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Record W2891376948 · doi:10.14740/jocmr3587w

Strong Association Between Weight Reduction and Suppression of Cardiovascular Events in Recent Clinical Trials of DPP4 Inhibitors, GLP-1 Receptor Agonists, and SGLT2 Inhibitors

2018· article· en· W2891376948 on OpenAlexvenueno aff
Tatsuo Yanagawa

Bibliographic record

VenueJournal of Clinical Medicine Research · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePharmacologyClinical trialGlucagon-like peptide 1 receptorWeight lossReceptorInternal medicineBioinformaticsObesityAgonistBiology

Abstract

fetched live from OpenAlex

The 2008 US Food and Drug Administration (FDA) regulation requires to demonstrate in clinical trials of new antidiabetic drugs, that these drugs do not increase the risk of development of cardiovascular events as compared to existing drugs, after adjustment for major risk factors.It has been difficult to show superiority of newer drugs after adjustments for the major risk factors, and in fact, superiority could not be demonstrated in the initial three trials of DPP-4 inhibitors [1][2][3].Therefore, it came as an unexpected surprise that the SGLT2 inhibitor empagliflozin showed superiority in the EMPA-REG OUTCOME study [4].Thereafter, superiority was again demonstrated in one study of SGLT2 inhibitor, CANVAS [5], two studies of GLP-1 receptor agonists, LEADER [6], and SUSTAIN-6 [7], but not in another two studies of GLP-1 receptor agonists, ELIXA [8], and EXCEL [9].Various hypotheses have been proposed in regard to factors influencing the demonstration of superiority, but there is no widely accepted theory.It has been suggested that differences in the patients' background characteristics may be a factor.It is also possible that the incidence of cardiovascular events is not sufficiently high in studies with a short study period, and that there is a bias towards patients with slightly higher risk being in the active drug group.We focused on weight reduction, because weight gain is a risk factor for cardiovascular diseases, independent of disordered glucose metabolism, elevated blood pressure, and abnormal lipid profile [10].We examined the correlations between the body weight changes and hazard ratios before and after treatment in eight studies [1-2, 4-9].In , since the analysis was carried out with semaglutide 0.5 mg and 1 mg treatment respectively, both were adopted.The TECOS study [3] was excluded, as there were no data on the body weight changes in this study.As shown in the Figure 1 [1-9], there was a strong cor-

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)0.024
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.257
GPT teacher head0.531
Teacher spread0.273 · 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.

Study designMeta-analysis
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

Citations2
Published2018
Admission routes1
Has abstractyes

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