Abstract 9716: Who Needs a Statin? Impact of the New Expert Panel Guidelines for Screening and Management of Dyslipidemia in Children and Adolescents
Bibliographic record
Abstract
Introduction: Recent Expert Panel guidelines commissioned by the National Heart, Lung and Blood Institute recommended universal and targeted lipid screening for children and adolescents, together with specification of lipid cutpoints and additional risk factors used in decision-making regarding initiation of lipid-lowering drug therapy. Given the current epidemic of childhood obesity and associated dyslipidemia, we sought to determine the potential impact of these guidelines on the estimated proportion of adolescents would potentially screen positive and be recommended for medication. Methods: We examined serial cross-sectional assessments using National Health and Nutrition Examination Survey data (1999-2010) of US children ages 12 to 17 years. The weighted proportion of participants meeting guideline screening and management lipid and risk factor cutpoints was determined, and compared to that obtained by applying previous guidelines. Results: Based only on non-fasting lipid measurement, 24.7% of screened individuals would have dyslipidemia (non-HDL >145 mg/dL + HDL <40 mg/dL) and require further evaluation. Using fasting assessment, 20.3% would screen positive, with 6.6% having high LDL (>130 mg/dL). Of those with fasting assessment, 17.2% were obese, 9.2% smoked, and 2.7% had hypertension. Assuming no improvement with lifestyle therapy and incorporating additional risk factors in decision-making, 0.85% (215,900 US children) might be recommended for statin therapy based on the new guidelines. For severely obese children with BMI > 97 th %ile, 3.1% might be recommended for statin therapy. Applying previous guidelines, 0.50% would meet National Cholesterol Education Program 1992 criteria and 1.00% would meet American Academy of Pediatrics 2008 criteria for medication. Conclusions: Despite the recommendation for universal screening and greater specification regarding risk factors, only a small proportion of adolescents will be recommended for drug therapy with the new guidelines, appropriately targeting those with clustering of risk factors commonly associated with severe obesity, as well as those with familial dyslipidemias.
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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 | 0.026 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".