Fibrinogen and plasma clot properties are associated with apolipoprotein B and apolipoprotein B-containing lipoproteins in Africans
Bibliographic record
Abstract
BACKGROUND: Case-control, intervention and laboratory studies have demonstrated a link between apolipoprotein B (ApoB)-containing lipoproteins and clot structure and thrombosis. There is, however, limited evidence on a population level. OBJECTIVES: We determined the cross-sectional relationship between lipoprotein(a) [Lp(a)], low-density lipoprotein cholesterol (LDL-C), and ApoB with fibrinogen and plasma clot properties in 1462 Black South Africans, a population with higher fibrinogen and Lp(a) levels compared with individuals of European descent. METHODS: Data were obtained from participants in the South African arm of the Prospective Urban and Rural Epidemiology study. Clot properties analyzed included lag time, slope, maximum absorbance, and clot lysis time (turbidity). Lp(a) was measured in nM using particle-enhanced immunoturbidimetry. General linear models (GLM) were used to determine the associations between ApoB and ApoB-containing lipoproteins with fibrinogen and plasma clot properties. Stepwise regression was used to determine contributors to clot properties and Lp(a) variance. RESULTS: GLM and regression results combined, indicated fibrinogen concentration and rate of clot formation (slope) had the strongest association with Lp(a); clot density associated positively with both Lp(a) and LDL-C; time to clot formation associated negatively with ApoB; and clot lysis time (CLT) demonstrated strong positive associations with both ApoB and LDL-C, while its association with Lp(a) was fibrinogen concentration dependent. CONCLUSION: These findings suggest that ApoB and the lipoproteins carrying it contribute to prothrombotic clot properties in Africans on an epidemiological level and highlight potential novel prothrombotic roles for these (apo)lipoproteins to be considered for the development of targeted therapeutic approaches to address thrombotic conditions related to clot properties.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".