Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol and apolipoprotein B for cardiovascular care
Bibliographic record
Abstract
PURPOSE OF REVIEW: Some experts and consensus groups continue to argue that apolipoprotein B (apoB) should not be introduced broadly into clinical care. But, too often, the present approach to clinical care is not succeeding. An important reason for this failure, we believe, is that the conventional approach limits what the expert clinician can accomplish and is too complex, confusing, and contradictory for primary care physicians to apply effectively in their practise. RECENT FINDINGS: There are four major reasons that apoB should be measured routinely in clinical care. First, apoB is a more accurate marker of cardiovascular risk than LDL-C or non-HDL-C. Second, the measurement of apoB is standardized whereas the measurements of LDL-C and non-HDL-C are not. Third, with apoB and a conventional lipid panel, all the lipid phenotypes can be simply and accurately distinguished. This will improve the care of the expert. Fourth, apoB, as the single measure to evaluate the success of therapy, would simplify the process of care for primary care physicians. SUMMARY: By introducing apoB broadly into clinical care, the process of care will be improved for both the expert and the primary care physician, and this will improve the outcomes of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".