Symptomatic acute reactive arthritis after an outbreak of salmonella.
Bibliographic record
Abstract
OBJECTIVE: In 2005, 592 individuals in Ontario developed acute gastroenteritis, predominantly after consuming bean sprouts contaminated with Salmonella enteritidis. Salmonella is a known trigger of reactive arthritis (ReA). We describe the population affected by the Salmonella outbreak in terms of clinical presentation of self-reported arthritic symptoms and HLA-B27 genotyping. METHODS: Subjects were mailed a questionnaire, which assessed symptoms consistent with ReA. Subsequently, subjects were asked to submit saliva samples, which were analyzed for HLA-B27. Simple descriptive statistics were performed for analysis of survey responses, and the genetic component was analyzed by chi-square or Fisher's exact tests. RESULTS: Most respondents were female (71.3%), with a mean age of 46.0 years. The mean duration of diarrhea symptoms was 16.5 days. 62.5% of respondents reported extraintestinal symptoms that were consistent with ReA. The most commonly reported features were joint pain, swelling or stiffness (46.2%), stiffness > 30 min (35.6%), ocular symptoms (24.0%), and visibly swollen joints (19.2%). Subjects with Salmonella infection had a similar incidence of HLA-B27, regardless of whether they developed symptoms consistent with ReA or not. Notably, HLA-B27 was present more frequently in those who developed Salmonella infection than in healthy controls (OR 3.0). CONCLUSION: The study, one of the largest for a dysenteric outbreak, revealed a high event rate of self-reported symptoms consistent with ReA in those infected with Salmonella. Our results showed that HLA-B27 may have rendered individuals more susceptible to Salmonella infection, but did not contribute to the development of symptoms consistent with ReA after infection. We note that the methods used in this study, including self-report, are not ideal for diagnosis of inflammatory arthritis. However, given the rarity of large outbreaks of Salmonella, the study adds valuable knowledge about the course of ReA.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".