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Record W4400241206 · doi:10.14740/jocmr5202

Botulinum Toxin Type A and Hyaluronic Acid Dermal Fillers in Dentistry: A Systematic Review of Clinical Application and Indications

2024· review· en· W4400241206 on OpenAlexvenueno aff
Marta Maci, Carlotta Fanelli, Mauro Lorusso, Donatella Ferrara, M. Caroprese, Michele Laurenziello, Michele Tepedino, Domenico Ciavarella

Bibliographic record

VenueJournal of Clinical Medicine Research · 2024
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHyaluronic acidMedicineDentistryBotulinum toxinCosmetic TechniquesDermatologySurgeryAnatomy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.153
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.346
GPT teacher head0.611
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

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