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穿支动脉疾病患者病情进展相关因素的分析 被引量:5

Risk factors for progressive perforating artery disease
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摘要 目的探讨穿支动脉疾病患者病情进展的危险因素。方法回顾性分析2008年8月~2014年12月在江苏省苏北人民医院诊治的急性脑梗死患者,根据中国缺血性卒中亚型分型筛选出穿支动脉疾病患者182例,根据入院7d内病情是否加重分为进展组27例和非进展组155例。采用单因素分析和logistic回归分析得出穿支动脉疾病患者病情进展的危险因素,采用ROC曲线分析各因素预测的临界值。结果进展组高血压、梗死灶直径、收缩压、舒张压、白细胞计数、TC、LDL、D-二聚体水平明显高于非进展组,差异有统计学意义(P<0.05,P<0.01)。根据ROC曲线下面积(area under curve,AUC)可见梗死灶直径>10.35mm(AUC=0.711,95%CI:0.606~0.817,P=0.009)和D-二聚体>0.87mg/L(AUC=0.639,95%CI:0.481~0.796,P=0.002)患者易出现病情进展。结论穿支动脉疾病患者梗死灶直径>10.35mm及D-二聚体>0.87mg/L可作为病情进展的预测因素。 Objective To study the risk factors for progressive perforating artery disease(PAD).Methods One hundred and eighty-two AIS patients admitted to our hospital from August 2008 to December 2014 were divided into progressive PAD group(n=27)and non-progressive PAD group(n=155)according to the Chinese ischemic stroke subclassification and according to whether their condition was aggrevated.The risk factors for progressive PAD were analyzed by univariate logistic regression analysis.The cutoff of different risk factors was analyzed according to the ROC curve.Results Univariate logistic regression analysis showed that the incidence of hypertension,systolic blood pressure and diastolic blood pressure,serum levels of TC,LDL and D-dimer were significantly higher,the infarction size was significantly larger,the number of WBC was significantly greater in progressive PAD group than in non-progressive PAD group(P〈0.05,P〈0.01).The area under the ROC curve showed that infarction diameter〉10.35 mm and D-dimer diameter〉0.87mg/L were the risk factors for progressive PAD in AIS patients(AUC=0.711,95%CI:0.606-0.817,P=0.009;AUC=0.639,95%CI:0.481-0.796,P=0.002).ConclusionInfarction diameter〉10.35 mm and D-dimer diameter〉0.87mg/L are the risk factors for progressive PAD in AIS patients.
出处 《中华老年心脑血管病杂志》 CAS 2017年第9期961-964,共4页 Chinese Journal of Geriatric Heart,Brain and Vessel Diseases
基金 国家自然科学基金(81471215)
关键词 脑梗死 白细胞计数 脑动脉疾病 卒中 ROC曲线 brain infarction leukocyte count cerebral arterial diseases stroke ROC curve
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