Acarbose Slows Progression of Intima-Media Thickness of the Carotid Arteries in Subjects With Impaired Glucose Tolerance
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Impaired glucose tolerance (IGT)-a prediabetic state-is an important risk factor for atherosclerosis. Acarbose, an alpha-glucosidase inhibitor, was shown in the placebo-controlled prospective study to prevent noninsulin-dependent diabetes mellitus (STOP-NIDDM) trial to reduce the risk of diabetes by 36% in IGT subjects. This article reports on a placebo-controlled subgroup analysis of the STOP-NIDDM study to examine the efficacy of acarbose to slow progression of intima-media thickness (IMT) in subjects with IGT. METHODS: One hundred thirty-two IGT subjects were randomized to placebo (n=66) or acarbose (n=66) 100 mg 3 times daily; the study duration was at least 3 years, mean follow-up time 3.9 (SD 0.6) years. Carotid IMT was determined at study entry and the end of the trial. The intent-to-treat analysis included 56 subjects in the acarbose and 59 in the control group who had a baseline and endpoint measurement. RESULTS: A significant reduction of the progression of IMT(mean) was observed in the acarbose group versus placebo. After an average time of 3.9 years, IMT(mean) increased by 0.02 (0.07) mm in the acarbose group versus 0.05 (0.06) mm in the placebo group (P=0.027). The annual increase of IMT(mean) was reduced by approximately 50% in the acarbose group versus placebo. Multiple linear regression revealed IMT progression as significantly related to acarbose intake. CONCLUSIONS: Acarbose slows progression of IMT in IGT subjects, a high-risk population for diabetes and atherosclerosis. This is the first placebo-controlled prospective subgroup analysis, demonstrating that counterbalancing of postprandial hyperglycemia may be vasoprotective.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".