Prevalence of hypercholesterolaemia in outpatient children aged 9–11 years
Bibliographic record
Abstract
Background: Hypercholesterolaemia is a silent disease that is considered to be one of the main risk factors for cardiovascular disease, often beginning in childhood, and early diagnosis and management may reduce the risk of developing atherosclerosis and early cardiovascular disease in early adulthood. Objectives: The purpose of this study was to evaluate the importance of universal screening for dyslipidemia in children aged 9–11 years. Methods: An observational, descriptive, cross-sectional study was conducted from July 2021 to June 2022. A total of 532 children (279 girls and 253 boys) aged 9–11 years were enroled, and non-fasting blood samples were obtained to measure total cholesterol (TC) levels in the blood. Results: The mean serum TC was 136.4±28.1 mg/dl. Thirty-two children (6%) of the screened participants had abnormal TC levels; those were tested subsequently by fasting serum TC, and 19 children were confirmed as dyslipidemic (3.5%). The prevalence of borderline blood cholesterol levels (TC between 170 and 199 mg/dl) was 2.6% CI 95% (2.2–3.2), and the prevalence of hypercholesterolaemia (TC ≥200 mg/dl) was 0.9% CI 95% (0.5–1.4). A positive correlation was found between body mass index and blood cholesterol level. (r = 0.55, P =0.002). Conclusions: Universal non-fasting TC screening in children aged 9–11 years old is effective in detecting hypercholesterolaemia. Since the authors found that the positive family history as the sole basis for selective examination in children is insufficient.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".