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Record W2997955937 · doi:10.1016/j.ortho.2019.12.002

Effects of clear aligner therapy for Class II malocclusion on upper airway morphology and daytime sleepiness in adults: A case series

2019· article· en· W2997955937 on OpenAlexaff
Thikriat Al‐Jewair, Kevin Kurtzner, Terry Giangreco, Stephen Warunek, Manuel O. Lagravère

Bibliographic record

VenueInternational Orthodontics · 2019
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
FundersAmerican Association of Orthodontists Foundation
KeywordsMedicineMalocclusionOverjetDentistryOrthodonticsEpworth Sleepiness ScaleAirwayCephalometrySurgeryAnesthesia

Abstract

fetched live from OpenAlex

To evaluate the effects of clear aligner therapy (CAT) on the upper airway dimensions and on daytime sleepiness in adults with dentoskeletal Class II malocclusion. This study was conducted from August 2017 to February 2019. Inclusion criteria were healthy adults ≥ 18 years old, Angle Class II division 1 malocclusion, first-molar relationship of end-to-end or greater, overjet < 10 mm, and presenting for multi-arch comprehensive orthodontic treatment with aligners. Treatment mechanics included mandibular dentoalveolar advancement with Class II elastics without maxillary sequential distalization programmed into aligners. Post-treatment changes in dentoskeletal and upper airway dimensions were assessed using CBCT images. The treatment effect on daytime sleepiness was evaluated using an Epworth Sleepiness Scale (ESS). Eight subjects were included in this pilot study (mean age at treatment initiation = 44.6 years [SD = 15.3]). The mean treatment duration was 12.2 months (SD = 3.4). No statistically significant treatment changes were observed in upper airway dimensions or dentoskeletal cephalometric analyses. Subjects with excessive daytime sleepiness at pre-treatment reported an improvement post-treatment, but no significant difference in the mean ESS score was found. Treatment of Class II division 1 malocclusion in adults by mandibular dentoalveolar advancement using CAT has no statistically significant effects on the airway and dentoskeletal measurements, or daytime sleepiness. Évaluer les effets de la thérapeutique par gouttière chez les patients adultes présentant des malocclusions dento-squelettique de Classe II sur la dimension des voies aériennes supérieures et la somnolence diurne. Cette série de cas a été menée d’août 2017 à février 2019. Les critères d’inclusion étaient les suivants : adultes ≥ 18 ans, malocclusion de Classe II division 1 d’Angle, classe II molaire bout à bout ou plus, surplomb horizontal < 10 mm, avec une motivation pour un traitement complet par gouttières des deux arcades. La stratégie programmée dans la technique des gouttières prévoyait une mécanique d’avancée dentoalvéolaire mandibulaire par élastiques de Classe II sans distalisation séquentielle du maxillaire. Les changements dento-squelettiques et de dimension des voies aériennes supérieures ont été mesurés sur des images CBCT. L’effet thérapeutique sur la somnolence diurne a été enregistré avec l’échelle d’évaluation de la somnolence d’Epworth (ESS). Huit sujets ont été inclus dans cette étude pilote (la moyenne d’âge au début du traitement était de 44,6 ans [ET = 15,3]). La durée moyenne de traitement était de 12,2 mois (ET = 3,4). Aucuns changements statistiquement significatifs liés au traitement ont été observés dans les dimensions des voies aériennes supérieures ou dans les paramètres céphalométriques dento-squelettiques. Les patients avec une somnolence diurne excessive au début du traitement ont montré une amélioration après traitement mais aucune différence significative dans le score moyen ESS n’a été trouvé. Le traitement de la malocclusion de Classe II division 1 chez les adultes par avancée mandibulaire dentoalvéolaire par gouttière ne présente aucun effet significatif sur les voies aériennes et les mesures dento-squelettiques, pas plus que sur la somnolence diurne.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.272
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations13
Published2019
Admission routes1
Has abstractyes

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