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Record W2970138454 · doi:10.2334/josnusd.18-0299

Oral inflammatory load in patients with coronary artery disease

2019· article· en· W2970138454 on OpenAlexafffund
Vinoda Sharma, Ahmed A. Hanafi, Christopher B. Overgaard, May Shaibani, Kevin R. An, Vladimír Džavík, Michael Glogauer, Howard C. Tenenbaum

Bibliographic record

VenueJournal of Oral Science · 2019
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversity of TorontoToronto General Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineCoronary artery diseaseInternal medicinePeriodontitisDiabetes mellitusProspective cohort studyStable anginaAnginaAcute coronary syndromeCardiologyCoronary angiographyGastroenterologyMyocardial infarction

Abstract

fetched live from OpenAlex

Periodontitis is an oral inflammatory disease that may have an association with coronary artery disease (CAD). Oral inflammatory load (OIL) can be quantified by assesment of oral polymorphonucleocytes (oPMN) in an oral rinse assay. The aim of the present study was to prospectively correlate OIL with CAD on angiography assessed in terms of SYNTAX score in patients presenting with stable angina or acute coronary syndrome (ACS). Consecutive eligible patients at a cardiac center were prospectively recruited. Two sets of oral rinse samples were collected before and after angiography, and the relationship between oPMN and SYNTAX score was assessed. Of the 137 patients recruited, 32.8% (n = 45) were female and 34.3% (n = 47) had diabetes mellitus. The overall mean oPMN count was low (mean 1.3 × 105 cells/mL), and the mean SYNTAX score was 7.4 ± 8.5. Most of the patients presented with stable angina (89.8%, n =123). Patients with oPMN ≥1.45 × 105 (periodontitis threshold) were more likely to be elderly males presenting with stable angina. No significant correlation was established between oPMN and SYNTAX score. Although this prospective study did not demonstrate a correlation between OIL and the severity of CAD, most patients had low mean oPMN values. Larger studies are required before definite conclusions can be drawn.

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)0.000
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 score0.002
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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

Citations6
Published2019
Admission routes2
Has abstractyes

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