3.3 Age- and Sex-specific Reference Intervals for Brachial Artery Flow-mediated Dilation in Healthy Individuals and the Relation with Cardiovascular Risk Factors
Bibliographic record
Abstract
Abstract Background Assessment of endothelial function using brachial artery flow-mediated dilation (FMD) predicts future cardiovascular disease (CVD) risk. However, poor adherence to protocol guidelines and lack of reference values hinders widespread FMD use. This study established age- and sex-specific reference intervals for brachial artery FMD in healthy individuals and examined the relation with CVD risk factors. Methods Collected according to expert-consensus guidelines, we combined brachial artery FMD and subject characteristics/medical history from 5,362 individuals (4–84 years; 2,076 females). We first examined healthy individuals ( n = 1,403 [582 females]) to generate age-/sex-specific percentile curves. Subsequently, we included subjects with CVD risk factors but without disease (un-medicated n = 3,167 [1,247 females], and medicated n = 792 [247 females]). Multiple linear regression tested the relation of CVD risk factors with FMD. Results Healthy men showed a negative, curvilinear relation between FMD and age, whilst females revealed a linear relation that started higher, but declined at a faster rate. Age-/sex-related differences in FMD, at least partly, relate to baseline artery diameter. FMD was affected by CVD risk factors in un-medicated (e.g. systolic-/diastolic blood pressure, diabetes) and medicated subjects (e.g. dyslipidaemia). Importantly, sex mediated these effects ( p < 0.05), with (supra) normalisation of FMD in medicated men, but not in women (except for blood pressure). Conclusion Sex alters the age-related decline in FMD, which is partly explained through differences in artery diameter. Sex also altered the effect of some CVD risk factors and medication on FMD. This work improves interpretation and future use of the FMD technique when strictly adhering to FMD protocol guidelines.
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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 | 0.005 | 0.000 |
| 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) | 0.000 | 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".