Increasing incidence of elderly‐onset autoimmune hepatitis
Bibliographic record
Abstract
AIM: Autoimmune hepatitis (AIH) commonly shows bimodal distribution of onset age: at young adulthood and at 50-60 years-of-age. However, in recent times, the incidence of elderly-onset AIH seems to be increasing. This study aimed to investigate whether the incidence of elderly-onset AIH is increasing, and whether these patients show any clinical features different from those observed in younger patients. METHODS: Data about patients with newly diagnosed AIH visiting the Japanese Red Cross Society Himeji Hospital, Himeji, Hyogo, Japan, were retrospectively collected for the period ranging from January 2010 to May 2016. A total of 71 patients (56 women and 15 men, age 18-88 years) were included in this study. Patients were divided into two cohorts: elderly (≥70 years; n = 28) and adult cohort (15-69 years; n = 43). Demographic and clinical characteristics, biochemical and serological markers, radiological and histological findings, and therapeutic courses were evaluated. RESULTS: The median age of the patients was 65 years, the most frequent range being the 70s (37%), followed by the 60s (25%). The elderly cohort had significantly higher levels of serum immunoglobulin G and antinuclear antibody, lesser hepatitis activity scores, and lesser chance of developing other autoimmune diseases. They tended to have higher C-reactive protein levels and lower serum alanine aminotransferase levels. All patients achieved clinical remission after treatment. CONCLUSIONS: This study clearly showed an increase in the incidence of elderly-onset AIH. These patients had some unique characteristics, showing that the development of elderly-onset AIH is influenced by age-associated immune dysfunction called immunosenescence. Geriatr Gerontol Int 2017; 17: 1722-1728.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".