Salmonella enterica serovars associated with bacteremia in Canada, 2006–2019
Bibliographic record
Abstract
Background: Members of the bacterial genus Salmonella cause salmonellosis, a disease with a spectrum of clinical presentations from a self-limiting gastroenteritis to more severe bacteremia, organ failure and sepsis. The genus consists of over 2,600 serological variants (serovars). Important differences in the pathogenesis of Salmonella serovars have been noted. Objective: The purpose of this study was to determine which Salmonella serovars were more likely to be associated with bacteremia in Canada. Methods: Information on the total number of Salmonella infections and blood isolations reported to the National Enteric Surveillance Program (NESP) from 2006 to 2019 was extracted for each serovar. The risk (proportion) and likelihood (odds) of bacteremia were calculated for all serovars. Results: Of the 96,082 Salmonella cases reported to the NESP during the 14-year study period, 4.4% (95% CI: 4.3%–4.6%) were bacteremic. Twenty nontyphoidal Salmonella (NTS) serovars were associated with lower rates of bacteremia compared to all NTS serovars, and 19 NTS serovars were identified as having higher rates. Heidelberg, Oranienburg, Schwarzengrund, Virchow, Panama and Poona among the top 25 most commonly reported serovars in Canada during the study period. Conclusion: The identification of serovars associated with Salmonella bacteremia in Canada is a first step towards understanding differences in pathogenesis and disease presentation.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".