A Population‐Based Study of Infectious Syphilis Rediagnosis in British Columbia, 1995–2005
Bibliographic record
Abstract
BACKGROUND: The Canadian province of British Columbia has experienced an ongoing heterosexual infectious syphilis epidemic since July 1997. In this study, we sought to characterize individuals who received a diagnosis of syphilis more than once in a cohort of reported cases from 1995 through 2005 in British Columbia. METHODS: Data for all cases of primary, secondary, and early latent syphilis from 1 January 1995 through 31 December 2005 were extracted from the British Columbia Provincial Sexually Transmitted Disease Surveillance Database. A descriptive analysis was conducted on all variables from the cases, and the incidence density of syphilis rediagnosis was calculated. Bivariate and multivariate analyses were conducted using Cox proportional hazards regression techniques to compare those who received a syphilis diagnosis once with those who received a syphilis diagnosis more than once within the 10-year period. RESULTS: By 2006, up to 10% of new cases of syphilis in the province were attributed to individuals who had received a previous diagnosis of syphilis within the preceding 10 years. In Cox proportional hazards regression analysis, individuals with the following characteristics were associated with an increased risk of becoming reinfected with syphilis: human immunodeficiency virus seropositivity, history of ever having gonorrhea or chlamydia, aboriginal ethnicity, and being a man who had sex with men. CONCLUSIONS: In this study, an increasing proportion of syphilis cases in British Columbia were attributed to a rediagnosis during the previous decade. Individuals with syphilis rediagnosis may represent a core group of transmitters who continue to engage in risky behavior and sustain the epidemic. Policies for prevention need to better consider the role of interventions to decrease rates of repeat diagnoses of sexually transmitted infections.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".