Spectrum of autoimmune liver diseases in western India
Bibliographic record
Abstract
BACKGROUND AND AIM: The prevalence and spectrum of autoimmune liver diseases (AILDs) in India are rarely reported in comparison to the West. METHOD: During a study period of 7 years, all patients with chronic liver diseases (CLDs) were evaluated for the presence of AILDs on the basis of clinical, biochemical, imaging, serological, and histological characteristics. RESULTS: Of a total of 1760 CLD patients (38.1% females), 102 patients (5.7%) had an AILD. A total of 75 (11.2%) female patients had an AILD. Among males, 27 (2.4%) had an AILD. The prevalence of AILDs in women increased from 11.2% to 45.7% and in men from 2.4% to 10.3%, after excluding alcohol, hepatitis B virus, and hepatitis C virus as a cause of CLD. Of the AILDs, autoimmune hepatitis (AIH) was present in 79 patients (77.4%), followed in descending order by primary biliary cirrhosis (PBC) in 10 patients (9.8%), PBC/AIH true overlap syndrome in six patients (5.8%), primary sclerosing cholangitis (PSC) in five patients (4.9%), and PBC/AIH switchover syndrome in two patients (1.9%). None had PSC/AIH or PBC/PSC overlap syndrome. Associated known autoimmune diseases were found in 40 (39.2%) patients. CONCLUSIONS: AILDs are not uncommon in India. They should be suspected in all cases of CLDs, especially in middle-aged women who do not have problems with alcoholism and who are without viral etiology, as well as in all patients with known autoimmune diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".