Can Measurement of Serum Apolipoprotein B Replace the Lipid Profile Monitoring of Patients with Lipoprotein Disorders?
Bibliographic record
Abstract
BACKGROUND: Current clinical guidelines require that five indices (total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and the total/HDL cholesterol ratio) be measured or calculated to assess the lipid-related risk of vascular disease. All five are also targets of therapy and therefore all must be measured initially and at follow-up. Considerable evidence indicates that apolipoprotein B (apo B) is a better index of reaching or not reaching treatment targets than total or LDL cholesterol. METHODS: The objective of this study was to examine whether measurement of a single marker (apo B) led to the same categorization of risk as the traditional five indices (lipid profile). If both apo B and lipid profile indicated that the patient was either within or outside their respective treatment targets, the indices were considered concordant. If not, the indices were considered discordant. Concordance/discordance was examined in 215 patients at their first and last clinic visit. RESULTS: Concordance was high in both higher (88% at the first and 92% at the last clinic visit) and lower (76% at the first and 78% at the last clinic visit) risk groups at both the initial and final visits. Discordance was virtually restricted to the group with hypertriglyceridemia with normal concentrations of apo B, a group in which little independent evidence points to any substantially increased risk of vascular disease. CONCLUSIONS: These data raise the possibility that at least for high risk patients treated with statins, follow-up could be simplified and expenses reduced if only apo B were measured. They also raise the possibility that outcome might be improved if the therapeutic algorithm were simplified.
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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 | 0.015 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".