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中国临床研究:2022,35(4):456-461
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急性缺血性脑卒中早期预后不良的危险因素分析及预测模型构建
(哈尔滨医科大学附属第一医院重症医学科,黑龙江 哈尔滨 150000)
Risk factors analysis and predictive model construction of poor early prognosis in acute ischemic stroke
(Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, China)
摘要
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投稿时间:2021-09-16   网络发布日期:2022-04-20
中文摘要: 目的 探讨急性缺血性脑卒中(AIS)患者早期预后不良的危险因素,并进一步构建风险预测模型。 方法 回顾性分析2016年8月至2020年12月哈尔滨医科大学附属第一医院诊治的727例AIS患者的临床资料。入院后3个月时,采用改良RANKIN量表(mRS)评估患者早期预后,727例患者分为预后良好组(mRS评分0~2分)508例和预后不良组(mRS评分3~6分)219例。多因素Logistic回归分析AIS患者预后不良的影响因素,构建风险预测模型,并采用ROC曲线分析对模型进行验证。 结果 单因素分析显示,预后不良组年龄>60岁、合并糖尿病史比例、入院时美国国立卫生研究院卒中量表(NIHSS)评分、血肌酐(SCr)、红细胞沉降率(ESR)、三酰甘油(TC)水平、红细胞分布宽度与血小板计数比值(RPR)和降钙素原(PCT)高于预后良好组,尿酸(UA)、25-羟基维生素D[25(OH)D]、血管生成素-1(Ang-1)低于预后良好组(P<0.05,P<0.01)。多因素Logistic回归分析显示,NIHSS>13分、RPR>0.065是AIS患者预后不良风险的独立影响因素(OR=2.56、1.63,P<0.01);UA>295.37 μmol/L、25(OH)D>20.00 ng/ml、Ang-1>3.26 ng/ml是降低其风险的独立影响因素(OR=0.76、0.66、0.57,P<0.05,P<0.01)。ROC曲线显示,风险模型预测AIS患者预后不良的AUC为0.884(95%CI:0.783~0.984, P<0.01),准确率85.00%,敏感度87.67%,特异度83.86%,临界值0.768。 结论 入院时NIHSS、RPR升高增加AIS患者早期预后不良的风险,UA、25(OH)D、Ang-1升高降低该风险。据此构建的风险预测模型可较好预测AIS早期预后不良的发生风险。
Abstract:b>Objective To explore the risk factors of poor prognosis in early-stage of patients with acute ischemic stroke (AIS) and to construct a risk prediction model. Methods A retrospective analysis was performed on the clinical data of 727 AIS patients treated in the First Affiliated Hospital of Harbin Medical University from August 2016 to December 2020. At 3 months after admission, the modified RANKIN scale (mRS) was used to evaluate the early prognosis of all patients. There were 508 cases in good prognosis group (mRS score 0-2) and 219 cases in poor prognosis group (mRS score 3-6). Multivariate logistic regression analysis was used to analyze the influencing factors for poor prognosis of AIS patients, and a risk prediction model was constructed, and receiver operating characteristic (ROC) curve was used to verify the risk prediction model. Results Univariate analysis showed that the age (more than 60 years old),the prevalence of diabetes mellitus, the National Institutes of Health Stroke Scale (NIHSS) score, the levels of serum creatinine (SCr), erythrocyte sedimentation rate (ESR), triglyceride (TC), red blood cell distribution width to platelet count ratio (RPR) and procalcitonin in poor prognosis group were statistically higher than those in good prognosis group, and the levels of uric acid (UA), 25-hydroxyl vitamin D[25 (OH) D] and angiopoietin-1 (Ang-1) were lower than those in good prognosis group (P<0.05,P<0.01). Multivariate logistic regression analysis showed that NIHSS>13 points and RPR>0.065 were independent factors that increased the risk of poor prognosis in AIS patients (OR=2.56,1.63, P<0.01); UA>295.37 μmol/L, 25(OH)D>20 ng/ml, Ang-1>3.26 ng/ml were its protective factors (OR=0.76, 0.66, 0.57, P<0.05,P<0.01). ROC curve showed that the AUC of risk model predicting poor prognosis in AIS patients was 0.884 (95% CI: 0.783-0.984, P<0.01), with accuracy rate of 85.00%, sensitivity of 87.67%, specificity of 83.86% and a cutoff value of 0.768. Conclusion Elevated NIHSS and RPR at admission increase the risk of poor early prognosis in patients with AIS, while elevated UA, 25(OH)D and Ang-1 decrease the risk. The risk prediction model constructed on this basis can better predict the occurrence risk of poor early prognosis.
文章编号:     中图分类号:R743.3    文献标志码:A
基金项目:黑龙江省卫计委科研项目(2017-087)
引用文本:
赵楠楠,郑印,黄穹琼,姜旭.急性缺血性脑卒中早期预后不良的危险因素分析及预测模型构建[J].中国临床研究,2022,35(4):456-461.

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