Advanced serum lipoprotein and glycoprotein profiling for cardiovascular event prediction in type 2 diabetes mellitus: the LIPOCAT study
Authors' conclusion
Advanced 1H-NMR analysis revealed previously hidden lipoprotein and glycoprotein characteristics associated with CVE in T2D subjects.
Study context
- Population
- Subjects with T2D from four Spanish prospective cohorts104 with cardiovascular events (CVE)
- Participants
- 933 subjects
- Exposure
- Advanced lipoprotein/glycoprotein variables added to traditional risk factor model vs traditional model
- Outcome
- Prediction of future CVE by advanced lipoprotein characteristics and glycoproteins
- Follow-up
- follow-up
Methodological detailsmulticohort (four Spanish prospective cohorts), external validation cohort
- Multicohort (four Spanish prospective cohorts)
- External validation cohort
Main finding
As reported in the abstract
CVE prediction (AUROC)
Adding advanced Liposcale® variables to traditional risk factor base model significantly improved CVE prediction: increase in C statistic (Area Under the Receiver Operating Characteristics (AUROC))
1.5-fold
AUROC reached
0.756
Observational data: associations, not effects.
Further findings
External validation cohort
- Similar AUROC improvements by adding advanced variables to traditional models
Original publication
Advanced serum lipoprotein and glycoprotein profiling for cardiovascular event prediction in type 2 diabetes mellitus: the LIPOCAT study. Cardiovasc Diabetol. Published 21 February 2025. doi:10.
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