Tobacco Smoking Is Not Associated With Accelerated Liver Disease in Human Immunodeficiency Virus-Hepatitis C Coinfection: A Longitudinal Cohort Analysis
Bibliographic record
Abstract
Background. Tobacco smoking has been shown to be an independent risk factor for liver fibrosis in hepatitis C virus (HCV) infection in some cross-sectional studies. No longitudinal study has confirmed this relationship, and the effect of tobacco exposure on liver fibrosis in human immunodeficiency virus (HIV)-HCV coinfected individuals is unknown. Methods. The study population consisted of participants from the Canadian Co-infection Cohort study (CTN 222), a multicenter longitudinal study of HIV-HCV coinfected individuals from 2003 to 2014. Data were analyzed for all participants who did not have significant fibrosis or end-stage liver disease (ESLD) at baseline. The association between time-updated tobacco exposure (ever vs nonsmokers and pack-years) and progression to significant liver fibrosis (defined as an aspartate-to-platelet ratio index [APRI] ≥1.5) or ESLD was assessed by pooled logistic regression. Results. Of 1072 participants included in the study, 978 (91%) had ever smoked, 817 (76%) were current smokers, and 161 (15%) were previous smokers. Tobacco exposure was not associated with accelerated progression to significant liver fibrosis nor with ESLD when comparing ever vs never smokers (odds ratio [OR] = 1.06, 95% confidence interval [CI], 0.43-1.69 and OR = 1.20, 95% CI, 0.21-2.18, respectively) or increases in pack-years smoked (OR = 1.05, 95% CI, 0.97-1.14 and OR = 0.94, 95% CI, 0.83-1.05, respectively). Both time-updated alcohol use in the previous 6 months and presence of detectable HCV ribonucleic acid were associated with APRI score ≥1.5. Conclusions. Tobacco exposure does not appear to be associated with accelerated progression of liver disease in this prospective study of HIV-HCV coinfected individuals.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".