Influence of Postprandial Hyperglycemic Conditions on Arterial Stiffness in Patients With Type 2 Diabetes
Bibliographic record
Abstract
CONTEXT: Patients with type 2 diabetes (T2D) are at an increased risk of cardiovascular disease. OBJECTIVE: The objective of the study was to determine whether postprandial hyperglycemia affects arterial function in T2D. DESIGN: A single-center, open-label study of three groups of men were studied: 1) T2D patients with albuminuria (n = 22), 2) T2D patients without albuminuria (n = 24), and 3) nondiabetic controls (n = 25). Patients were randomized to a two-period crossover study schedule, ingesting breakfast, with or without insulin lispro (to induce low or high postprandial glycemia). MAIN OUTCOME MEASURES: Arterial stiffness was assessed by calculating pulse wave velocity (PWV) and augmentation index using applanation tonometry, and endothelial dysfunction was assessed using peripheral arterial tonometry, 30 minutes before breakfast and up to 240 minutes after breakfast. RESULTS: At baseline, arterial stiffness was increased in patients. When adjusted for age and body mass index, in a combined group of patients with and without albuminuria, brachial PWV was higher during low (P = .032) and high (P = .038) postprandial glycemia vs controls. These differences were driven by the albuminuria group vs controls during low (P = .014) and high (P = .018) postprandial glycemia. No differences were observed in aortic PWV, augmentation index, or peripheral arterial tonometry ratio between patients and controls. Endothelin-1 and IL-6 were higher, and superoxide dismutase was lower, during postprandial hyperglycemia in T2D patients vs controls. CONCLUSIONS: In patients with T2D and albuminuria, brachial PWV was higher under postprandial hyperglycemic conditions, relative to controls. These data suggest that hyperglycemia induces an increase in stiffness of intermediate-sized arteries. We found no changes in other parts of the arterial bed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".