Syphilis: Understanding the disease and the role of dental professionals
Bibliographic record
Abstract
, poses significant public health challenges globally. Its varied clinical presentations, especially oral manifestations, position dental professionals uniquely for early detection and intervention. This review synthesizes current epidemiological trends, clinical features, diagnostic approaches, prevention strategies, and management guidelines with an emphasis on the role of dental professionals. A literature review was conducted to assess the clinical presentation of syphilis, prevention and management by dental professionals. Key topics included epidemiology, risk factors, transmission, diagnosis and treatment. A systematic search was conducted across PubMed, Ovid MEDLINE, EMBASE, Scopus, and Google Scholar for studies published in English from 2010 to 2024, supplemented by public health and media reports. A notable increase in syphilis cases was reported globally, including Canada and the United States, with disproportionate impacts on vulnerable populations. Oral lesions, including chancres and mucosal patches, frequently present in early stages, underscoring the importance of dental examination. Rapid point-of-care testing offers opportunities for timely diagnosis in dental settings. Prevention relies on education, routine screening, and structural interventions, while management centres on penicillin-based treatment and coordinated referrals. Dental professionals can play a critical role in mitigating syphilis transmission through early identification, patient education, and referral. Strengthening interdisciplinary collaboration and provider training is essential for improving syphilis outcomes and population health.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".