Hepatic Fibrosis Progression in HIV-Hepatitis C Virus Co-Infection – The Effect of Sex on Risk of Significant Fibrosis Measured by Aspartate-to-Platelet Ratio Index
Bibliographic record
Abstract
BACKGROUND: In Hepatitis C virus (HCV) mono-infection, male sex is associated with faster liver fibrosis progression but the effects of sex have not been well studied in HIV-HCV co-infected patients. We examined the influence of sex on progression to significant liver fibrosis in HIV-HCV co-infected adults receiving antiretroviral therapy (ART) using the aspartate aminotransferase-to-platelet ratio index (APRI) as a surrogate biomarker of liver fibrosis. METHODS: We evaluated 308 HIV infected, HCV RNA positive participants of a Canadian multicentre prospective cohort receiving antiretrovirals and without significant liver fibrosis or end-stage liver disease at baseline. We used multivariate discrete-time proportional hazards models to assess the effect of sex on time to significant fibrosis (APRI≥1.5) adjusting for baseline age, alcohol use, cigarette smoking, HCV duration, and APRI and time-updated CD4 count and HIV RNA. RESULTS: Overall, 55 (18%) participants developed an APRI ≥ 1.5 over 544 person-years of at-risk follow-up time; 18 (21%) women (incidence rate (IR)=14.0/100 PY; 7.5-20.4) and 37 (17%) men (IR=8.9/100 PY; 6.0-11.8). Women had more favourable profiles with respect to traditional risk factors for liver disease progression (younger, shorter duration of HCV infection and less alcohol use). Despite this, female sex was associated with a greater than two-fold increased risk of fibrosis progression (adjusted hazard rate (HR) =2.23; 1.22-4.08). CONCLUSIONS: HIV-HCV co-infected women receiving antiretroviral therapy were at significantly greater risk of progressing to liver fibrosis as measured by APRI compared with men. Enhanced efforts to engage and treat co-infected women for HCV are needed.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".