Apo-B/AI ratio identifies cardiovascular risk in childhood:The Australian Aboriginal Birth Cohort study
Bibliographic record
Abstract
We describe the lipoprotein and apolipoprotein profiles and their relationship to cardiovascular risk factors in Australian Aboriginal children. This cross-sectional study within a longitudinal birth cohort study involved Australian Aboriginal children born between 1987 and 1990 and re-examined between 1998 and 2001. Height, weight, blood pressure, waist circumference, body fat percentage, cholesterol, triglycerides, HDL-c, LDL-c, apolipoprotein B and A1 were measured. Mean age was 11.4 years (52% male). Mean cholesterol, triglyceride, HDL-c and LDL-c did not differ from reference data. Measures of obesity, blood pressure and prevalence of the metabolic syndrome did not differ in those children with lipoproteins in the upper quartile of the cohort (lower quartile for HDL-c). Boys with an Apo-B/A1 ratio in the upper quartile of the cohort had higher BMI z-score, waist z-score, % body fat, diastolic blood pressure and frequency of the metabolic syndrome (p<0.05). In girls, waist circumference, % body fat and the prevalence of the metabolic syndrome was higher in those with an Apo-B/A1 ratio in the upper quartile (p<0.05).The Apo-B/A1 ratio may be useful to identify cardiovascular risk in Australian Aboriginal children and is suited to clinical practice as the assays are standardised, accurate, automated and a fasting sample is not required.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".