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Record W175375830

Oral health-related quality of life in non-syndromic cleft lip and/or palate patients: a systematic review.

2013· review· en· W175375830 on OpenAlexaff
Gregory S. Antonarakis, Rhianna Patel, Bryan Tompson

Bibliographic record

VenuePubMed · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsSickKids Foundation
Fundersnot available
KeywordsMedicineInclusion and exclusion criteriaQuality of life (healthcare)DentistryOral healthPopulationSystematic reviewSample size determinationMEDLINEPediatricsAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

THE OBJECTIVE: To evaluate oral health-related quality of life (OHRQoL) in non-syndromic patients with cleft lip and/or palate (CLP), in comparison to a general non-cleft population. BASIC RESEARCH DESIGN: Systematic review. A literature search was conducted to identify papers reporting on OHRQoL in cleft samples. Only studies with suitable control groups were included. From each included paper were extracted the study and sample characteristics and results. MAIN OUTCOME MEASURES: OHRQoL score. RESULTS: Three papers were chosen according to the preset inclusion and exclusion criteria. All used an OHRQoL generic patient-reported questionnaire with evidence of a development and validation process, with responses recorded on a five-point scale. The results could not be combined for the purposes of meta-analysis due to lack of standardisation. In 2 of the 3 studies, the OHRQoL was found to be significantly lower in the cleft than in the non-cleft samples (in patients 8-18 or 18-65 years of age). The third study, based on a relatively small sample size, could not detect significant differences between cleft and non-cleft individuals. CONCLUSIONS: Based on the results of the few studies included in the present systematic review, non-syndromic patients with CLP tend to have a lower OHRQoL than a general non-cleft population. This seems to hold true both for children and adults.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
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 head0.087
GPT teacher head0.358
Teacher spread0.271 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations55
Published2013
Admission routes1
Has abstractyes

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