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Record W3169877704 · doi:10.14740/cr1268

Update on the Cardiovascular Benefits of Sodium-Glucose Co-Transporter-2 Inhibitors: Mechanism of Action, Available Agents and Comprehensive Review of Literature

2021· review· en· W3169877704 on OpenAlexvenueno aff
Randa Abdelmasih, Ramy Abdelmaseih, Ravi Thakker, Mohammed Faluk, Arroj Ali, Mrhaf Alsamman, Syed Mustajab Hasan

Bibliographic record

VenueCardiology Research · 2021
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRenal glucose reabsorptionDiabetes mellitusHeart failureClinical trialEmpagliflozinIntensive care medicineMechanism (biology)GlycosuriaInternal medicinePharmacologyType 2 Diabetes MellitusCardiologyBioinformaticsEndocrinology

Abstract

fetched live from OpenAlex

Despite the currently established treatment for heart failure (HF), HF remains a growing public healthcare problem with an increasing burden. Therefore, novel therapeutic innovations are needed to overcome this issue and improve HF prognosis. Sodium-glucose co-transporter-2 inhibitors (SGLT2i) are state-of-the-art in type 2 diabetes mellitus management. They inhibit the reabsorption of glucose from the proximal renal tubules, leading to increased glycosuria and decreased plasma glucose levels. SGLT2i use is growing significantly, especially after recent clinical trials demonstrating favorable cardiovascular and renal protective effects independently of blood glucose-lowering. The mechanisms by which SGLT2i demonstrate their cardio-renal protective effects remain incompletely understood but are thought to be related to potential diuretic and natriuretic effects along with other mechanisms that will be discussed in this article. Over the past few years, there has been significant research on the safety, efficacy, and quality of this class of medications. Here, we review the current guideline-directed medical therapy for HF, focus on SGLT2i mechanism of action and potential role in HF patients, and finally summarize the cardiovascular clinical trials with SGLT2.

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)0.002
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 score0.799
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.173
GPT teacher head0.397
Teacher spread0.224 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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