The epidemiology of autoimmune liver disease varies with geographic latitude
Bibliographic record
Abstract
Abstract Background & aims The epidemiology of autoimmune liver disease (AILD) is challenging to study because of the diseases’ rarity and because of cohort selection bias. Increased incidence further from the Equator is reported for multiple sclerosis, another autoimmune. We assessed the incidence of primary biliary cholangitis (PBC), primary biliary cholangitis (PSC), and autoimmune hepatitis (AIH) in relation to latitude. Methods Retrospective cohort study using anonymised UK primary care records 2002-01-01 to 2016-05-10. All adults without a baseline diagnosis of autoimmune liver disease were included and followed until first occurrence of an AILD diagnosis, death, or they left the database. Latitude was measured as registered general practice rounded down to whole degrees. Results The cohort included 8 590 421 records with 53.3 10 7 years follow-up from 694 practices. There were 1314 incident cases of PBC, 396 of PSC, and 1034 of AIH. Crude incidences (95% confidence interval) was: PBC 2.47 (2.34-2.60), PSC 0.74 (0.67-0.82), and AIH 1.94 (1.83-2.06)/100 000/year. PBC incidence correlated with female sex, smoking, and deprivation; PSC incidence correlated with male sex and not smoking; AIH incidence correlated with female sex and deprivation. More northerly latitude was strongly associated with incidence of PBC: 2.16 (1.79-2.60) to 4.86 (3.93-6.00) from 50-57°N (p=0.002) and AIH 2.00 (1.65-2.43) to 3.28 (2.53-4.24)(p=0.003), but not PSC 0.82 (0.60-1.11) to 1.02 (0.64-1.61)(p=0.473). Incidence after adjustment for age, sex, smoking, and deprivation status showed similar positive correlations for PBC and AIH with latitude, but not PSC. Incident AIH cases were younger at greater latitude. Conclusions We describe a novel association between increased latitude and the incidence of PBC and AIH that requires both confirmation and explanation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".