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Record W4280585270 · doi:10.1016/j.jacc.2022.03.353

Sodium Glucose Cotransporter-2 Inhibition for Acute Myocardial Infarction

2022· review· en· W4280585270 on OpenAlexafffund
Jacob A. Udell, W. Schuyler Jones, Mark C. Petrie, Josephine Harrington, Stefan D. Anker, Deepak L. Bhatt, Adrian F. Hernandez, Javed Butler

Bibliographic record

VenueJournal of the American College of Cardiology · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsToronto General HospitalWomen's College HospitalUniversity of Toronto
FundersJanssen PharmaceuticalsDuke Clinical Research InstituteNational Heart, Lung, and Blood InstituteNational Institutes of HealthMinistry of Colleges and UniversitiesServierSt. Jude MedicalAssistance publique-Hôpitaux de ParisAgency for Healthcare Research and QualityVifor PharmaMyoKardiaNovo NordiskDaiichi-SankyoWomen's College HospitalImpulse DynamicsBoston VA Research InstituteRegado BiosciencesBoston Scientific CorporationUniversity of TorontoBritish Heart FoundationBristol-Myers SquibbCleveland ClinicAmerican Heart AssociationSanofiAstraZenecaAmgen
KeywordsMedicineMyocardial infarctionHeart failureDiabetes mellitusInternal medicineCardiologyType 2 Diabetes MellitusDiseaseCanagliflozinKidney diseaseIntensive care medicineType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Sodium glucose cotransporter-2 (SGLT2) inhibitors improve cardiorenal outcomes in patients with type 2 diabetes mellitus, chronic kidney disease, and chronic heart failure. SGLT2 inhibitors also reduce the risk of cardiovascular mortality and hospitalization for heart failure among patients with type 2 diabetes mellitus and a remote history of myocardial infarction (MI). As a result of the growing body of evidence in diverse disease states, and the hypothesized mechanisms of action, it is reasonable to consider the potential of SGLT2 inhibition to improve outcomes in patients with acute MI as well if initiated early after presentation. Whether these therapies are efficacious and safe to use early in the course of acute coronary heart disease remains relatively unexplored. Here, we describe the contemporary data and continuing evidence gap for considering the use of SGLT2 inhibitors early following an acute MI to reduce cardiovascular morbidity and mortality.

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 score0.908
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
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 head0.025
GPT teacher head0.311
Teacher spread0.286 · 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

Citations101
Published2022
Admission routes2
Has abstractyes

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