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Record W4392597454 · doi:10.1186/s13023-024-03096-y

The impact of osteogenesis imperfecta severity on oral health-related quality of life in Spain: a cross-sectional study

2024· article· en· W4392597454 on OpenAlexaff
Amira Ahmed Elfituri, Mohammadamin Najirad

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOsteogenesis imperfectaQuality of life (healthcare)Oral healthCross-sectional studyCraniofacialOral hygieneDentistryPediatricsInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Osteogenesis imperfecta (OI) affects dental and craniofacial development; therefore, it can influence oral health-related quality of life (OHRQoL). The objective of this study was to explore the influence of the severity of OI on OHRQoL in adults older than eighteen years residing in Spain. METHOD: Adults with OI were recruited from the Spanish Association of Crystal Bone (AHUCE) foundation. OHRQoL was evaluated using the Spanish version of the Oral Health Impact Profile questionnaire (OHIP-14sp), oral hygiene habits, and a dental care survey. Clinical and radiological dental examinations were performed to evaluate the patients' oral conditions. RESULTS: A total of 65 adults (n = 46 females) aged between nineteen and sixty-two years who were diagnosed with OI and classified as type I, III, and IV (n = 20, 14, and 31, respectively) participated in this research. The total OHIP-14sp scores were significantly greater (worse) for type III (23 [SD = 10]) and type IV (21.4 [SD = 12]) than for type I (13.8 [SD = 6]) (P < 0.05). The negative impact of OHRQoL was due to the association of type III OI with all domains except for the handicap domain, while type IV OI was associated with the physical disability, social disability, and handicap domains (P < 0.05 for all). CONCLUSION: The severity of OI negatively impacted OHRQoL in adults. This association was statistically significant.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.041
GPT teacher head0.396
Teacher spread0.355 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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