Noninvasive measures of vascular health are reliable in preschool-aged children
Bibliographic record
Abstract
Measures of vascular health are known to be important predictors of cardiovascular disease in adulthood. The reliability of commonly used measures of vascular health has been demonstrated in school-aged children, adolescents, and adults; however, their reliability in preschool-aged children remains to be determined. Twenty 2- to 6-year-old children participated in 2 identical testing sessions on different days. Following 10 min of supine rest, carotid artery blood pressures and common carotid artery images were assessed simultaneously for 10 heart cycles, using applanation tonometry and B-mode ultrasound, respectively, while electrocardiogram (ECG) and infrared measures of arterial pressure waves at the dorsalis pedis were recorded continuously. Brachial artery blood pressures were determined using an automated oscillometric device. Carotid artery diameters and intima-media thickness (IMT) were analyzed using a semiautomated detection software program. Carotid compliance, distensibility, and stiffness index were calculated from carotid diameters and carotid blood pressures. Whole-body pulse-wave velocity (PWV) was determined from the time delay between the R spike of the ECG and the foot of the dorsalis pedis arterial pressure wave. Reliability of all measures was assessed using the coefficient of variation (CV) and the intraclass correlation coefficient (ICC). The most reliable measures were carotid artery IMT and PWV with CVs of 2.6% and 3.5% and ICCs of 0.86 and 0.76, respectively. The lower reliability of carotid compliance and distensibility (ICC≤0.63) is likely attributable to the variability of blood pressure measurements. This study confirms that vascular measurements demonstrate substantial reliability in preschool-aged children as young as 2 years.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".