Impact of Direct Acting Antiviral Drugs (DAADs) on Cognitive function among Hepatitis C Virus Infected Patients
Bibliographic record
Abstract
Background: chronic hepatitis C virus (HCV) is a major cause of liver-related morbidity and mortality. Successful antiviral therapy with sustained viral clearance is associated with improved quality of life, and reduced risk of liver complications such as cirrhosis and hepatocellular carcinoma. Aim of the Work: to evaluate the impact of HCV eradication using direct acting antiviral drugs (DAADs) on cognitive function among hepatitis c virus infected patients. Patients and Methods: this study was conducted at Viral Hepatitis Unit of Dar El Shefaa Hospital (one of the centers of national committee for control of viral hepatitis) and MASRI (Faculty of Medicine Ain-Shams Research institute) unit at El-Demerdash Hospital. Data were prospectively collected using MoCA, PHQ-9 and PSQI scales to assess the cognitive function of the treated patients with the newly used DAADs before the start of treatment, during treatment and at 12 weeks after the end of treatment, and the laboratory data were collected from the files of the patients in the previously mentioned centers. Results: results of the current study as regarding the analytical part of the study showed that: Pre treatment: slightly cognitive impairment was found with mild level of depression and sleep disturbance with MoCA test Mean ± SD 23.02 ± 4.96. At the end of treatment: there was no direct effect of the newly used drugs on the cognitive function. After 3 months of treatment (SVR): there was significant improvement of the cognitive function. Conclusion: HCV eradication had beneficial effect on cognitive function. Sofosbuvir based treatment had no effect on cognitive function.
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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 | 0.001 |
| 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 | 0.001 |
| 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".