Effect of carbohydrate restriction-induced weight loss on aortic pulse wave velocity in overweight men and women
Bibliographic record
Abstract
Increased aortic stiffness, measured by carotid-to-femoral pulse wave velocity (PWV), is an independent predictor of cardiovascular disease, and past data have shown that low-fat and low-energy diets, fed for 8–24 weeks, lower PWV. The purpose of this study was to determine whether a reduction in PWV would be achieved by dietary carbohydrate (CHO) restriction, shown to bring about weight loss over a shorter timeframe. Men (n = 10, age: 41.8 ± 10.2 years, BMI: 34.2 ± 3.0 kg/m2 (mean ± SD)) and women (n = 10, age: 38.6 ± 6.1 years, BMI: 33.5 ± 3.8 kg/m2) with characteristics of insulin resistance and the metabolic syndrome consumed a structured, CHO-restricted diet for 4 weeks (energy deficit, 645 kcal/day). For the whole group, subjects lost 5.4% ± 0.5% (P < 0.001) of body weight and experienced significant reductions in blood pressure (6%–8%), plasma insulin (34%), and triglycerides (34%). PWV was reduced by 6% ± 2% (7.1 ± 0.2 m/s to 6.7 ± 0.2 m/s, P = 0.008) and surprisingly, in women, it fell significantly (from 7.2 ± 0.3 m/s to 6.3 ± 0.3 m/s, P = 0.028), while no changes were observed in men (7.2 ± 0.3 vs. 7.0 ± 0.3 m/s, P = 0.144). This is the first study to demonstrate that weight loss can improve PWV in as little as 4 weeks and that dietary CHO restriction may be an effective treatment for reducing aortic stiffness in women. Future studies are needed to establish the mechanisms by which dietary CHO restriction may confer more cardiovascular benefits to women than to men.
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 | 0.001 | 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".