Lamivudine, Entecavir, or Tenofovir Treatment of Hepatitis B Infection: Effects on Calcium, Phosphate, FGF23 and Indicators of Bone Metabolism
Bibliographic record
Abstract
BACKGROUND: The prevalence of two functional polymorphisms (rs1127354 and rs7270101) of the inosine triphosphatase (ITPA) gene associated with ribavirin-induced hemolytic anemia (RIHA) during antiviral therapy for hepatitis C virus (HCV) infection varies by ethnicity. In Mexico, the distribution of these polymorphisms among Native Amerindians (NA) and admixed population (Mestizos) is unknown. This study aimed to determine the prevalence of the ITPA polymorphisms among healthy NA and Mestizos, as well as in HCV patients from West Mexico. MATERIAL AND METHODS: In a cross-sectional study, 600 unrelated subjects (322 Mestizos, 100 NA, and 178 treatment-naïve, HCV-infected Mestizos patients) were enrolled. A medical history was registered. ITPA genotype was determined by Real-Time PCR. Fst-values and genetic relatedness between study and reference populations were assessed. RESULTS: The frequency of the risk genotypes rs1127354CC and rs7270101AA was higher among NA (98-100%) than in Mestizos (87-92.9%), (p < 0.05). The NA presented the highest prevalence of the rs1127354CC genotype reported worldwide. The Fst-values revealed a genetic relatedness among Mexican NA, South Americans and African populations (p > 0.05). The frequency of the predicted risk for RIHA was higher among NA (98%) than in Mestizos (80.5%) and HCV-infected patients (81.5%) (p < 0 .01). The CC/AA alleles were associated with lower values of total bilirubin, aspartate/alanine aminotransferases, and aspartate-to-platelet-ratio-index score among HCV-patients. CONCLUSION: A high prevalence of the ITPA polymorphisms associated with RIHA was found in Mexican NA. These polymorphisms could be a useful tool for evaluating potential adverse effects and the risk or benefit of antiviral therapy in Mexicans and other admixed populations.
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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 | 0.000 | 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".