Evaluation of the Hepatitis C Testing Strategy for Human Immunodeficiency Virus–Positive Men Who Have Sex With Men at the Sexually Transmitted Infections Outpatient Clinic of Amsterdam, the Netherlands
Bibliographic record
Abstract
INTRODUCTION: As the incidence of hepatitis C virus (HCV) infections remains high among human immunodeficiency virus (HIV)-positive men who have sex with men (MSM) an HCV testing strategy was introduced at the sexually transmitted infections (STI) clinic in Amsterdam in 2017. We aimed to evaluate this HCV testing strategy. METHODS: The HIV-positive MSM and transgender women (TGW) were eligible for HCV testing (anti-HCV and HCV ribonucleic acid) at the STI clinic if they did not visit their HIV clinician in the 3 months before the consultation and had not been tested for HCV at the STI clinic in the previous 6 months. All eligible individuals were administered the 6 questions on risk behavior of the HCV-MSM observational study of acute infection with hepatitis C (MOSAIC) risk score; a risk score of 2 or greater made a person eligible for testing. RESULTS: From February 2017 through June 2018, 1015 HIV-positive MSM and TGW were eligible for HCV testing in 1295 consultations. Eleven active HCV infections (HCV ribonucleic acid positive) were newly diagnosed (positivity rate, 0.9%; 95% confidence interval [CI], 0.4-1.5%). Sensitivity and specificity of the HCV-MOSAIC score for newly diagnosed active HCV infections were 80.0% (95% CI, 49.0-94.3%) and 53.7% (95% CI, 50.8-56.5%), respectively. If an HCV-MOSAIC score of 2 or greater were used to determine whom to test, 46.6% of individuals currently tested for HCV would be eligible for testing. CONCLUSIONS: Using the new HCV testing strategy, HCV testing was done in 1295 consultations with HIV-positive MSM and TGW in 17 months. We newly diagnosed 11 active HCV infections. The HCV-MOSAIC risk score could reduce the number of tests needed, but some active HCV infections will be missed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".