Serum immunoglobulin A levels and non-alcoholic fatty liver disease
Bibliographic record
Abstract
Background: Intestinal immunity, and immunoglobulin A (IgA) in particular, may play an important role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). The aim of this study was to document the prevalence of elevated serum IgA levels in NAFLD patients and determine whether the severity and course of NAFLD differs in those with elevated (E-IgA) versus normal (N-IgA) levels. Methods: A retrospective review of a clinical database containing demographic, laboratory, and histologic findings of adult NAFLD patients was undertaken. Liver biochemistry, model for end stage-liver disease (MELD) and Fib-4 scores served to document disease severity and progression. Results: Of 941 NAFLD study subjects, 254 (27%) had E-IgA at presentation. E-IgA patients were older, and had lower serum albumin levels and higher MELD scores than N-IgA patients. The percent of E-IgA patients with Fib-4 scores >3.25 (suggestive of cirrhosis) was also higher (25% vs. 5.5%, p<0.001). E-IgA patients had higher METIVIR fibrosis scores (2.2 ± 1.4 vs. 1.0 ± 1.2, p<0.0001) than N-IgA patients. After mean follow-ups of 47 (E-IgA) and 41 (N-IgA) months, serum albumin levels remained lower, INR values were now more prolonged and MELD scores higher in E-IgA patients. Of the non-cirrhotic patients at baseline, a larger percent of E-IgA patients developed cirrhosis by Fib-4 testing at last visit (11% vs. 2.9%, p<0.001). Conclusions: Elevated serum IgA levels are common in NAFLD patients and when present, are associated with more advanced disease. Patients with elevated serum IgA levels are also more likely to progress to cirrhosis than those with normal levels.
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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 | 0.002 |
| 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".