The association between near‐infrared spectroscopy assessment of microvascular reactivity and flow‐mediated dilation is disrupted in individuals at high risk for cardiovascular disease
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the correlation between the NIRS-derived reperfusion slope and %FMD in the arm of healthy and at high risk for CVD individuals. METHODS: Twelve healthy (24 ± 4 years) and twelve at high risk for cardiovascular disease (65 ± 11 years) individuals participated in the study. The individuals were submitted to a conduit artery FMD followed by a NIRS-VOT microvascular function test in the arm. Microvascular responsiveness was calculated as the forearm reperfusion slope, and macrovascular function was assessed as the percent of change in FMD (%FMD) of the brachial artery. RESULTS: There was a significant correlation between reperfusion slope and %FMD (R = 0.61, P < 0.05) in the healthy group; however, no significant correlation between FMD and reperfusion slope (R = -0.21, P > 0.05) was found in individuals at high risk for CVD. CONCLUSION: The correlation between NIRS-derived reperfusion slope and %FMD was disrupted in the arm of individuals at high risk for cardiovascular disease compared to healthy individuals. The findings of the present study reinforce the importance of examining vascular function at microvasculature and conduit artery level, especially in populations with risk factors for CVD.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".