MétaCan
Menu
Back to cohort
Record W2940353781 · doi:10.1111/joor.12798

Where periodontitis meets metabolic syndrome—The role of common health‐related risk factors

2019· article· en· W2940353781 on OpenAlexaff
Ragda Abdalla‐Aslan, Mordechai Findler, Liran Levin, Avraham Zini, Boaz Shay, Gilad Twig, Galit Almoznino

Bibliographic record

VenueJournal of Oral Rehabilitation · 2019
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePeriodontitisMetabolic syndromeDiabetes mellitusBlood pressureAbdominal obesityWaistInternal medicineStroke (engine)ObesityPopulationLogistic regressionEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVES: To analyse and compare associations between metabolic syndrome (MetS) and its components in periodontitis compared to control patients. METHODS: This 7-year cross-sectional study retrospectively analysed medical records of 504 individuals aged 18-90 who attended the student dental clinic between 2008 and 2014. Demographics, smoking habits, blood pressure, waist circumference, as well as presence of: periodontitis, MetS, diabetes, hypertension, hyperlipidaemia, stroke, heart disease, cancer and psychiatric disorders were recorded. RESULTS: The study population composed of 231 (45.8%) males and 273 (54.2%) females, with an average age of 55.79 ± 16.91 years. A patient profile associated with periodontitis was identified and included male sex, older age, smoking, higher smoking pack-years, abdominal obesity, higher systolic and diastolic blood pressures, the presence of MetS or its components, hypertension, hyperlipidaemia, diabetes or diseases associated with its consequences such as ischaemic heart disease and stroke. Following multivariate logistic regression analysis, age and smoking retained a significant association with periodontitis, whereas the systemic disorders did not. CONCLUSIONS: The association between periodontitis and MetS may be explained by shared common profile and risk factors. An appropriate risk factors management approach should be adopted by both dental and general health clinicians and health authorities, to control common high-risk behaviours.

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)0.002
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.290
Teacher spread0.281 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oral RehabilitationSame topicOral microbiology and periodontitis researchFrench-language works237,207