Twenty-year follow-up of an outbreak of hepatitis C in a small rural town of Argentina: The O'Brien Project
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVES: In 1999, a population-based survey showed a 5.6 % (102/1832) prevalence of HCV infection in O'Brien, a small rural town of Argentina. The aim of this study was to assess the impact of screening, clinical evaluation and antiviral therapy on elimination of HCV after 20 years of follow-up. PATIENTS AND METHODS: HCV+ subjects (n=102) underwent clinical, biochemical and histological evaluation to assess the presence and severity of liver disease. Antiviral therapy included pegylated interferon + ribavirin in 2005 and direct antiviral agents from 2017. RESULTS: All viremic subjects (n=84) had genotype 1b with 90%-97.5% sequence homology scores, suggesting the existence of a common source of infection (use of unsafe injections administered by the same health professional). Liver biopsy (n=55) showed chronic hepatitis in all patients. The prevalence of cirrhosis was 28% overall (29/102) and 34.5% among viremic patients. Sustained virological response (SVR) was obtained in 20/34 (59%) patients treated with interferon. From 2005 to 2017, when oral antivirals became available 37/50 untreated patients died. Median age of this group in 2005 was 67 years. Six interferon non-responders and five naive subjects received direct antiviral agents and all developed SVR. Only 1/31 patient (3.2%) with SVR died and none developed decompensated cirrhosis or HCC. In 2019, a new population-based study showed that the prevalence of HCV in O'Brien decreased 20-fold, from 5.6% to 0.28% (3/1070). CONCLUSIONS: Despite the high mortality rate precluding timely access to direct antiviral agents, the O'Brien Project is a good example of HCV micro-elimination studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".