Syphilis and Co-Infections with HIV-1, HBV, and HCV among People Who Use Crack-Cocaine in Northern Brazil
Bibliographic record
Abstract
The rates of syphilis and viral co-infections among people who use crack-cocaine (PWUCC) were assessed in this study. This cross-sectional study relied on biological and self-reported socio-behavioral data from a convenience sample of 990 PWUCC from twenty-six municipalities in the states of Amapá and Pará, northern Brazil. Blood samples were collected to assess the presence of Treponema pallidum using the Rapid Qualitative Test (RQT) and the Venereal Disease Research Laboratory (VDRL). Reactive samples by RQT were used to assess the presence of HBV, HCV, and HIV-1 using Enzyme Immunoassay (EIA) and Polymerase Chain Reaction (PCR). Logistic regression models were used to determine the association of variables assessed with syphilis. In total, 287 (29.0%) of the PWUCC sample had reactive results for syphilis. HBV (15.7%), HCV (5.9%), and HIV-1 (9.8%) were detected among PWUCC with syphilis. Young age, low monthly income and education level, long duration of crack-cocaine use, condomless sex, multiple sex partners, and exchange of sex for money/drugs were associated with syphilis. The present study provides unique insights on the epidemiological status of syphilis among PWUCC in northern Brazil, with multiple implications for improving urgent interventions for diagnosis, prevention, and treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".