<scp>HIV</scp> virological rebounds but not blips predict liver fibrosis progression in antiretroviral‐treated <scp>HIV</scp>/hepatitis <scp>C</scp> virus‐coinfected patients
Bibliographic record
Abstract
OBJECTIVES: Antiretroviral interruption is associated with liver fibrosis progression in HIV/hepatitis C virus (HCV) coinfection. It is not known what level of HIV viraemia affects fibrosis progression. METHODS: We evaluated 288 HIV/HCV-coinfected cohort participants with undetectable HIV RNA (<50 HIV-1 RNA copies/mL) on two consecutive visits while on combination antiretroviral therapy (cART) without fibrosis [aspartate aminotransferase to platelet ratio index (APRI) <1.5], end-stage liver disease or HCV therapy. An HIV blip was defined as a viral load of ≥ 50 and <1000 copies/mL, preceded and followed by undetectable values. HIV rebound was defined as: (i) HIV RNA ≥ 50 copies/mL on two consecutive visits, or (ii) a single HIV RNA measurement ≥ 1000 copies/mL. Multivariate discrete-time proportional hazards models were used to assess the effect of different viraemia levels on liver fibrosis progression (APRI ≥ 1.5). RESULTS: The mean age of the patients was 45 years, 74% were male, 81% reported a history of injecting drug use, 51% currently used alcohol and the median baseline CD4 count was 440 [interquartile range (IQR) 298, 609] cells/μL. Fifty-seven (20%) participants [12.4/100 person-years (PY); 95% confidence interval (CI) 9.2-15.7/100 PY] progressed to an APRI ≥ 1.5 over a mean 1.1 (IQR 0.6, 2.0) years of follow-up time at risk. Virological rebound [hazard ratio (HR) 2.3; 95% CI 1.1, 4.7] but not blips (HR 0.5; 95% CI 0.2, 1.1) predicted progression to APRI ≥ 1.5. Each additional 1 log10 copies/mL HIV RNA exposure (cumulative) was associated with a 20% increase in the risk of fibrosis progression (HR 1.2; 95% CI 1.0-1.3). CONCLUSIONS: Liver fibrosis progression was associated with HIV rebound, but not blips, and with increasing cumulative exposure to HIV RNA, highlighting the importance of achieving and maintaining HIV suppression in the setting of HIV/HCV coinfection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".