基于列线图模型预测机械取栓治疗心源性急性脑卒中患者的预后情况

Predicting the prognosis of patients with cardiogenic acute stroke based on the nomogram model

目的构建用于预测心源性急性脑卒中患者机械取栓手术预后不良及死亡风险的列线图模型。方法回顾性选取2016年1月—2020年6月江阴市中医院收治的276例行机械取栓治疗的心源性急性脑卒中患者为研究对象,记录其一般资料及实验室检查结果,于术后第90天根据是否预后不良,将研究对象分为预后良好组(n=122)和预后不良组(n=154);根据是否死亡,将研究对象分为存活组(n=208)和死亡组(n=68)。分组后,比较患者相关资料的差异;采用Logistic回归分析筛选预后不良及死亡的危险因素;建立列线图预测模型,并采用受试者工作特征(ROC)曲线评估列线图模型对预后不良及死亡的预测能力。将多因素回归分析筛选出的各独立因素作为预测因子构建列线图模型,预测心源性急性脑卒中患者机械取栓手术的预后情况,对本研究建立的列线图模型的校准度和有效性进行评价。服从正态分布的计量资料采用均数±标准差(±s)表示,组间比较采用两独立样本t检验。计数资料组间比较采用χ^(2)检验。结果多因素Logistic回归分析结果显示,年龄(OR=1.165;95%CI:1.046~1.284;P=0.001),糖尿病(OR=1.123;95%CI:1.021~1.225;P<0.001),出血转化(OR=2.394;95%CI:1.857~2.931;P=0.001),再通情况(OR=0.418;95%CI:0.410~0.552;P=0.001),NIHSS评分(OR=1.502;95%CI:1.373~1.631;P=0.001),中性粒细胞计数(NEUT)(OR=1.024;95%CI:1.009~1.139;P=0.001),NEUT/淋巴细胞计数(NLR)(OR=1.235;95%CI:1.112~1.358;P=0.001),D-二聚体(OR=1.939;95%CI:1.328~2.551;P=0.001)是心源性急性脑卒中患者预后不良的独立危险因素;年龄(OR=1.153;95%CI:1.080~1.226;P<0.001),出血转化(OR=6.330;95%CI:4.904~7.754;P=0.001),再通情况(OR=0.418;95%CI:0.323~0.514;P=0.001),NIHSS评分(OR=2.051;95%CI:1.784~2.338;P=0.001),NEUT(OR=1.399;95%CI:1.275~1.523;P=0.001),NLR(OR=1.528;95%CI:1.414~1.642;P=0.001),D-二聚体(OR=2.391;95%CI:1.948~2.834;P=0.001)是心源性急性脑卒中患者死亡的独立预测因素。建立的列线图模型预测预后不良和死亡的ROC曲线下面积分别为0.814(95%CI:0.800~0.828)、0.842(95%CI:0.828~0.857)。结论年龄、出血转化、再通情况、NIHSS评分、NEUT、NLR、D-二聚体对于机械取栓治疗心源性急性脑卒中患者的预后情况均有重要意义,糖尿病仅对预后不良有提示作用。基于这些因素建立的列线图模型可有效帮助临床医师评估患者预后情况,为其制定合理的治疗方案,提高预后。

Objective A nomogram model was constructed to predict poor prognosis and death risk of mechanical thrombectomy in patients with cardiogenic acute stroke.Methods Selected 276 patients with cardiogenic acute stroke who were treated by Jiangyin Hospital of Traditional Chinese Medicine from January 2016 to June 2020 who underwent mechanical thrombectomy as the research objects,and recorded their general information and laboratory test results.On the 90th day,the subjects were divided into a good prognosis group(n=122)and a poor prognosis group(n=154)according to whether the prognosis was poor or not;according to whether they died,the subjects were divided into the survival group(n=208)and the death group(n=68).The differences in patient related data were compared,Logistic regression analysis was used to screen for risk factors for poor prognosis and death,the line chart prediction model was established,and the ability of the column chart model to predict poor prognosis and death was evaluated by using the subject work characteristic(ROC)curve.The independent factors selected by multivariate regression analysis were used as predictors to construct a nomogram model to predict the prognosis of mechanical thrombectomy surgery in patients with cardiogenic acute stroke.The degree of calibration and validity of the nomogram model established in this study Make an evaluation.The measurement data that obey the normal distribution were represented by the Mean±standard deviation(±s),and the two independent sample t test was used for the comparison between groups;The comparison of enumeration data between groups adopted chi-square test.Results Multivariate logistic regression analysis showed age(OR=1.165;95%CI:1.046-1.284;P=0.001),diabetes(OR=1.123;95%CI:1.021-1.225;P<0.001),hemorrhage transformation(OR=2.394;95%CI:1.857-2.931;P=0.001),recanalization(OR=0.418;95%CI:0.410-0.552;P=0.001),NIHSS score(OR=1.502;95%CI:1.373-1.631);P=0.001),neutrophil count(NEUT)(OR=1.024;95%CI:1.009-1.139;P=0.001),NEUT/lymphocyte count(NLR)(OR=1.235;95%CI:1.112-1.358;P=0.001),D-dimer(OR=1.939;95%CI:1.328-2.551;P=0.001)was an independent risk factor for poor prognosis in patients with cardiogenic acute stroke;age(OR=1.153;95%CI:1.080-1.226;P<0.001),hemorrhage transformation(OR=6.330;95%CI:4.904-7.754;P=0.001),recanalization(OR=0.418;95%CI:0.323-0.514;P=0.001),NIHSS score(OR=2.051;95%CI:1.784-2.338;P=0.001),NEUT(OR=1.399;95%CI:1.275-1.523;P=0.001),NLR(OR=1.528;95%CI:1.414-1.642;P=0.001),D-dimer(OR=2.391;95%CI:1.948-2.834;P=0.001)was an independent predictor of death in patients with cardiogenic acute stroke.The established nomogram model predicted poor prognosis and the area under the ROC curve of death were 0.814(95%CI:0.800-0.828)and 0.842(95%CI:0.828-0.857).Conclusions Age,hemorrhage transformation,recanalization,NIHSS score,NEUT,NLR,and D-dimer are all important for the prognosis of patients with cardiogenic acute stroke by mechanical thrombectomy.Diabetes only has a suggestive effect on poor prognosis.The nomogram model established based on these factors can effectively help clinicians evaluate the prognosis of patients,formulate reasonable treatment plans for them,and improve the prognosis.