Bibliographic record
Abstract
Childhood HTN (hypertension) has become a widely investigated topic within the last decade due to its increasing prevalence. In the present review, we examine new developments and trends that have significantly contributed to aetiology, diagnosis, evaluation and management of childhood HTN. Many recent reports document an increasing prevalence of HTN, mainly essential HTN, in children worldwide. This is probably related to the increase of childhood obesity, although obesity is not the only factor. Evidence has been accumulating to suggest a rather complex interplay between obesity, uric acid level, dietary sodium intake, inflammation, inheritance and other factors, which lead to increased risk of developing HTN in childhood and adulthood. The detection and monitoring of HTN has significantly improved with the use of ABPM (ambulatory blood pressure monitoring), which allows not only for a more accurate classification and staging of HTN, but also for the calculation of more sophisticated parameters such as the AASI (ambulatory arterial stiffness index). Measurement of arterial stiffness enables assessment of arterial dysfunction, which may precede structural vascular changes evaluated by carotid intima media thickness. Sustained HTN eventually leads to end-organ damage [LVH (left ventricular hypertrophy), central nervous system], which in turn increases the risk of cardiovascular morbidity and mortality. New developments in childhood HTN, as outlined in the present review, will hopefully contribute to better screening and management of HTN in children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".