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Record W6927010540 · doi:10.25384/sage.c.6722307

Cardiometabolic risk factors, peripheral arterial tonometry and metformin in adults with type 1 diabetes participating in the REducing with MetfOrmin Vascular Adverse Lesions trial

2023· other· en· W6927010540 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsMetforminHyperaemiaBlood pressureWaistDiabetes mellitusPlaceboType 2 diabetesVascular disease

Abstract

fetched live from OpenAlex

BackgroundPeripheral arterial tonometry (PAT) provides non-invasive measures of vascular health. Beneficial effects of metformin on vascular function have been reported in youth with type 1 diabetes (T1D). In the REducing with MetfOrmin Vascular Adverse Lesions (REMOVAL) trial in adults with T1D and high cardiovascular risk, we examined: (i) the extent to which routinely-measured cardiometabolic risk factors explain variance in baseline PAT; and (ii) the effects of metformin on PAT measures.MethodsCross-sectional univariable and multivariable analyses of baseline reactive hyperaemia index (RHI) and augmentation index (AI) (EndoPAT® (Itamar, Israel); and analysis of 36-months metformin versus placebo on vascular tonometry.ResultsIn 364 adults ((mean ± SD) age 55.2 ± 8.5 years, T1D 34.0 ± 10.6 years, HbA1c 64.5 ± 9.0 mmol/mol (8.1 ± 0.8%)), RHI was 2.26 ± 0.74 and AI was 15.9 ± 19.2%. In an exhaustive search, independent associates of (i) RHI were smoking, waist circumference, systolic blood pressure and vitamin B12 (adjusted <i>R</i><sup>2</sup> = 0.11) and (ii) AI were male sex, pulse pressure, heart rate and waist circumference (adjusted <i>R</i><sup>2</sup> = 0.31). Metformin did not significantly affect RHI or AI.ConclusionCardiometabolic risk factors explained only a modest proportion of variance in PAT measures of vascular health in adults with T1D and high cardiovascular risk. PAT measures were not affected by metformin.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.279
Teacher spread0.245 · 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.

Study designOther design
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

Citations0
Published2023
Admission routes1
Has abstractyes

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