Marijuana Use Is Not Associated With Progression to Advanced Liver Fibrosis in HIV/Hepatitis C Virus–coinfected Women
Bibliographic record
Abstract
BACKGROUND: Marijuana (hereafter "tetrahydrocannabinol [THC]") use has been associated with liver fibrosis progression in retrospective analyses of patients with chronic hepatitis C (HCV). We studied long-term effects of THC on fibrosis progression in women coinfected with human immunodeficiency virus (HIV)/HCV enrolled in the Women's Interagency HIV Study (WIHS). METHODS: Liver fibrosis was categorized according to FIB-4 scores as none, moderate, or significant. THC and alcohol use were quantified as average exposure per week. Associations between THC use and progression to significant fibrosis were assessed using Cox proportional hazards regression. RESULTS: Among 575 HIV/HCV-coinfected women followed for a median of 11 (interquartile range, 6-17) years, 324 (56%) reported no THC use, 141 (25%) less than weekly use, 70 (12%) weekly use, and 40 (7%) daily use at WIHS entry. In univariable analysis, entry FIB-4 score (hazard ratio [HR], 2.26 [95% confidence interval {CI}, 1.88-2.73], P < .001), log HCV RNA (HR, 1.19 [95% CI, 1.02-1.38], P = .02), tobacco use (HR, 1.37 [95% CI, 1.02-1.85], P = .04), CD4(+) count (risk per 100-cell increase: HR, 0.90 [95% CI, .86-.95], P < .001), and log HIV RNA (HR, 1.18 [95% CI, 1.05-1.32], P = .005) were associated with progression to significant fibrosis, as was cumulative alcohol use in follow-up (HR, 1.03 [95% CI, 1.02-1.04], P < .001). In multivariable analysis, entry FIB-4, entry CD4(+) count, and cumulative alcohol use remained significant. Cumulative THC use was not associated with fibrosis progression (HR, 1.01 [95% CI, .92-1.10], P = .83). CONCLUSIONS: In this large cohort of HIV/HCV-coinfected women, THC was not associated with progression to significant liver fibrosis. Alcohol use was independently associated with liver fibrosis, and may better predict fibrosis progression in HIV/HCV-coinfected women.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".