Usefulness of the 1998 American academy of pediatrics recommendations to screen children and adolescents for raised blood low density lipoprotein-cholesterol levels
Bibliographic record
Abstract
The American Academy of Pediatrics recommends that children and adolescents with a family history of premature cardiovascular disease (CVD) and/or parental total cholesterol (TC) ≥6.2 mmol/L be screened for hypercholesterolemia. Questionnaires (from children and parents), clinical and blood sample data were collected in a provincially representative sample of 9-, 13-, and 16-year-olds (n = 2217) in Quebec to evaluate the usefulness of parental history (PH) of CVD and/or parental hypercholesterolemia to screen youth for raised low density lipoprotein cholesterol (LDL-C). Mean bias assessed by an external laboratory gold standard ranged from 1.0% to 2.1%, -0.4% to 5.1%, and -1.4% to 0.1% according to TC, triglyceride, and high density lipoprotein cholesterol tertiles. LDL-C was calculated using the Friedewald equation. Positive PH was defined as one/both biological parents diagnosed with a high cholesterol level, and/or taking cholesterol-lowering medication, and/or ever having had a heart attack, angina, stroke, cerebral vascular disease, peripheral vascular disease, and/or taking medication 'for the heart'. Performance statistics were calculated to determine the usefulness of PH in predicting borderline/high LDL-C (LDL-C ≥2.8 mmol/L) and high LDL-C (LDL-C ≥3.4 mmo1/L). 18.3% and 4.8% of subjects had borderline/high LDL-C and high LDL-C; positive predictive value (PPV) was 23.7% and 7.7%, respectively. Therefore PPVs were only marginally higher than the corresponding population prevalences and likelihood ratios were respectively 1.38 and 1.63: close to 1.00. In conclusion, PH offers little improvement over random screening.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".