 mutations and antibiotic susceptibility by disc diffusion against 14 antibiotics. MIC values of three antibiotics were determined for 316 isolates using microbroth dilution. Results: Non-typeable H. influenzae accounted for 54.6% of the isolates and 45.4% were serotypeable, predominantly type a (23.1%), type b (8.3%) and type f (10.8%). The overall rate of ampicillin resistance due to β-lactamase production was 16.4% and increased from 13.5% in 2007-10 to 19% in 2011-14. Significant PBP3 mutations were identified in 129 isolates (14.6%) with 23 (2.6%) also producing β-lactamase. MLST identified related STs (ST-136, ST-14 and ST-367) associated exclusively with genetically β-lactamase-negative, ampicillin-resistant isolates and confirmed previously reported associations between significant PBP3 mutations and ST. Conclusions: A significant increase in β-lactamase-producing isolates was observed from 2007 to 2014; the rate of significant PBP3 mutations has increased since previously reported and 52.5% of non-typeable H. influenzae now show resistance markers. Resistance to trimethoprim/sulfamethoxazole was common and no resistance to fluoroquinolones or third-generation cephalosporins was found.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".