A narrative review of infections associated with personal service establishments Part II: Piercing and tattooing
Bibliographic record
Abstract
In part II of our paper on personal service establishment services-related infections, we review bacterial, viral, and fungal infections related to piercing, tattooing, and body modification. Sixty-six studies were identified for piercing and tattooing-related viral and bacterial infections. No studies investigating fungal infections, or body modification service-related infections were identified. Bacterial infections, particularly, mycobacterium infections were commonly reported for piercing and tattooing, while viral risks were less well characterized, with the exception of tattooing related hepatitis B and C infections. Aside from localized infections at the pierced or tattooed site, a systemic infection involving the outer lining of the heart, infective endocarditis (IE), was also identified as an important health concern; those with pre-existing heart conditions are at highest risk of IE from invasive procedures. Both bacterial and viral outbreaks were linked to poor infection control procedures, and in two events, the use of municipal water to dilute tattoo ink was suspected as a source of mycobacteria leading to outbreaks of infection. The majority of studies identified were case reports; these studies provide only a limited understanding of infection pathways and do not allow for a quantitative estimation of risk. Despite important gaps in current knowledge, the available scientific literature can be used to support and inform the development of health-protective policies and practices in personal service establishments.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".