Dietary Management of Children and Adolescents with High Blood Pressure
Bibliographic record
Abstract
Abstract Hypertension (systolic blood pressure [SBP] >140 mmHg or diastolic blood pressure [DBP] >90 mmHg) is a major risk factor for cardiovascular disease and is estimated to affect over 60 million adults at a cost of 14 billion dollars annually (Gillman and Ellison, 1993; Fernandes and McCrindle, 2000). Pre-hypertension (SBP of 120-139 mmHg or DBP of80-89 mmHg) is estimated to affect another 45 million individuals and is strongly associated with development of hypertension with increasing age (Chobanian et al., 2003). Although hypertension in childhood is typically secondary to some other pathological condition, growing evidence from landmark studies including the Muscatine, Bogalusa, and Cardiovascular Risk in Young Finns studies confirms that blood pressure in youth tracks into adulthood (Webber et al., 1983; Lauer et al., 1984; Lauer and Clarke, 1989; Raitakari et al., 1994; Muntner et al., 2004). This phenomenon may be even more pronounced in certain ethnic groups (Rosner et al., 2000). For example, the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) research group reported that, based on autopsy studies, more extensive raised lesions were found in blacks than in whites with hypertension (McGill et al., 2000; also see Chapter 1). Concerns about these associations are further magnified by evidence of increased levels of blood pressure in children and adolescents, ages 8 to 17 years, from the National Health and Nutrition Examination Survey (NHANES) conducted in 1988-94 and 1999-2000 (Muntner et al., 2004).
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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 | 0.001 | 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) | 0.002 | 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".