Botulinum Toxin Type A and Hyaluronic Acid Dermal Fillers in Dentistry: A Systematic Review of Clinical Application and Indications
Bibliographic record
Abstract
Background: Botulinum toxin type A (BoNT-A) and hyaluronic acid (HA) dermal fillers are increasingly utilized in dentistry for therapeutic and aesthetic purposes. However, a comprehensive synthesis of their clinical applications and indications in dentistry is lacking. This systematic review aimed to analyze the clinical application and indications of BoNT-A and HA dermal fillers in dentistry, providing insights into their efficacy, safety profiles, and limitations. Methods: A systematic search was conducted in PubMed/MEDLINE databases to identify relevant studies published between 2018 and 2024. Medical Subject Headings (MeSH) terms and keywords related to BoNT-A, HA dermal fillers, dentistry, clinical applications, and indications were used. Study selection criteria included randomized controlled trials (RCTs) and non-RCTs involving human participants of any age group. Data extraction and synthesis followed established guidelines, focusing on study characteristics, participant demographics, intervention details, outcome measures, and key findings related to BoNT-A and HA dermal fillers' clinical application in dentistry. Results: Systematic searches across electronic databases and grey literature identified 857 records, with an additional 73 from hand searches. After screening titles and abstracts, 542 records were excluded, leaving 374 full-text publications for evaluation. Ultimately, 12 RCTs and 13 non-RCTs were included. The systematic review encompassed diverse geographic locations: Brazil, Italy, Spain, Syria, India, Egypt, Korea, and the Netherlands, involving samples sizes ranging from 14 to 143 participants. The review synthesized findings on HA's efficacy in various areas, including bone repair, gingivitis management, temporomandibular joint disorders, postoperative swelling reduction, periodontal defect treatment, chin and check projection and lips augmentation. BoNT-A exhibited promising efficacy in managing orofacial pain conditions, gummy smile treatment and neuromodulation of the lower third muscles. Safety profiles varied among studies, with some reporting minimal adverse effects while others noted dose-related concerns. Conclusion: BoNT-A and HA dermal fillers offer a wide array of clinical applications in dentistry, ranging from therapeutic interventions to aesthetic enhancements. Despite promising efficacy, careful consideration and monitoring of safety outcomes are essential when integrating these interventions into clinical practice. Further research addressing methodological limitations and safety concerns is warranted to optimize their utilization and improve patient care in dentistry.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| 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) | 0.005 | 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".