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Related Concept Videos

Blood Studies for Cardiovascular System III: Serum Lipid Profile01:25

Blood Studies for Cardiovascular System III: Serum Lipid Profile

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Understanding serum lipids is crucial for maintaining cardiovascular health and preventing heart disease and stroke.
Serum lipids are fats and fatty substances in the blood and are crucial for various bodily functions, including energy storage, cellular structure, and hormone production. Serum lipids consist of cholesterol, triglycerides, and phospholipids.
Cholesterol is a soft, fat-like substance found in all body cells. It is crucial for producing hormones, vitamin D, and substances that aid...
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Enrichment of Native Lipoprotein Particles with microRNA and Subsequent Determination of Their Absolute/Relative microRNA Content and Their Cellular Transfer Rate
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Lipemic Plasma Identified Blood Donors: Triglyceride Variability and Exploratory Machine Learning Analysis.

Sirinya Sitthirak1,2, Sodsai Narkpetch3, Rujira Nonsa-Ard4

  • 1Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat 80160, Thailand.

Medical Sciences (Basel, Switzerland)
|March 27, 2026
PubMed
Summary

Blood donors with lipemic plasma frequently show high triglyceride levels, indicating potential for metabolic monitoring. This exploratory study highlights hypertriglyceridemia in this group, suggesting future research opportunities.

Keywords:
blood donorscardiovascular riskdyslipidemiamachine learningtriglycerides

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Area of Science:

  • Cardiovascular disease research
  • Metabolic health monitoring
  • Blood donor screening

Background:

  • Early detection of cardiometabolic issues is key to preventing cardiovascular disease.
  • Habitual blood donors are an underutilized resource for metabolic monitoring.
  • Lipemic plasma in donors may indicate underlying metabolic irregularities.

Purpose of the Study:

  • To investigate metabolic variability in blood donors with lipemic plasma.
  • To assess lipid profiles and cardiovascular risk in this selected subgroup.
  • To explore the potential of donor data for metabolic surveillance.

Main Methods:

  • Lipid profiling and cardiovascular risk assessment were performed on 160 blood donors with lipemic plasma.
  • Multivariable and machine-learning analyses were conducted on 90 donors with complete data.
  • Random Forest classification was used to predict elevated triglyceride levels.

Main Results:

  • Significant triglyceride variability was observed, with higher and more dispersed values in males.
  • Triglycerides correlated with Body Mass Index (BMI) and composite cardiovascular risk metrics.
  • Age was the primary determinant of the 10-year cardiovascular risk score.
  • A Random Forest model achieved an Area Under the Curve (AUC) of 0.86 for predicting elevated triglycerides (exploratory).

Conclusions:

  • Clinically relevant hypertriglyceridemia was common in blood donors with lipemic plasma.
  • Routine donor data may offer avenues for targeted metabolic monitoring.
  • Findings are specific to this subgroup and cannot be generalized; larger studies are needed.