Prevalence, Correlates, and Viral Dynamics of Hepatitis Delta among Injection Drug Users
Bibliographic record
Abstract
BACKGROUND: Most hepatitis delta virus (HDV) prevalence estimates from the United States are >10 years old, and HDV has shown significant temporal variation in other populations. HDV-hepatitis B virus (HBV) dual infection progresses rapidly, has more complications, and has a different treatment regimen than HBV infection alone. Accurate estimates of prevalence and risk factors are important to help clinicians decide who to screen. METHODS: Injection drug users in Baltimore, Maryland, who were positive for HBV serologic markers were tested for hepatitis delta antibody (HDAb) at 2 time periods: 1988-1989 (194 participants) and 2005-2006 (258 participants). Those who were HDAb positive in 2005-2006, plus a random sample of HDAb negative, HBV-positive participants were tested for HDV RNA, HBV DNA, and HCV RNA. Characteristics associated with HDV exposure and viremia were identified. RESULTS: HDV prevalence declined from 15% in 1988-1989 to 11% in 2005-2006. Among those with chronic HBV infection, prevalence increased from 29% (14 of 48 participants) to 50% (19 of 38 participants) (P=.05). Visiting a "shooting gallery" (a location where people gather to inject illegal drugs) was a strong correlate of HDAb positivity (relative risk, 3.08; P=.01). Eight (32%) of those who were HDAb positive had HDV viremia. Viremic participants had elevated liver enzyme levels and more emergency room visits. CONCLUSIONS: The temporal increase in HDV prevalence among those with chronic HBV infection is troubling; understanding this change should be a priority to prevent the burden from increasing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".