Evidence map›Paper›PMID 41639852›Full record

ArticleBMC oral health2026

Effect of attachment wear on maxillary canine rotation in clear aligner therapy: a three-dimensional finite element analysis.

Qiuying Li, Bowen Xu, Dongyu Fang, Kai Yang

Abstract read
In one paragraph

Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qiuying LiDepartment of Orthodontics, School of Stomatology, Capital Medical University, No.9, Fanjiacun Road, Beijing, 100071, China.
Bowen XuDepartment of Orthodontics, School of Stomatology, Capital Medical University, No.9, Fanjiacun Road, Beijing, 100071, China.
Dongyu FangDepartment of Orthodontics, School of Stomatology, Capital Medical University, No.9, Fanjiacun Road, Beijing, 100071, China.
Kai YangDepartment of Orthodontics, School of Stomatology, Capital Medical University, No.9, Fanjiacun Road, Beijing, 100071, China. dr_yangkai@mail.ccmu.edu.cn.

Funding

the Capital's Funds for Health Improvements and Research CFH2022-2-2144the Young Scientist Program of Beijing Stomatological Hospital, Capital Medical University YSP202405
6 · The paper itself

Abstract

backgroundThis study aimed to explore the effect of attachment wear on maxillary canine rotation in clear aligner therapy through three-dimensional finite element analysis.

methodsFinite element models, comprising the maxillary bone, periodontal ligament, upper dentition, attachments (initial and worn), and clear aligners, were created to simulate maxillary canine rotation. Two attachment types (vertical rectangular and rotation-optimized) with five wear levels (M0, M2, M4, M6, and M8) were considered for canine rotation analysis. Tooth displacement and equivalent stress in the roots and periodontal ligaments were analyzed.

resultsWith increased attachment wear, both groups showed reduced canine rotation angles and lower stress levels in roots and periodontal ligaments. The most significant reduction in the canine rotation angles and stress values for the rectangular group occurred between M2 and M4, with the efficiency of canine rotation falling below 50% from M4 onward. In contrast, the optimized group experienced the most substantial decline between M6 and M8, with the efficiency of canine rotation falling below 50% at M8.

conclusionsAttachment wear decreased maxillary canine rotation efficiency. It is preferable to use optimized rotation attachments when correcting maxillary canine rotation. After six months of optimized attachment use, if maxillary canines still require rotation, orthodontists should closely monitor attachment wear to ensure treatment effectiveness. Immediate restoration or re-bonding of the attachments is required if it is determined to be essential.

Indexed as

CuspidFinite Element AnalysisOrthodontic Appliances, RemovableTooth Movement TechniquesDental Stress AnalysisHumansImaging, Three-DimensionalMaxillaOrthodontic Appliance DesignPeriodontal LigamentRotationStress, MechanicalTooth RootAttachmentCanine RotationClear AlignerFinite Element AnalysisWear

Identifiers

PMID41639852
PMCPMC12964941

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.