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Sickle cell disease does not predispose to caries or periodontal disease

2012· article· en· W2151018982 on OpenAlexfundno aff
Cristina Pinho Passos, Poliana Ramos Braga Santos, Márcio Cajazeira Aguiar, Maria Cristina Teixeira Cangussú, Maria Betânia Pereira Toralles, Maria Christina Bahiana Olympio da Silva, Roberto José Meyer Nascimento, Maria Isabela Guimarães Campos

Bibliographic record

VenueSpecial Care in Dentistry · 2012
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
FundersAGE-WELL
KeywordsMedicineLogistic regressionPeriodontal diseaseDiseaseDental flossDentistryTooth lossOral healthInternal medicine

Abstract

fetched live from OpenAlex

This study investigated the prevalence of dental caries and periodontal condition in a population with sickle cell disease (SCD), analyzing some associations with disease severity. The Decayed, Missing and Filled Teeth index (DMFT) and Community Periodontal Index (CPI) were recorded for 99 individuals with SCD and 91 matched controls. Socio-demographic status, oral health behaviors, and history of clinical severity of SCD were assessed. Statistical comparisons were performed between the group with SCD and the control group, as well as multivariate logistic regression analyses with DMFT index and CPI as the dependent variables. The mean number of decayed teeth was significantly higher in individuals with HbSS. Older age, female gender, and daily smoking were identified as risk factors for higher DMFT, while older age and absence of daily use of dental floss were risk factors for the development of periodontal disease. In conclusion, risk factors known to cause caries and periodontal disease had more influence on oral health than the direct impact of SCD.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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 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

Citations46
Published2012
Admission routes1
Has abstractyes

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