Assessment of flow-mediated dilation in humans: a methodological and physiological guideline
Bibliographic record
Abstract
Endothelial dysfunction is now considered an important early event in the development of atherosclerosis, which precedes gross morphological signs and clinical symptoms. The assessment of flow-mediated dilation (FMD) was introduced almost 20 years ago as a noninvasive approach to examine vasodilator function in vivo. FMD is widely believed to reflect endothelium-dependent and largely nitric oxide-mediated arterial function and has been used as a surrogate marker of vascular health. This noninvasive technique has been used to compare groups of subjects and to evaluate the impact of interventions within individuals. Despite its widespread adoption, there is considerable variability between studies with respect to the protocols applied, methods of analysis, and interpretation of results. Moreover, differences in methodological approaches have important impacts on the response magnitude, can result in spurious data interpretation, and limit the comparability of outcomes between studies. This review results from a collegial discussion between physiologists with the purpose of developing considered guidelines. The contributors represent several distinct research groups that have independently worked to advance the evidence base for improvement of the technical approaches to FMD measurement and analysis. The outcome is a series of recommendations on the basis of review and critical appraisal of recent physiological studies, pertaining to the most appropriate methods to assess FMD in humans.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".