Are Farming and Animal Exposure Risk Factors for the Development of Granulomatosis With Polyangiitis? Environmental Risk Factors Revisited: A Case-control Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the possible association between animal exposure and risk for granulomatosis with polyangiitis (GPA). METHODS: Patients with GPA at the Department of Rheumatology, Uppsala University Hospital, between January 1, 2011, and December 31, 2018, were consecutively included. All patients filled in a questionnaire on possible environmental exposures: occupation, hobbies, and animal contact. As controls we included 128 patients with rheumatoid arthritis (RA) and 248 population controls collected from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, matched for age, sex, and geographical area of residence. The controls filled out a questionnaire on current and past contact with farming and animals, at the time of the RA patient's diagnosis. RESULTS: A total of 62 patients with GPA, 128 patients with RA, and 248 population controls were included in the study. GPA was significantly associated with horse exposure, with a 2- to 3-fold increased risk compared with RA (OR 3.08, 95% CI 1.34-7.08) and population controls (OR 2.61, 95% CI 1.29-5.29). Borderline increased risks were found for any animal contact, but no association was found when analyzing contact with cats/dogs only. A significant association was found between GPA and farming compared to the population controls (OR 7.60, 95% CI 3.21-17.93). CONCLUSION: This study has identified for the first time, to our knowledge, a significant association between exposure to specific animals, namely horses, and the development of GPA. The results also support previous studies reporting an association between farming and GPA, underscoring the possibility of exogenous factors as initiators in the development of GPA.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".