DETERMINANTS OF PRIMARY HYPERTENSION IN CHILDREN AND ADOLESCENTS
Bibliographic record
Abstract
Objective: The aim of our study was to assess determinants of primary hypertension (PH) in patients diagnosed with hypertension (HT) based on office blood pressure (BP) measurements and hospitalized in 2012–2022 at the Department of Nephrology, Kidney Transplantation and Hypertension of the Children’s Memorial Health Institute in Warsaw, Poland. Design and method: A retrospective analysis of 2,008 children aged 0–18 years (mean age: 12.3 ± 4.9 years) diagnosed with HT based on office BP was conducted. Patients were categorized into white coat hypertension (WCH), primary hypertension (PH), or secondary hypertension (SH) groups using office (BP) measurements, 24-hour ambulatory BP monitoring (ABPM), and comprehensive clinical evaluation. Anthropometric, hemodynamic, and biochemical data were analyzed to identify the determinants of PH. Results: HT was confirmed in 1,452 cases (556 identified as having WCH). Of the 1,452 patients with confirmed HT, 42.8% were diagnosed with PH, while 57.2% had SH. PH emerged as the leading cause of HT after 13 years of age, comprising 59.1% of confirmed HT cases in patients aged 13–18 years. Significant anthropometric, hemodynamic, and biochemical differences were observed between PH and SH patients. Notably, all anthropometric parameters were higher in the PH group, particularly those linked to overweight, obesity, and metabolic syndrome risk. Multivariate regression analysis identified age > 12.5 years, obesity (BMI-SDS greater than or equal 1.65), and serum uric acid > 4.8 mg/dL as significant determinants of PH in all patients and also after exclusion of patients with impaired kidney function (GFR < 90 mL/min/1.73m2) and kidney transplant patients.Conclusions: Our study, encompassing the largest European cohort of children with HT described in recent years, provides detailed insights into pediatric hypertension etiology and trends. We confirmed the importance of anthropometric assessment in diagnosing PH and showed, based on multivariate regression analysis, that serum uric acid is strongly associated with PH in children and adolescents.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".