Hepatic Fibrosis: A Manifestation of the Evolution of Liver Disease in Patients with Ataxia-Telangiectasia
Bibliographic record
Abstract
Abstract Background: Ataxia-telangiectasia (A-T) is a DNA repair disorder characterized by changes in several organs and systems. Advances in clinical protocols have resulted in increased survival of A-T patients, however disease progression is evident, mainly through metabolic and liver changes. We aimed to identify the frequency of significant hepatic fibrosis in A-T patients and to verify association with metabolic alterations and degree of ataxia. Results: Dyslipidemia was observed in 16/25 (64%), diabetes in 4/22 (18%), insulin resistance in 5/17 (29%), hepatic steatosis in 13/20 (65%) and suggestive of significant hepatic fibrosis in 5/25 (20%). Patients in the group with significant hepatic fibrosis were older (p<0.001), had lower platelet values (p=0.027), albumin (p=0.019), HDL-c (p=0.013) and Matsuda index (p=0.044); and high values of LDL-c (p=0.049), AST (p=0.001), alanine aminotransferase (p=0.002), gamma-glutamyl transferase (p=0.001), ferritin (p=0.001), 120-minutes glycemia by OGTT (p=0.049), HOMA-AD (p=0.016) and degree of ataxia (p=0.009). Conclusions: A suggestive diagnosis of significant hepatic fibrosis was observed in 20% of A-T patients which was associated with changes in liver enzymes, ferritin, increased HOMA-AD and with severity of ataxia compared to patients without hepatic fibrosis.
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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 | 0.000 |
| 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) | 0.001 | 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".