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Oral health related quality of life of edentulous patients after denture relining with a silicone‐based soft liner

2011· article· en· W1862042266 on OpenAlex
Marina Xavier Pisani, Antônio de Luna Malheiros‐Segundo, Karina Lencioni Balbino, Raphael Freitas de Souza, Helena de Freitas Oliveira Paranhos, Cláudia Helena Silva‐Lovato

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGerodontology · 2011
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineDentistryDenturesQuality of life (healthcare)SiliconeOral healthSoft tissueOrthodonticsSurgeryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge of benefits caused by a treatment on quality of life is very relevant. Despite the wide use and acceptance of soft denture liners, it is necessary to evaluate the patient's response about the use of these materials with regard to improvement in oral health related quality of life (OHRQoL). OBJECTIVES: The aim of this study was to evaluate the influence of denture relining in the OHRQoL of edentulous patients. MATERIALS AND METHODS: Thirty-two complete denture wearers had their lower dentures relined with a silicone-based material (Mucopren soft, Kettenbach, Germany) according to chairside procedures. OHRQoL was assessed before and after 3 months of relining by means of OHIP-EDENT, and the median scores were compared by Wilcoxon test (p ≤ 0.05). RESULTS: After 3 months of relining, participants reported significant improvement of their OHRQoL (p ≤ 0.01). CONCLUSION: Denture relining with a soft liner may have a positive impact on the perceived oral health of edentulous patients.

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.

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 score0.004
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.062
GPT teacher head0.309
Teacher spread0.248 · 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