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Effect of acarbose treatment on the risk of silent myocardial infarctions in patients with impaired glucose tolerance: results of the randomised STOP-NIDDM trial electrocardiography substudy

2004· article· en· W2046113689 on OpenAlexaff
Uwe Zeymer, Alexandra Schwarzmaier-D'Assie, D. Petzinna, J.‐L. Chiasson

Bibliographic record

VenueEuropean Journal of Cardiovascular Prevention & Rehabilitation · 2004
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsHôtel-Dieu de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsAcarboseMedicinePostprandialImpaired glucose tolerancePlaceboInternal medicineDiabetes mellitusImpaired fasting glucoseCardiologyType 2 diabetesIncidence (geometry)EndocrinologyInsulinPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The moderate increase in postprandial plasma glucose in subjects with impaired glucose tolerance has been shown to be a predictor of cardiovascular disease. In the randomised STOP-NIDDM trial, we could demonstrate that lowering postprandial plasma glucose with acarbose in subjects with impaired oral glucose tolerance could reduce the risk of diabetes. METHODS: The current report focuses on the effect of acarbose on silent ischaemic events evaluated in the electrocardiographic substudy, using the Minnesota code classification. RESULTS: A total of 1181 patients were included in the ECG substudy. From these 72 patients had significant changes between the baseline and end of treatment ECG, 33 in the acarbose and 39 in the placebo group. Higher rates of myocardial infarctions occurred in the placebo group (P=0.07 with Fisher's Exact test and P=0.023 with Chi-square test), while there were no differences between the two groups with ECG changes classified under the other Minnesota codes. CONCLUSIONS: In this prospective intervention study we could show that acarbose, by decreasing postprandial hyperglycaemia, can reduce the incidence of silent myocardial infarctions in subjects with impaired glucose tolerance. This approach should therefore be evaluated in other higher risk populations.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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 designRandomized trial
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

Citations50
Published2004
Admission routes1
Has abstractyes

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