Plasma Clot Lysis Time and Its Association with Cardiovascular Risk Factors in Black Africans
Bibliographic record
Abstract
Studies in populations of European descent show longer plasma clot lysis times (CLT) in patients with cardiovascular disease (CVD) than in controls. No data are available on the association between CVD risk factors and fibrinolytic potential in black Africans, a group undergoing rapid urbanisation with increased CVD prevalence. We investigated associations between known CVD risk factors and CLT in black Africans and whether CLTs differ between rural and urban participants in light of differences in CVD risk.Data from 1000 rural and 1000 urban apparently healthy black South Africans (35-60 years) were cross-sectionally analysed.Increased PAI-1(act), BMI, HbA1c, triglycerides, the metabolic syndrome, fibrinogen concentration, CRP, female sex and positive HIV status were associated with increased CLTs, while habitual alcohol consumption associated with decreased CLT. No differences in CLT were found between age and smoking categories, contraceptive use or hyper- and normotensive participants. Urban women had longer CLT than rural women while no differences were observed for men.CLT was associated with many known CVD risk factors in black Africans. Differences were however observed, compared to data from populations of European descent available in the literature, suggesting possible ethnic differences. The effect of urbanisation on CLT is influenced by traditional CVD risk factors and their prevalence in urban and rural communities.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".