P4.02 Assessing ventricular–vascular interactions non-invasively in healthy adolescents☆
Bibliographic record
Abstract
Background: Characterization of normal ventricular–vascular interactions by non-invasive assessment in healthy adolescents may provide new mechanistic insights into altered physiological states in congenital and acquired heart disease in this age group. Methods: Ventricular and vascular measures were non-invasively determined in 113 healthy adolescents (57 females, aged 10–18 years) on the same occasion. Ventricular assessment included standard echocardiographic M-mode and 2D volumetric techniques, and pulse and tissue Doppler imaging. Vascular assessment included carotid and brachial artery ultrasound, applanation tonometry and echo-Doppler of the aorta. Arterial (Ea) and left ventricular (LV) end-systolic (Ees) elastance were estimated noninvasively and their ratio used to assess ventricular-arterial coupling. Sample characteristics were assessed against a standard normal distribution. Relationships were tested using Pearson’s correlations. Statistical significance was considered at p<0.01. Results: All measures were normally distributed. Carotid intima-media thickness (CIMT) had significant positive correlations (see Table) with LV mass-indexed to BSA, LV mean velocity of circumferential fibre shortening corrected (VCFc), mitral valve (MV) pulse/tissue Doppler velocity ratio (E/E′) and Ea/Ees ratio, but a negative correlation with Ees. Central pulse wave velocity (PWV) around the aortic arch by echo-Doppler assessment had significant positive correlations with LV ejection fraction (EF) and myocardial performance index (MPI). Aortic PWV from carotid to femoral artery by applanation tonometry and flow-mediated dilatation (FMD) showed no significant correlations. Conclusions: Ventricular-vascular interactions were found with proximal rather than distal aortic and arterial structure and function. These non-invasively determined ventricular-vascular interactions may be of benefit in monitoring progression and therapeutic response in adolescent disease populations. Variable CIMT FMD Aortic PWV Central PWV Mean±SD 0.431±0.046 mm 7.4±3.1% 5.0±0.9 m/s 4.5±1.1 m/s LV EF r=+0.06, p=0.54 r=+0.07, p=0.53 r=−0.01, p=0.99 r=+0.26, p<0.01 61±6% LV VCFc r=+0.28, p<0.005 r=−0.06, p=0.57 r=+0.01, p=0.91 r=+0.19, p=0.05 1.13±0.17 circ/s LV mass-indexed r=+0.25, p<0.01 r=−0.08, p=0.42 r=−0.08, p=0.43 r=+0.09, p=0.37 65±12 g/m2 LV MPI r=+0.17, p=0.08 r=+0.05, p=0.63 r=+0.03, p=0.73 r=+0.30, p<0.01 0.3±0.09 MV E/E′ r=+0.25, p<0.01 r=−0.08, p=0.44 r=+0.06, p=0.56 r=+0.15, p=0.12 5.2±0.9 Ea r=−0.17, p=0.08 r=+0.06, p=0.55 r=−0.13, p=0.18 r=+0.15, p=0.11 1.63±0.44 mmHg/ml Ees r=−0.27, p<0.01 r=+0.08, p=0.40 r=−0.11, p=0.26 r=+0.07, p=0.46 3.13±1.01 mmHg/ml Ea/Ees r=+0.28, p<0.01 r=−0.14, p=0.17 r=+0.03, p=0.74 r=+0.09, p=0.36 0.54±0.12
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 0.001 |
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".