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Record W2922459115 · doi:10.2337/dc18-2483

Dysglycemia and the Density of the Coronary Vasa Vasorum

2019· article· en· W2922459115 on OpenAlexaff
Hertzel C. Gerstein, Vidhya Nair, Ruchi Chaube, Heidi Stoute, Geoff H. Werstuck

Bibliographic record

VenueDiabetes Care · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsOttawa HospitalThrombosis and Atherosclerosis Research InstituteUniversity of OttawaHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsVasa vasorumAdventitiaMedicineDiabetes mellitusAutopsyCardiologyInternal medicineArteryImmunohistochemistryEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVE This study was conducted to determine the relationship between dysglycemia and the coronary artery vasa vasorum density. RESEARCH DESIGN AND METHODS The left anterior descending coronary artery was removed from 57 deceased individuals during autopsy, and the capillaries in the vessel wall were identified using fluorescent immunohistochemical staining. HbA1c was determined in postmortem whole blood for each individual. The density of the vasa vasorum in the intima-media and the adventitia was manually quantified and recorded by readers unaware of the individual’s other characteristics. RESULTS The individuals with diabetes had a lower density of the coronary vasa vasorum than those without diabetes. The higher the HbA1c, the lower the density of these vessels in the adventitia and entire vessel wall. CONCLUSIONS Dysglycemia-induced damage to the vasa vasorum may promote ischemic heart disease in people with diabetes.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.009
Threshold uncertainty score0.138

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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

Labeled directly by 2 models reading the full record.

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

Citations23
Published2019
Admission routes1
Has abstractyes

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