Accelerated vascular age in adolescents with primary hypertension
Bibliographic record
Abstract
BACKGROUND: Primary hypertension may lead to early vascular ageing. We aimed to evaluate differences between expected vascular age based on pulse wave velocity (PWV)/carotid intima-media thickness (cIMT) and actual chronological age (CHA) in adolescents with primary hypertension. METHODS: Three hundred and fifty-two children (median age of 15.5 years) with office hypertension and 64 normotensive healthy children of the same age underwent anthropometry, office and ambulatory blood pressure (BP), left ventricular mass index, cIMT, PWV, pulse wave analysis and biochemistry measurements. Vascular age was calculated using pooled pediatric and adult normative PWV and cIMT data. The difference between vascular age and CHA was calculated in relation to the 90th percentile for PWV (PWVAgeDiff90) and the 95th percentile for cIMT (cIMTAgeDiff95). RESULTS: One hundred and sixty-six patients had white-coat hypertension (WCH), 32 had ambulatory prehypertension (AmbPreHT), 55 had isolated systolic hypertension with normal central SBP (ISH+cSBPn), 99 had elevated office, ambulatory and cSBP (true hypertension, tHT). The differences between vascular age (both PWV and cIMT based) and CHA were significantly higher in AmbPreHT and tHT compared with normotension, WCH and ISH+cSBPn. Median PWVAgeDidff90 was -3.2, -1.2, -2.1, +0.8 and +0.3 years in normotension, WCH, ISH+cSBPn, AmbPreHT and tHT, respectively. Median cIMTAgeDiff95 was -8.0, -6.3, -6.8, -3.8 and -4.3 years in normotension, WCH, ISH+cSBPn, AmbPreHT and tHT, respectively. Significant predictors of PWVAge90Diff were the DBP and serum cholesterol, whereas cSBP and augmentation index were significant predictors of cIMTAgeDiff95. CONCLUSION: Children with AmbPreHT and tHT show accelerated vascular age compared with their normotensive peers.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".