Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis

Jiahuan Guo1,2,3, Anxin Wang1,2,3, Yu Wang1,2,3

  • 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Frontiers in Neurology
|September 17, 2021
PubMed

Insights

Non-traditional lipid parameters like non-HDL-C and atherogenic indices are significant predictors of asymptomatic intracranial arterial stenosis (aICAS). These findings highlight their potential role in stroke risk assessment and prevention strategies.

Area of Science:

  • Cardiology
  • Neurology
  • Clinical Lipidology

Background:

  • Intracranial arterial stenosis (ICAS) is a major risk factor for stroke.
  • Identifying easily measurable predictors for ICAS is crucial for clinical practice.
  • Non-traditional lipid parameters may offer greater predictive value than traditional ones for ICAS.

Purpose of the Study:

  • To investigate the association between non-traditional lipid parameters and asymptomatic ICAS (aICAS).
  • To evaluate the predictive value of parameters such as non-HDL-C, TG/HDL-C ratio, AC, AIP, and CRI for aICAS.

Main Methods:

  • A cohort of 5,314 participants from the Asymptomatic Polyvascular Abnormalities in Community study was analyzed.
  • Asymptomatic ICAS was diagnosed using transcranial Doppler ultrasonography (TCD).
  • Multivariable logistic analysis was employed to assess the association between lipid parameters and aICAS, with trend and subgroup analyses conducted.

Main Results:

  • 695 participants were diagnosed with aICAS.
  • Higher levels of non-HDL-C, Atherogenic Coefficient (AC), Castelli's Risk Index I (CRI-I), and CRI-II were significantly associated with increased prevalence of aICAS.
  • Significant interactions were observed between AC, CRI-I, and diabetes in subgroup analyses.

Conclusions:

  • Non-HDL-C, AC, CRI-I, and CRI-II are significantly associated with a higher prevalence of asymptomatic ICAS.
  • These non-traditional lipid parameters demonstrate potential as valuable biomarkers for stroke risk assessment.
  • Further research may elucidate the clinical utility of these parameters in managing patients at risk for ICAS.

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