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Record W3114296056 · doi:10.1016/j.cjco.2020.12.020

Observational Cross-Sectional Study of Inflammatory Markers After Transient Ischemic Attacks, Acute Coronary Syndromes, and Vascular Stroke Events

2020· article· en· W3114296056 on OpenAlexafffund
Kevin E. Boczar, Peter Liu, Aun‐Yeong Chong, Derek So, Dar Dowlatshahi, Katey J. Rayner, Rob Beanlands

Bibliographic record

VenueCJC Open · 2020
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchGenome CanadaHeart and Stroke Foundation of CanadaGE HealthcareRocheAstraZenecaLantheus Medical ImagingUniversity of OttawaAbbott Laboratories
KeywordsPrediabetesInterquartile rangeMedicineDiabetes mellitusInternal medicineC-reactive proteinType 2 diabetesCardiologyAcute coronary syndromeMyocardial infarctionInflammationEndocrinology

Abstract

fetched live from OpenAlex

We identified the prevalence of elevated high-sensitivity C-reactive protein and interleukin-6 in patients with recent cardiovascular (CV) events with or without prediabetes/diabetes, and in a control group of patients with remote CV events. Interleukin-6 was elevated in patients with prediabetes/diabetes and recent CV events (median, 4.84 pg/mL; interquartile range, 3.27-7.45) compared with patients with remote events (2.36 pg/mL; interquartile range, 1.09-4.00). There was a trend for elevated high-sensitivity C-reactive protein in patients with acute events and prediabetes/diabetes (P = 0.147). This supports the notion that patients with prediabetes/diabetes and recent CV events have higher inflammatory burdens than patients without recent CV events or dysglycemia.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.661

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 head0.035
GPT teacher head0.308
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 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

Citations0
Published2020
Admission routes2
Has abstractyes

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