Atherosclerotic cardiovascular disease risk profile of patients with chronic hepatitis B treated with tenofovir alafenamide or tenofovir disoproxil fumarate for 96 weeks
Bibliographic record
Abstract
BACKGROUND: Patients with chronic hepatitis B (CHB) who switch from tenofovir disoproxil fumarate (TDF) to tenofovir alafenamide (TAF) show changes in lipid profiles. AIM: To evaluate how these changes affect cardiovascular risk. METHODS: This pooled analysis, based on two large prospective studies, evaluated fasting lipid profiles of patients with CHB who were treated with TAF 25 mg/day or TDF 300 mg/day for 96 weeks. Patients who fulfilled the American College of Cardiology criteria (age 40-79 years, high-density lipoprotein [HDL] 20-100 mg/dL, total cholesterol [TC] 130-320 mg/dL and systolic blood pressure 90-200 mmHg) required to assess 10-year atherosclerotic cardiovascular disease (ASCVD) risk with baseline lipid data and at least one post-baseline measurement were included in the ASCVD-risk population. The 10-year ASCVD risk was calculated for patients in this population, and changes from baseline to Week 96 were assessed using intermediate- (≥7.5%) and high-risk (≥20%) cut-offs. RESULTS: Among 1632 patients, 620 (38%) met the criteria for the ASCVD-risk population. At Week 96, fasting levels of all lipids, except TC:HDL ratio, were lower with TDF than TAF. No significant increase was observed in overall ASCVD risk or in any ASCVD-risk categories during the 96-week treatment period compared with baseline. A similar proportion of patients in the TAF and TDF treatment groups (1.3% and 2.3%, respectively; p = 0.34) reported cardiovascular events. CONCLUSION: Despite on-treatment differences in lipid profiles with TAF and TDF, predicted cardiovascular risk and clinical events were similar for both groups after 96 weeks.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".