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Record W2540531980 · doi:10.22374/1710-6222.23.1.1

Sulfonylurea and the Heart: Theoretically a Compounded Question from a Pathophysiological Perspective.

2016· article· en· W2540531980 on OpenAlexaff
Pendar Farahani

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePathophysiologyAtrial fibrillationInternal medicineCardiologyHypoglycemiaPerspective (graphical)Diabetes mellitusSulfonylurea receptorObesityHeart failureIntensive care medicineBioinformaticsEndocrinology

Abstract

fetched live from OpenAlex

Evidence from literature illustrates that from a pathophysiological perspective, sulfonylureas (SU) may impact the heart three ways: directly by intrinsic properties from a pharmacological receptor perspective, indirectly by adverse effects related to hypoglycemia, and obesity. From a pharmacologlogical receptor perspective, SU can bind to ATP-sensitive potassium channels in cardiomyocytes. Channel binding by SU in cardiac tissue may prevent ischemia myocardial protective mechanisms. From a pathophysiological perspective, obesity is associated with cardiac issues such as pulmonary hypertension, left ventricular hypertrophy, arrhythmia, and atrial fibrillation. From a pathophysiological perspective, hypoglycemia is associated with cardiac sympathetic activation and QT prolongation. With the high prevalence and incidence of diabetes, obesity and aging, future basic and clinical studies should further explore the questions related to the pathophysiology of SU utilization and potential cardiac impact in randomized clinical trials and real-world outcome research settings.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.225
Teacher spread0.217 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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