The incidence of complications associated with lip and/or tongue piercings: a systematic review
Bibliographic record
Abstract
OBJECTIVE: This review determines the incidence of complications associated with lip and/or tongue piercings based on a systematic evaluation of the available literature. MATERIAL AND METHODS: MEDLINE-PubMed, Cochrane-CENTRAL and EMBASE databases were comprehensively searched through June 2014 to identify appropriate studies. The incidence of complications, as established by a dental professional associated with oral and peri-oral piercings, was evaluated in populations with lip and/or tongue piercings. The quality of the case-control studies was assessed using the Newcastle-Ottawa Scale. For case series studies, the risk of bias was assessed using the National Institute for Health and Clinical Excellence scale. RESULTS: An independent screening of 1580 unique titles and abstracts revealed 15 publications that met the eligibility criteria. The incidence of gingival recessions appeared to be 50% in subjects with lip piercings and 44% in subjects with a tongue piercing. Tooth injuries were observed in 26% individuals with lip piercings and in up to 37% of individuals with tongue piercings. Subjects with a lip piercing were 4.14 times (P = 0.005) more likely to develop gingival recession than those without a lip piercing. Subjects with a tongue piercing were more likely than non-pierced subjects to experience gingival recession (relative risk (RR) 2.77; P = 0.00001) and tooth injuries (RR 2.44; P = 0.003). CONCLUSION: Both lip and tongue piercings are highly associated with the risk of gingival recession, and tongue piercings are also associated with tooth injuries.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".