Elevated blood pressure is not equal to hypertension
Bibliographic record
Abstract
In a recent issue of blood pressure monitoring, Maric et al. reported the results of an interesting study in which blood pressure was measured in 780 children between 7 and 17 years of age in two schools of the district of Vozdovac of Belgrade, Serbia. The authors reported a prevalence of elevated blood pressure of 10.5% and concluded that there was a high prevalence of hypertension in (this) sample of schoolchildren'. In this commentary, we would like to stress the importance of distinguishing elevated blood pressure from hypertension. Hypertension is a state of sustained elevated blood pressure. This means that blood pressure must be elevated on repeated occasions for the diagnosis of hypertension Individuals with high blood pressure at one visit, however, generally have lower blood pressure levels at subsequent visits because of familiarization with the measurement procedure and a regression to the mean effect. Therefore, if blood pressure is high at an initial visit, it is necessary to measure blood pressure at other visits to confirm or exclude hypertension. According to the guidelines of the National High Blood Pressure Education Program Working Group on Children and Adolescents, elevated blood pressure must be confirmed on at least three visits before characterizing a child as having hypertension'. It is also recommended to have blood pressure measured at more than one visit for the diagnosis of hypertension in adults.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".