Environmental risk factors associated with ANCA associated vasculitis: A systematic mapping review
Bibliographic record
Abstract
BACKGROUND: Anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) is a rare multi-system autoimmune disease, characterised by a pauci-immune necrotising small-vessel vasculitis, with a relapsing and remitting course. Like many autoimmune diseases, the exact aetiology of AAV, and the factors that influence relapse are unknown. Evidence suggests a complex interaction of polygenic genetic susceptibility, epigenetic influences and environmental triggers. This systematic mapping review focuses on the environmental risk factors associated with AAV. The aim was to identify gaps in the literature, thus informing further research. METHODS: Articles that examined any environmental risk factor in AAV disease activity (new onset disease or relapse) were included. Studies had to make explicit reference to AAV, which includes the 3 clinico-pathological phenotypes (GPA, MPA and EGPA), rather than isolated ANCA-positivity. All articles identified were English-language, full manuscripts involving adult humans (>16 years). There was no restriction on publication date and all study designs, except single case reports, were included. The systematic search was performed on 9th December 2019, using the following databases: EMBASE, Medline (Ovid), Cochrane Library, CINAHL and Web of Science. RESULTS: The search yielded a total of 2375 articles. 307 duplicates were removed, resulting in the title and abstract of 2068 articles for screening. Of these, 1809 were excluded. Thus, 259 remained for full-text review, of which 181 were excluded. 78 articles were included in this review. The most notable findings support the role of various pollutants - primarily silica and other environmental antigens released during natural disasters and through farming. Assorted geoepidemiological triggers were also identified including seasonality and latitude-dependent factors such as UV radiation. Finally, infection was tightly associated, but the exact microorganism(s) is not clear - Staphylococcus aureus is the most presently convincing. CONCLUSION: The precise aetiology of AAV has yet to be elucidated. It is likely that different triggers, and the degree to which they influence disease activity, vary by subgroup (e.g. ANCA subtype, geographic region). There is a need for more interoperable disease registries to facilitate international collaboration and hence large-scale epidemiological studies, with novel analytical techniques.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".