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128 Periodontal disease in systemic lupus erythematosus: is there a link?

2018· article· en· W2799744841 on OpenAlexaff
Zoe Rutter‐Locher, Nicholas R. Fuggle, Marco Orlandi, Arvind Kaul, Francesco D’Aiuto, Nidhi Sofat

Bibliographic record

VenueLara D. Veeken · 2018
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineSystemic diseasePeriodontal diseaseDermatologyLupus erythematosusSystemic lupusDiseaseImmunologyInternal medicineAntibody

Abstract

fetched live from OpenAlex

Background: An association has been demonstrated between periodontal disease (PD) and rheumatoid arthritis. Less data is available for systemic lupus erythematosus (SLE) but on meta-analysis of eight studies including 1,383 participants, risk of PD in SLE cases compared to controls was significantly greater with a risk ratio of 1.76 (95% CI 1.29-2.41, p = 0.0004). Our objective was to assess PD severity in participants with SLE in a London tertiary centre. Methods: SLE patients (diagnosis by rheumatologist + Anti dsDNA/Anti Sm positive) were compared to healthy controls and non-inflammatory osteoarthritis (OA) control patients. Measures of periodontal disease were ascertained by a blinded examiner. Periodontitis was defined according to Eke & Page classification. Kruskal-Wallis test and Chi-square test were applied to test numerical and categorical data respectively. Spearman’s correlation and linear regression were used to test for correlations. Results: 100% of participants in the SLE and controls groups had either mild, moderate or severe periodontitis. All measures of PD were similar in the three groups (Table 1)

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.293
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes1
Has abstractyes

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