United Kingdom pediatric dentistry specialist views on the administration of articaine in children
Bibliographic record
Abstract
BACKGROUND: Lidocaine is the gold standard local anesthetic (LA) for UK pediatric dental treatment. Recent reports suggest frequent Articaine use in Europe and Canada, with evidence indicating more profound anesthesia. The aim of this study was to examine pediatric dentistry specialist experiences and practices relating to Articaine administration in the UK. METHODS: A literature review was followed by a survey using an anonymous 15-item electronic questionnaire, which was sent to 200 registered British Society of Pediatric Dentistry (BSPD) specialists. Descriptive analyses, Z score, chi-squared test, Fisher's exact test, and Spearman's correlation test were performed. RESULTS: Sixty-one (30.5%) participants responded, and 12 (19.7%) indicated Articaine as their first line anesthetic. Articaine was used daily or weekly by 38 (62.3%) respondents, depending on the clinical context. Articaine was commonly used to avoid inferior alveolar nerve blocks and gain more profound anesthesia in abscessed or hypomineralized teeth. Participants reported significantly more adverse effects with lidocaine (Fisher's exact test, P < 0.0001) than with Articaine. Articaine was most often administered in children aged > 4 years via infiltration techniques. Only 15 (24.6%) respondents reported awareness of guidelines for Articaine use in pediatric patients. CONCLUSIONS: Articaine use in pediatric dentistry is common; however, evidence supporting its practice is limited. Several specialists follow conventions based on anecdotal evidence. Formulating guidance to aid decision-making when treating pediatric patients under LA would be beneficial.
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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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".