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Prevalence of oral diseases in Shwachman‐Diamond syndrome

2007· article· en· W1986672365 on OpenAlexafffund
William Ho, Chrisovalantou Cheretakis, Peter R. Durie, Gajanan Kulkarni, Michael Glogauer

Bibliographic record

VenueSpecial Care in Dentistry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineDentistryInternal medicineCross-sectional studyOral examinationOral healthPathology

Abstract

fetched live from OpenAlex

The aim of this study was to determine the prevalence and severity of oral diseases in patients with ShwachmanDiamond syndrome (SDS). Thirty-five persons with SDS were compared to 20 healthy controls. A cross-sectional survey was carried out using self-reporting questionnaires and dental radiographs collected from the subjects and their dentists. Overall, oral diseases were more prevalent among subjects with SDS when compared to controls (p < 0.001). Persons with SDS also had more caries in both primary (p < 0.03) and permanent dentitions (p < 0.01), and also had delayed dental development (p < 0.04). Oral soft tissue pathoses, such as recurrent oral ulcerations (p < 0.00) and gingival bleeding upon brushing (p < 0.00), were significantly more prevalent in subjects with SDS. Pain on eating was also more frequent amongst persons with SDS (p < 0.008) and was often associated with oral ulcerations (p < 0.002). In conclusion, based on self-completed subject and dentist questionnaires, diseases of oral hard and soft tissues were more prevalent and severe in persons with SDS when compared with healthy controls.

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 score0.011
Threshold uncertainty score0.451

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 head0.006
GPT teacher head0.264
Teacher spread0.258 · 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

Citations19
Published2007
Admission routes2
Has abstractyes

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