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Record W4409569962 · doi:10.1186/s12903-025-05874-x

Adjunctive therapies in orthodontics: a scoping systematic review

2025· review· en· W4409569962 on OpenAlexaff
Dana Salha, Kausar Sadia Fakhruddin, Samaranayake Lakshman, Victor Haruo Matsubara, Nabiha Belkacem Remmani, Snigdha Pattanaik, Siew‐Ging Gong

Bibliographic record

VenueBMC Oral Health · 2025
Typereview
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOral and maxillofacial surgeryOrthodonticsMEDLINEDentistry

Abstract

fetched live from OpenAlex

BACKGROUND: Orthodontic tooth movement (OTM) induces physiological and sometimes pathological inflammation in periodontal tissues. This review evaluates the effectiveness of low-level laser therapy (LLLT), vibrational therapy, and probiotics as adjunctive treatments for managing inflammation, pain, and the duration of OTM. METHODS: Medline via OVID, Cochrane, EMBASE, and Web of Science databases were utilized to identify randomized controlled trials (RCTs) published between January 1990 and November 2023. Studies were selected based on their evaluation of LLLT, vibrational therapy, and probiotics as adjuncts in fixed orthodontic treatment. RESULTS: LLLT shows promise in enhancing orthodontic tooth movement by accelerating tooth movement and potentially reducing pain. However, disparate study outcomes indicate a need for standardized application protocols. The efficacy of vibrational therapy as an adjunct in OTM remains inconclusive. Some studies in this regard indicate a significant acceleration in OTM but most did not. Probiotic therapy shows potential to improve oral microbiota balance and inflammation but requires more rigorous studies to determine its efficacy and optimal administration methods. CONCLUSION: Future research should focus on establishing standardized guidelines and protocols to achieve consistent and reliable outcomes across these adjunctive therapies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.500
Teacher spread0.348 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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