Distinct Hepatitis B and HIV co‐infected populations in Canada
Bibliographic record
Abstract
Due to shared modes of exposure, HIV-HBV co-infection is common worldwide. Increased knowledge of the demographic and clinical characteristics of the co-infected population will allow us to optimize our approach to management of both infections in clinical practice. The Canadian Hepatitis B Network Cohort was utilized to conduct a cross-sectional evaluation of the demographic, biochemical, fibrotic and treatment characteristics of HIV-HBV patients and a comparator HBV group. From a total of 5996 HBV-infected patients, 335 HIV-HBV patients were identified. HIV-HBV patients were characterized by older median age, higher male and lower Asian proportion, more advanced fibrosis and higher anti-HBV therapy use (91% vs. 30%) than the HBV-positive / HIV seronegative comparator group. A history of reported high-risk exposure activities (drug use, high-risk sexual contact) was more common in HIV-HBV patients. HIV-HBV patients with reported high-risk exposure activities had higher male proportion, more Caucasian ethnicity and higher prevalence of cirrhosis than HIV-HBV patients born in an endemic country. In the main cohort, age ≥60 years, male sex, elevated ALT, the presence of comorbidity and HCV seropositivity were independent predictors of significant fibrosis. HIV seropositivity was not an independent predictor of advanced fibrosis (adj OR 0.75 [95%CI: 0.34-1.67]). In conclusion, Canadian co-infected patients differed considerably from those with mono-infection. Furthermore, HIV-HBV-infected patients who report high-risk behaviours and those born in endemic countries represent two distinct subpopulations, which should be considered when engaging these patients in care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".