A larger low‐flow‐mediated constrictor response is associated with augmented flow‐mediated dilation in the popliteal artery
Bibliographic record
Abstract
Abstract In the brachial artery, conflicting evidence exists regarding the relationship between the low‐flow–mediated constriction (L‐FMC) and subsequent flow‐mediated dilation (FMD) responses, which may confound interpretation of the latter. The popliteal artery is a common site for atherosclerotic development, which is preceded by endothelial dysfunction. We aimed to determine whether the magnitude of popliteal L‐FMC impacted FMD responses, which is currently unknown. L‐FMC and FMD were assessed in the popliteal artery via high‐resolution duplex ultrasonography and quantified as the percent change in diameter (from baseline) during ischaemia and in response to hyperaemia, respectively. Using partial correlations and multiple regression analyses, we evaluated the association between popliteal L‐FMC on FMD in 110 healthy participants (60 females; 42 ± 22 [19–77] years). All variables univariately associated (p < 0.05) with popliteal relative FMD (relative L‐FMC, log‐SRAUC, age, systolic blood pressure, diastolic blood pressure, resting shear rate) were inputted into a model that explained 35% of the variance. The reactive hyperaemia stimulus (log‐SRAUC: β = 1.10) and relative L‐FMC (β = −0.39) were the only independent predictors of FMD (both, p < 0.01). Relative L‐FMC was negatively correlated to relative FMD, after controlling for the significant univariate predictor variables listed above (R = −0.30; p = 0.002). An augmented (ie healthier) L‐FMC response was linked with a larger FMD response as determined by the independent inverse association observed between these shear‐stress–mediated measures of vasoreactivity.
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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 | 0.001 | 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 | 0.001 |
| 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".