Arthritis risk after acute bacterial gastroenteritis
Bibliographic record
Abstract
OBJECTIVES: Reactive arthritis (ReA) may occur from bacterial gastroenteritis. We studied the risk of arthritis after an outbreak of Escherichia coli O157:H7 and Campylobacter species within a regional drinking water supply to examine the relationship between the severity of acute diarrhoea and subsequent symptoms of arthritis. METHODS: Participants with no known history of arthritis before the outbreak participated in a long-term follow-up study. Of the 2299 participants, 788 were asymptomatic during the outbreak, 1034 had moderate symptoms of acute gastroenteritis and 477 had severe symptoms that necessitated medical attention. The outcomes of interest were new arthritis by self-report and a new prescription of medication for arthritis during the follow-up period. RESULTS: After a mean follow-up of 4.5 yrs after the outbreak, arthritis was reported in 15.7% of participants who had been asymptomatic during the outbreak, and in 17.6 and 21.6% of those who had moderate and severe symptoms of acute gastroenteritis, respectively (P-value for trend = 0.009). Compared with the asymptomatic participants, those with moderate and severe symptoms of gastroenteritis had an adjusted relative risk of arthritis of 1.19 [95% confidence interval (CI) 0.99-1.43] and 1.33 (95% CI 1.07-1.66), respectively. No association was observed between gastroenteritis and the subsequent risk of prescription medication for arthritis (P = 0.49). CONCLUSIONS: Acute bacterial gastroenteritis necessitating medical attention was associated with a higher risk of arthritic symptoms, but not arthritic medications, up to 4 yrs afterwards. The nature and chronicity of these arthritic symptoms requires further study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".