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Novel Drugs for Diabetes Also Have Dramatic Benefits on Hard Outcomesof Heart and Kidney Disease

2022· review· en· W4280518784 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Cardiology Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDiabetes mellitusType 2 diabetesDiseaseIntensive care medicineClinical trialCanagliflozinKidney diseaseInternal medicineDiabetologySemaglutideLiraglutideEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetes is a major risk factor for developing cardiovascular disease. Patients with both diabetes and cardiovascular disease have even higher mortality. The convergence of cardiology and diabetology therapy is an important step in treating patients and advancing research. RESULTS: Major landmark trials and meta-analyses involving Sodium Glucose Cotransporter 2 inhibitors have shown dramatic clinical cardiorenal benefits in patients both with and without type 2 diabetes. In type 2 diabetes patients, Glucagon-like peptide-1 receptor agonists have been shown to improve major cardiac outcomes. CONCLUSION: This hot topic of research and clinical use of glucose lowering drugs intersects the fields of cardiovascular, renal, and diabetic medicine. The numerous cardiorenal benefits have led to the rapid adoption in clinical guidelines of these glucose lowering drugs in patients with Type 2 diabetes, cardiovascular disease, or renal disease.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.003
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 head0.139
GPT teacher head0.376
Teacher spread0.237 · 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