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Record W3117691572 · doi:10.1111/eos.12758

Effectiveness of pit and fissure sealants on primary molars: A 2‐yr split‐mouth randomized clinical trial

2020· article· en· W3117691572 on OpenAlexaff
O. Chabadel, Jacques Véronneau, Sylvie Montal, Paul Tramini, E. Moulis

Bibliographic record

VenueEuropean Journal Of Oral Sciences · 2020
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineMolarDentistrySealantOral hygieneRandomized controlled trialDentitionLogistic regressionOrthodonticsSurgery

Abstract

fetched live from OpenAlex

The primary objective of this study was to evaluate the effects of sealants in preventing pit and fissure caries in primary molars. The secondary objective was to assess the sealant retention during a 2-yr study period. A 2-yr split-mouth randomized clinical trial including 90 3-7-yr-old children was conducted in the paediatric dental department of Montpellier hospital. The dentition of each included patient was divided into an experimental side and a control side, with annual follow-up visits. Caries increments, measured as the number of new occlusal cavitated lesions, were not different between the sealed (mean 0.23) and the control primary molars (mean 0.29). A multiple mixed-effects logistic regression showed that male gender, moderate/high caries risk, and a higher oral hygiene index score, had a statistically significant effect resulting in higher caries increments in the primary molars, than did female gender, low caries risk, and lower oral hygiene index scores. Sealing showed no statistically significant influence on the development of new caries lesions. After 2 yr, the percentages of partially or totally lost sealants were 22.7% and 32.0%, respectively. In this sample of children, the caries increment was not significantly different between the sealed and the unsealed molars. At the end of this 2-yr study, more than half of the sealants were totally or partially lost, which could explain the low sealant effectiveness.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.083
GPT teacher head0.386
Teacher spread0.303 · 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 designRandomized trial
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

Citations23
Published2020
Admission routes1
Has abstractyes

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