The impact of metabolic syndrome and endothelial dysfunction on exercise‐induced cardiovascular changes
Bibliographic record
Abstract
OBJECTIVE: There is limited information regarding the synergistic or additive effects of metabolic syndrome (MS) and endothelial dysfunction (ED) on cardiovascular disease (CVD). Altered cardiovascular responses to exercise have been shown to predict future cardiovascular events as well as assess autonomic function. The present study evaluated the impact of MS and brachial artery reactivity (a proxy of ED) on peak exercise-induced cardiovascular changes. DESIGN AND METHODS: Individuals (n = 303) undergoing a standard nuclear medicine exercise stress test were assessed for MS. Participants underwent a Forearm Hyperaemic Reactivity test and were considered to have dysfunctional reactivity if their rate of uptake ratio (RUR) was <3.55. Resting and peak blood pressure (BP) and heart rate (HR) were measured. Reactivity was calculated as the difference between peak and resting measures. RESULTS: Analyses, adjusting for age, sex, resting HR, total metabolic equivalents (METs), and a history of major CVD, revealed a main effect of MS (F = 5.51, η(2) = 0.02, P = 0.02) and RUR (F = 6.69, η(2) = 0.02, P = 0.01) on HR reactivity, such that patients with MS and/or poor RUR had reduced HR reactivity. There were no interactive effects of RUR and MS. There were no effects of RUR or MS on systolic BP (SBP) or diastolic BP (DBP) reactivity or rate pressure product (RPP) reactivity. CONCLUSIONS: The presence of decreased HR reactivity among participants with MS or poor brachial artery reactivity, combined with the lack of difference in other exercise-induced cardiovascular changes, indicates that these patients may have some degree of parasympathetic dysregulation. Further longitudinal studies are needed to understand the long-term implications of MS and endothelial abnormalities in this context.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".