Host- rather than virus-related factors reduce health-related quality of life in hepatitis C virus infection
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) infection is associated with decreased health-related quality of life (HRQOL). Although HCV has been suggested to directly impair neuropsychiatric functions, other factors may also play a role. PATIENTS AND METHODS: In this cross-sectional study, we assessed the impact of various host-, disease- and virus-related factors on HRQOL in a large, unselected population of anti-HCV-positive subjects. All individuals (n = 1736) enrolled in the Swiss Hepatitis C Cohort Study (SCCS) were asked to complete the Short Form 36 (SF-36) and the Hospital Anxiety Depression Scale (HADS). RESULTS: 833 patients (48%) returned the questionnaires. Survey participants had significantly worse scores in both assessment instruments when compared to a general population. By multivariable analysis, reduced HRQOL (mental and physical summary scores of SF-36) was independently associated with income. In addition, a low physical summary score was associated with age and diabetes, whereas a low mental summary score was associated with intravenous drug use. HADS anxiety and depression scores were independently associated with income and intravenous drug use. In addition, HADS depression score was associated with diabetes. None of the SF-36 or HADS scores correlated with either the presence or the level of serum HCV RNA. In particular, SF-36 and HADS scores were comparable in 555 HCV RNA-positive and 262 HCV RNA-negative individuals. CONCLUSIONS: Anti-HCV-positive subjects have decreased HRQOL compared to controls. The magnitude of this decrease was clinically important for the SF-36 vitality score. Host and environmental, rather than viral factors, seem to impact on HRQOL level.
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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 | 0.000 | 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) | 0.002 | 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".