Evaluation of fat mass and its correlation with abnormal blood pressure in children and adolescents
Bibliographic record
Abstract
E -Manuscript Preparation, F -literature search, G -funds collectionBackground. the problem of developmental obesity is growing in most countries of the world, reaching an epidemic.excessive body weight in childhood results in a greater likelihood of obesity in adulthood, as well as causing endocrine, orthopedic, cardiological and psychogenic disorders.overweight and obesity appear to be the most important causative factor.Objectives. the aim of the study was to estimate the usefulness of body composition analysis in predicting high blood pressure among children and adolescents and the correlation between the parameters of body mass and blood pressure (BP).Material and methods.children from the age of 8 to 15 with recurrent respiratory tract diseases were selected during a rehabilitation and wellness stay in crr Krus in szklarska Poreba.Body composition analysis was performed using the tanita Mc-780Ma analyzer, and blood pressure was measured with a dial gauge.the study was conducted between 2015 and 2016, creating a database of 325 results sets.Results.statistically significant correlations between systolic blood pressure, diastolic blood pressure, body weight and fat mass content were shown (p < 0.001).BMI and body fat content correlations were also statistically significant (p < 0.001). Conclusions.there is a problem of under-diagnosis of hypertension in the pediatric population.obesity and overweight are connected with abnormal BP and hypertension.the total content of fat mass correlates with abnormal BP and hypertension.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".