Effect of viral eradication with direct-acting antiviral agents on iron parameters in patients with chronic hepatitis c and hyperferritinemia
Bibliographic record
Abstract
Background: Patients with chronic hepatitis C are at increased risk for hyperferritinemia (HF). Abnormalities of serum iron parameters are frequently observed in patients with chronic hepatitis C (CHC). About a third of patients have increased iron parameters. Recently, studies on the effect of direct-acting antiviral agents (DAAs) in HCV eradication in patients with increased serum iron has been published, demonstrating the restoration of normal iron status. The aim of this study was to evaluate the effect of viral eradication with DDAs in patients with CHC and HF. Methods: Retrospective study conducted from January 2018 to December 2020 including patients treated with DAAs for HCV. Pre-treatment (PreT) and post-treatment (PostT) serum ferritin values were evaluated in all patients. Inclusion criteria: Pret HF (>400 μg/L); CHC patients treated with DAA achieving sustained viral response (SVR). Exclusion criteria: No PreT or PostT HF available; no SVR; lost patients. Results: From 621 patients treated with DAAs for CHC, 77 presented HF (12.40%), and 74 were included in the study. Fifty nine were men (79.73%) with a mean age 58.33, SD 8.68; PreT mean ferritin: 893.20 (SD 1037.09); PostT: 264.17 (SD 161.33); PreT mean transferrin saturation: 40.96 (SD 15.71); PostT: 29.82 (SD 11.17); PreT mean serum iron 152.32 (SD 62.07), PostT: 109.32 (SD 39.49). When we compared PreT and PostT iron parameters, significant statistical differences were present considering ferritin ( p = 0.0000), transferrin saturation ( p = 0.0000), and iron ( p = 0.0002) determinations. Conclusions: SVR after DAAs for CHC induces a statistically significant reduction on iron parameters.
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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) | 0.000 | 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".