The Influence of C‐Hepatitis on C‐Reactive Protein in a Cohort of Brazilian Hemodialysis Patients
Bibliographic record
Abstract
Background: The aim of this study was to investigate the influence of HCV on two markers of systemic inflammation, serum CRP, and interleukin‐6 (IL‐6) in HD patients. Methods: The study included 118 HD patients (47% males, age 47 ± 13 years, 9% diabetics) who were treated by on standard HD for at least 6 months. The patients were divided in two groups, depending on the presence (HCV+) or absence (HCV–) of serum antibodies against HCV. Serum albumin (S‐Alb), plasma high sensitivity CRP (hsCRP), IL‐6, and alanine aminotransferase (ALT) were measured, and the values were compared with 22 healthy controls. Results: The median of hsCRP, IL‐6, and the hsCRP/IL‐6 ratio were: 3.5 vs. 2.1 mg/L, p < 0.05; 4.3 vs. 0.9 pg/mL, p < 0.0001; and 0.8 vs. 2.7 pg/mL, p < 0.0001 for patients and controls, respectively. Age, gender, S‐Alb, IL‐6, and hsCRP did not differ between the HCV+ and HCV– patients. However, HCV+ patients had higher ALT (29 ± 21 vs. 21 ± 25 UI/L) and had been a longer time on HD (6.1 ± 3.0 vs. 4.0 ± 2.0 years) (p < 0.0001), respectively. Moreover, HCV+ patients had a significantly lower median hsCRP/IL‐6 ratio (0.7 vs. 0.9; p < 0.05) as compared to the HCV group. Conclusion: The finding that the hsCRP/IL‐6 ratio was lower in HCV+ patients than in HCV– patients suggests that hsCRP may be a less useful marker of inflammation in HCV+ patients and that a different cut‐off value for hsCRP may be required to define inflammation in HD patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".