MétaCan
Menu
Back to cohort
Record W4225113897 · doi:10.1155/2022/4505063

Effect of Low‐Intensity Pulsed Ultrasound (LIPUS) on Alveolar Bone during Maxillary Expansion Using Clear Aligners

2022· article· en· W4225113897 on OpenAlexaff
Maha A. Bahammam, Tarek El‐Bialy

Bibliographic record

VenueBioMed Research International · 2022
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLow-intensity pulsed ultrasoundDental alveolusIntensity (physics)DentistryMedicineOrthodonticsUltrasoundMaterials scienceTherapeutic ultrasoundRadiologyOpticsPhysics

Abstract

fetched live from OpenAlex

The present study evaluated the possible effect of low‐intensity pulsed ultrasound (LIPUS) on buccal bone plate thickness and height after maxillary arch expansion using clear aligners. The cone beam computed tomography (CBCT) of before and immediately after maxillary arch expansion (3 mm per side) of 28 adult patients (18 in LIPUS group and 10 in control) (average age 36.2 ± 13.2 years old) was analyzed. The wearing protocol of clear aligners in the LIPUS group was to change the aligners every 4 to 5 days, while the wearing protocol in the control group (without LIPUS) was to change the aligners every 7 to 10 days. Bone thickness at 3 mm and 6 mm from the buccal alveolar bone crests, along with the measurements of buccal alveolar bone heights, was measured in standardized sagittal sections. Data were analyzed through paired sample t ‐test and the Wilcoxon test. The results were given as mean ± standard deviation and 95% confidence intervals. p value < 0.05 was considered statistically significant. The results showed significant increase in bone height in both groups. However, comparison of both LIPUS and control groups showed no statistically significant difference in bone thickness or bone height. The results of this study showed that the use of LIPUS together with accelerated aligner tray change protocol did not affect alveolar bone integrity when compared to the control group.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.355
Teacher spread0.328 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBioMed Research InternationalSame topicDental Radiography and ImagingFrench-language works237,207