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Record W2888680621 · doi:10.2337/dbi18-0008

The Ascending GLP-1 Road From Clinical Safety to Reduction of Cardiovascular Complications

2018· review· en· W2888680621 on OpenAlexafffund
Daniel J. Drucker

Bibliographic record

VenueDiabetes · 2018
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineIncretinDiabetes mellitusGlucagon-like peptide-1Type 2 diabetesMyocardial infarctionGlucose homeostasisGastric emptyingLiraglutideGlucagon-like peptide 1 receptorStroke (engine)Internal medicineEndocrinologyBioinformaticsReceptorInsulin resistanceAgonistBiology

Abstract

fetched live from OpenAlex

Glucagon-like peptide 1 (GLP-1) was originally identified as a gut-derived incretin hormone that lowered glycemia through potentiation of glucose-dependent insulin secretion. Subsequent studies expanded the actions of GLP-1 to include inhibition of glucagon secretion, gastric emptying, and appetite, collectively useful attributes for a glucose-lowering agent. The introduction of GLP-1 receptor (GLP-1R) agonists for the treatment of diabetes was associated with questions surrounding their safety, principally with regard to medullary thyroid cancer, pancreatitis, and pancreatic cancer, yet cardiovascular outcome trials subsequently revealed reductions in rates of stroke, myocardial infarction, and cardiovascular death with a paucity of major safety signals. We discuss the controversies, unanswered questions, and established use of GLP-1R agonists from a mechanistic and clinical perspective. We highlight methods for detection and cellular sites of GLP-1R expression, key uncertainties, recent insights, and experimental caveats surrounding the use of GLP-1R agonists for the treatment of diabetes and the reduction of diabetes-related complications.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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 head0.079
GPT teacher head0.374
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations76
Published2018
Admission routes2
Has abstractyes

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