Detection of lipoprotein(a)- cholesterol expression in Bangladeshi adults with dyslipidemia
Bibliographic record
Abstract
<p><span>Lipoprotein(a)-cholesterol (Lp(a)-C)</span><span lang="EN-GB">, a low-density lipoprotein (LDL)-like particle is considered as a risk factor for cardiovascular diseases (CVDs). <br /> We aimed to investigate the association of Lp(a)-C expression with dyslipidemia among the Bangladeshi population and assess the relationship with cardiovascular risks. </span><span>In this cross-sectional comparative study, a total of 180 urban males and females between ages 19-65 years were included who were enrolled in a hospital setting of Bangladesh. Participants were selected based on their total c</span><span>holesterol (TC) level≥200 mg/dl, high density lipoprotein (HDL)-C&lt;40 mg/dl, LDL-C≥140 mg/dl, and triacylglycerol (TG)≥150 mg/dl regardless of race, religion and socioeconomic status. Venous blood was collected from all participants and analyzed. <br /> Further, participants’ socio-demographics and body mass index (BMI) were collected. Expression of Lp(a)-C was detected in 22.86% patients with desirable levels (&lt;14 mg/dL) of serum Lp(a)-C. This study suggests that the prevalence of hyperlipidemia and hypertriglyceridemia is high in the Bangladeshi population. Males were found to have lower HDL-C and higher TG than females. and, similar to other ethnic groups, a negative correlation between BMI and HDL-C was found in this population. In addition, Lp(a)-C had a positive correlation with TG which may recommend routine clinical investigation of Lp(a)-C as a biomarker for CVD risk.</span></p>
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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 | 0.007 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".