Correlation between Remnant Cholesterol and the Risk of Ischemic Stroke Recurrence and Its Predictive Value

doi:10.12114/j.issn.1007-9572.2024.0012

Abstract

Abstract:

Background

Serum remnant cholesterol (RC) is associated with the onset of ischemic stroke (IS). However, studies on the correlation between RC levels and recurrent IS are limited, and the predictive value of RC in recurrent IS has not been analyzed.

Objective

To investigate the correlation between serum RC and the recurrence of IS, and to evaluate the predictive value of RC levels in recurrent IS by detecting serum RC levels in patients with IS.

Methods

Patients diagnosed as IS and hospitalized in the First Affiliated Hospital of Nanchang University, the Second Affiliated Hospital of Nanchang University, the Second Hospital of Nanchang, and the Third Hospital of Nanchang from March 2019 to March 2021 were included in the study. Relevant clinical information within 48 hours of admission was collected. All patients were followed up for 12 months to record the cases of recurrent IS. Cox regression and Restricted Cubic Spline (RCS) were performed to identify the correlation between RC levels and recurrent IS. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of RC levels in recurrent IS.

Results

A total of 1 023 eligible patients were included in the study, and 107 (10.46%) of them experienced IS recurrence within 1 year. Multivariable Cox regression analysis showed that high RC was an independent risk factor for recurrent IS (HR=2.709, 95%CI=1.150-6.382; P<0.05). There was a nonlinear positive dose-response relationship between RC levels and the risk of recurrent IS (P-Nonlinear=0.019 3). The area under the curve (AUC) of RC in discriminating 1-year recurrence of IS was 0.687 (95%CI=0.631-0.743), with the optimal cutoff of 0.58 mmol/L. There was a significant difference in the AUC between the combination detection of RC and the Essen Stroke Risk Score (ESRS) versus ESRS alone in discriminating 1-year recurrence of IS (Z=2.356 2, P<0.05) .

Conclusion

High RC is an independent risk factor for recurrent IS, showing a predictive value in the recurrence of IS.

Key words: Ischemic stroke, Remnant cholesterol, Recurrence, Cox proportional hazards regression model, Prognosis

摘要： 背景血清残余胆固醇（RC）与缺血性脑卒中发病相关，然而RC水平与缺血性脑卒中复发的相关性研究较少，且尚少有研究探讨RC在缺血性脑卒中患者脑卒中复发中的预测价值。目的通过检测缺血性脑卒中患者血清RC水平，探讨RC水平与脑卒中复发的相关性及其预测价值。方法纳入2019年3月—2021年3月在南昌大学第一附属医院、南昌大学第二附属医院、南昌市第二医院和南昌市第三医院住院且确诊为缺血性脑卒中的住院患者为研究对象，收集入院后48 h内的相关临床信息，并对其随访12个月，明确脑卒中复发情况。采用Cox比例风险回归模型及限制性立方样条（RCS）分析RC水平与缺血性脑卒中复发的相关性。通过受试者工作特征（ROC）曲线分析RC水平对缺血性脑卒中复发的预测价值。结果研究共纳入1 023例患者，其中107例（10.46%）缺血性脑卒中患者1年内复发。多因素Cox比例风险回归模型分析结果显示，高RC水平是缺血性脑卒中复发的独立危险因素（HR=2.709，95%CI=1.150~6.382，P<0.05）。RC水平与缺血性脑卒中患者复发风险存在非线性的正性剂量-反应关系（P-Nonlinear=0.019 3）。RC预测缺血性脑卒中患者1年内复发的ROC曲线下面积为0.687（95%CI=0.631~0.743），最佳截断值为0.58 mmol/L。RC联合Essen卒中风险评分量表（ESRS）与单独ESRS预测缺血性脑卒中患者1年内复发的ROC曲线下面积比较，差异有统计学意义（Z=2.356 2，P<0.05）。结论高RC水平是缺血性脑卒中患者复发的独立危险因素，并对于缺血性脑卒中复发具有一定的预测价值。

关键词: 缺血性脑卒中, 残余胆固醇, 复发, Cox比例风险回归模型, 预后

CLC Number:

R 743.3

LIU Xingyu,DU Huijie,MO Jiali, et al. Correlation between Remnant Cholesterol and the Risk of Ischemic Stroke Recurrence and Its Predictive Value[J]. Chinese General Practice, 2024, 27(26): 3227-3231. DOI: 10.12114/j.issn.1007-9572.2024.0012.
刘星雨,杜慧杰,莫佳丽等. 残余胆固醇水平与缺血性脑卒中复发风险的关联性及其预测价值研究[J]. 中国全科医学, 2024, 27(26): 3227-3231. DOI: 10.12114/j.issn.1007-9572.2024.0012.

Figures/Tables 5

References 22

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变量	B	SE	Wald χ²值	P值	HR（95%CI）
年龄	0.019	0.009	4.776	0.029	1.019（1.000~1.038）
既往卒中	0.481	0.202	5.001	0.025	1.618（1.089~2.403）
生化检测指标
CRP	0.013	0.003	15.415	<0.001	1.013（1.007~1.018）
UC	0.004	0.001	6.481	0.011	1.004（1.002~1.006）
HCY	-0.002	0.011	0.081	0.775	0.998（0.976~1.021）
TC	0.245	0.068	7.592	0.006	1.277（1.118~1.459）
TG	0.096	0.106	1.462	0.227	1.101（0.894~1.356）
HDL-C	-0.400	0.317	3.764	0.052	0.775（0.608~0.989）
LDL-C	-0.496	0.333	2.488	0.115	0.609（0.317~1.169）
ApoA	-1.389	0.559	4.833	0.028	0.249（0.083~0.746）
ApoB	-0.996	0.408	15.895	<0.001	0.369（0.166~0.822）
ApoE	-0.002	0.005	0.074	0.786	0.998（0.988~1.009）
Lp（a）	-0.001	0.001	1.125	0.289	0.999（0.997~1.001）
non HDL-C	0.538	0.170	12.201	<0.001	1.713（1.227~2.392）
RC	0.773	0.180	34.343	<0.001	2.166（1.522~3.081）

变量	B	SE	Wald χ²值	P值	HR（95%CI）
年龄	0.019	0.009	4.776	0.029	1.019（1.000~1.038）
既往卒中	0.481	0.202	5.001	0.025	1.618（1.089~2.403）
生化检测指标
CRP	0.013	0.003	15.415	<0.001	1.013（1.007~1.018）
UC	0.004	0.001	6.481	0.011	1.004（1.002~1.006）
HCY	-0.002	0.011	0.081	0.775	0.998（0.976~1.021）
TC	0.245	0.068	7.592	0.006	1.277（1.118~1.459）
TG	0.096	0.106	1.462	0.227	1.101（0.894~1.356）
HDL-C	-0.400	0.317	3.764	0.052	0.775（0.608~0.989）
LDL-C	-0.496	0.333	2.488	0.115	0.609（0.317~1.169）
ApoA	-1.389	0.559	4.833	0.028	0.249（0.083~0.746）
ApoB	-0.996	0.408	15.895	<0.001	0.369（0.166~0.822）
ApoE	-0.002	0.005	0.074	0.786	0.998（0.988~1.009）
Lp（a）	-0.001	0.001	1.125	0.289	0.999（0.997~1.001）
non HDL-C	0.538	0.170	12.201	<0.001	1.713（1.227~2.392）
RC	0.773	0.180	34.343	<0.001	2.166（1.522~3.081）

模型	β	SE	Wald χ²值	P值	HR值	95%CI
模型1	0.899	0.153	34.343	<0.001	2.457	1.819~3.320
模型2	1.061	0.164	42.062	<0.001	2.888	2.096~3.980
模型3	1.031	0.170	36.593	<0.001	2.804	2.008~3.916
模型4	0.996	0.437	5.194	0.023	2.709	1.150~6.382

模型	β	SE	Wald χ²值	P值	HR值	95%CI
模型1	0.899	0.153	34.343	<0.001	2.457	1.819~3.320
模型2	1.061	0.164	42.062	<0.001	2.888	2.096~3.980
模型3	1.031	0.170	36.593	<0.001	2.804	2.008~3.916
模型4	0.996	0.437	5.194	0.023	2.709	1.150~6.382

变量	AUC	95%CI	P值	灵敏度	特异度
单独ESRS	0.571	0.540~0.602	0.035	0.500	0.563
RC联合ESRS	0.610	0.579~0.640	0.001	0.375	0.794