Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis
Background: Intracranial arterial stenosis (ICAS) is a common cause of stroke. Identifying effective predictors of ICAS that could be easily obtained in clinical practice is important. The predictive values of serum individual lipid parameters have been well-established. In recent years, several non...
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Frontiers Media S.A.
2021-08-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2021.679415/full |
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| author | Jiahuan Guo Jiahuan Guo Jiahuan Guo Anxin Wang Anxin Wang Anxin Wang Yu Wang Yu Wang Yu Wang Xinmin Liu Xinmin Liu Xinmin Liu Xiaoli Zhang Xiaoli Zhang Shouling Wu Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao |
| author_facet | Jiahuan Guo Jiahuan Guo Jiahuan Guo Anxin Wang Anxin Wang Anxin Wang Yu Wang Yu Wang Yu Wang Xinmin Liu Xinmin Liu Xinmin Liu Xiaoli Zhang Xiaoli Zhang Shouling Wu Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao |
| author_sort | Jiahuan Guo |
| collection | DOAJ |
| description | Background: Intracranial arterial stenosis (ICAS) is a common cause of stroke. Identifying effective predictors of ICAS that could be easily obtained in clinical practice is important. The predictive values of serum individual lipid parameters have been well-established. In recent years, several non-traditional lipid parameters demonstrated greater predictive values for cardiovascular disease and ischemic stroke than traditional individual lipid parameters. However, their effects on asymptomatic ICAS (aICAS) are less clear. Therefore, we sought to observe the effects of non-traditional lipid parameters on aICAS.Methods: We enrolled 5,314 participants from the Asymptomatic Polyvascular Abnormalities in Community study. Asymptomatic ICAS was detected by transcranial Doppler ultrasonography (TCD). Non-traditional lipid parameters, including non-high-density lipoprotein cholesterol (non-HDL-C), the triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-C), atherogenic coefficient (AC), atherogenic index of plasma, and Castelli's risk index (CRI) were measured. We used multivariable logistic analysis to assess the association of different lipid parameters with aICAS; a trend test and subgroup analyses were also performed.Results: In total, 695 of 5,314 participants had aICAS in this study. For the comparison of the highest to the lowest tertile, the multivariable-adjusted odds ratios (ORs) (95% CIs) were 1.78 (1.39–2.27) (p trend < 0.001) for non-HDL-C, 1.48 (1.18–1.85) (p trend = 0.004) for the AC, 1.48 (1.18–1.85) (p trend = 0.004) for CRI-I, and 1.34 (1.09–1.66) (p trend = 0.032) for CRI-II. Subgroup analyses showed significant interactions between the AC, CRI-I, and diabetes.Conclusions: This large community-based study showed that non-HDL-C, AC, CRI-I, and CRI-II were significantly associated with increased prevalence of aICAS. |
| first_indexed | 2024-12-17T22:41:14Z |
| format | Article |
| id | doaj.art-d909b49a60bb48759d9d340048a2e909 |
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| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-12-17T22:41:14Z |
| publishDate | 2021-08-01 |
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| series | Frontiers in Neurology |
| spelling | doaj.art-d909b49a60bb48759d9d340048a2e9092022-12-21T21:29:56ZengFrontiers Media S.A.Frontiers in Neurology1664-22952021-08-011210.3389/fneur.2021.679415679415Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial StenosisJiahuan Guo0Jiahuan Guo1Jiahuan Guo2Anxin Wang3Anxin Wang4Anxin Wang5Yu Wang6Yu Wang7Yu Wang8Xinmin Liu9Xinmin Liu10Xinmin Liu11Xiaoli Zhang12Xiaoli Zhang13Shouling Wu14Xingquan Zhao15Xingquan Zhao16Xingquan Zhao17Xingquan Zhao18Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaResearch Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, ChinaCenter of Stroke, Beijing Institute for Brain Disorders, Beijing, ChinaBackground: Intracranial arterial stenosis (ICAS) is a common cause of stroke. Identifying effective predictors of ICAS that could be easily obtained in clinical practice is important. The predictive values of serum individual lipid parameters have been well-established. In recent years, several non-traditional lipid parameters demonstrated greater predictive values for cardiovascular disease and ischemic stroke than traditional individual lipid parameters. However, their effects on asymptomatic ICAS (aICAS) are less clear. Therefore, we sought to observe the effects of non-traditional lipid parameters on aICAS.Methods: We enrolled 5,314 participants from the Asymptomatic Polyvascular Abnormalities in Community study. Asymptomatic ICAS was detected by transcranial Doppler ultrasonography (TCD). Non-traditional lipid parameters, including non-high-density lipoprotein cholesterol (non-HDL-C), the triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-C), atherogenic coefficient (AC), atherogenic index of plasma, and Castelli's risk index (CRI) were measured. We used multivariable logistic analysis to assess the association of different lipid parameters with aICAS; a trend test and subgroup analyses were also performed.Results: In total, 695 of 5,314 participants had aICAS in this study. For the comparison of the highest to the lowest tertile, the multivariable-adjusted odds ratios (ORs) (95% CIs) were 1.78 (1.39–2.27) (p trend < 0.001) for non-HDL-C, 1.48 (1.18–1.85) (p trend = 0.004) for the AC, 1.48 (1.18–1.85) (p trend = 0.004) for CRI-I, and 1.34 (1.09–1.66) (p trend = 0.032) for CRI-II. Subgroup analyses showed significant interactions between the AC, CRI-I, and diabetes.Conclusions: This large community-based study showed that non-HDL-C, AC, CRI-I, and CRI-II were significantly associated with increased prevalence of aICAS.https://www.frontiersin.org/articles/10.3389/fneur.2021.679415/fullasymptomatic intracranial atherosclerosislipid parameterspredictorepidemiologyprevalence |
| spellingShingle | Jiahuan Guo Jiahuan Guo Jiahuan Guo Anxin Wang Anxin Wang Anxin Wang Yu Wang Yu Wang Yu Wang Xinmin Liu Xinmin Liu Xinmin Liu Xiaoli Zhang Xiaoli Zhang Shouling Wu Xingquan Zhao Xingquan Zhao Xingquan Zhao Xingquan Zhao Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis Frontiers in Neurology asymptomatic intracranial atherosclerosis lipid parameters predictor epidemiology prevalence |
| title | Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis |
| title_full | Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis |
| title_fullStr | Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis |
| title_full_unstemmed | Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis |
| title_short | Non-traditional Lipid Parameters as Potential Predictors of Asymptomatic Intracranial Arterial Stenosis |
| title_sort | non traditional lipid parameters as potential predictors of asymptomatic intracranial arterial stenosis |
| topic | asymptomatic intracranial atherosclerosis lipid parameters predictor epidemiology prevalence |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2021.679415/full |
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