[1]肖改荣,丁新苑,云宗金.急性脑梗死不良预后的危险因素分析及RDW与MPV的预测[J].医学信息,2020,33(24):67-70.[doi:10.3969/j.issn.1006-1959.2020.24.019]
　XIAO Gai-rong,DING Xin-yuan,YUN Zong-jin.Analysis of Risk Factors for Poor Prognosis of Acute Cerebral Infarction and Prediction of RDW and MPV[J].Medical Information,2020,33(24):67-70.[doi:10.3969/j.issn.1006-1959.2020.24.019]
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急性脑梗死不良预后的危险因素分析及RDW与MPV的预测()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
33卷
期数:
2020年24期
页码:
67-70
栏目:
论著
出版日期:
2020-12-15

文章信息/Info

Title:
Analysis of Risk Factors for Poor Prognosis of Acute Cerebral Infarction and Prediction of RDW and MPV
文章编号:
1006-1959（2020）24-0067-04
作者:
肖改荣; 丁新苑; 云宗金
安徽医科大学附属阜阳医院神经内科，安徽 阜阳 236000
Author(s):
XIAO Gai-rong; DING Xin-yuan; YUN Zong-jin
Department of Neurology,Fuyang Hospital,Anhui Medical University,Fuyang 236000,Anhui,China
关键词:
红细胞分布宽度; 平均血小板体积; 急性脑梗死; 预后
Keywords:
Red blood cell distribution width; Mean platelet volume; Acute cerebral infarction;  Prognosis
分类号:
R743.33
DOI:
10.3969/j.issn.1006-1959.2020.24.019
文献标志码:
A
摘要:
目的 分析急性脑梗死不良预后的影响因素及红细胞分布宽度（RDW）、平均血小板体积（MPV）与急性脑梗死预后的相关性。方法 选取2018年1月~2019年6月在我院诊治98例急性脑梗死患者的临床资料进行回顾性分析。依据患者脑梗死后3个月的改良Rankin量表（mRS）的评分结果将患者分为预后良好组（mRS≤2）71例和预后不良组（mRS＞2）27例。分析急性脑梗死不良预后的影响因素，并采用ROC曲线分析RDW、MPV对急性脑梗死不良预后的预测价值。结果 预后不良组糖尿病、高脂血症患病率均为48.15%，高于预后良好组的26.76%、25.35%，预后不良组的美国国立卫生研究院卒中量表（NIHSS）评分、RDW、MPV高于预后良好组，差异有统计学意义（P＜0.05）；经二元Logistic回归分析，NIHSS评分、RDW、MPV是急性脑梗死不良预后的独立危险因素（P＜0.05）；ROC曲线分析得出，RDW、MPV、二者联合诊断急性脑梗死预后的曲线下面积（AUC）分别为0.770、0.706、0.782，均具有诊断价值，其中二者联合诊断的AUC最大，RDW其次。选在最佳临界值点对应的灵敏度、特异度分别为：RDW为93.00%、59.30%，MPV为38.00%、94.30%，二者联合为74.60%、81.50%。结论 高NIHSS评分、RDW、MPV是急性脑梗死不良预后的独立危险因素，因此临床上对于此类患者需多加以预防措施，RDW、MPV对急性脑梗死预后均具有一定的诊断价值，二者联合的诊断价值较高。
Abstract:
Objective The correlation between red blood cell distribution width （RDW） and mean platelet volume （MPV） and poor prognosis of acute cerebral infarction was analyzed.Methods The clinical data of 98 patients with acute cerebral infarction diagnosed and treated in our hospital from January 2018 to June 2019 were selected for retrospective analysis. According to the results of the modified Rankin Scale (mRS) 3 months after cerebral infarction, the patients were divided into a good prognosis group (mRS≤2) 71 cases and a poor prognosis group (mRS>2) 27 cases. The factors affecting the poor prognosis of acute cerebral infarction were analyzed, and the ROC curve was used to analyze the predictive value of RDW and MPV on the poor prognosis of acute cerebral infarction.Results The prevalence of diabetes and hyperlipidemia in the poor prognosis group were 48.15%， which were significantly higher than the 26.76% and 25.35% in the good prognosis group. The National Institutes of Health Stroke Scale （NIHSS） score,RDW,MPV in the poor prognosis group. It was significantly higher than the group with good prognosis,the differences were statistically significant （P＜0.05）. By binary Logistic regression analysis， the NIHSS score,RDW,and MPV were independent risk factors for poor prognosis of acute cerebral infarction （P＜0.05）.ROC curve analysis showed that RDW， MPV， and the combined diagnosis of the area under the curveof acute cerebral infarction （AUC） are 0.770， 0.706， and 0.782， respectively， all of which had a diagnostic value,among them,the combined diagnosis of the two had the largest AUC, followed by RDW. The sensitivity and specificity corresponding to the optimal critical value point were respectively: RDW was 93.00%, 59.30%, MPV was 38.00%, 94.30%, the combination of the two was 74.60%, 81.50%.Conclusion High NIHSS score, RDW, and MPV are independent risk factors for the poor prognosis of acute cerebral infarction. Therefore, more preventive measures are needed for such patients in clinical practice. RDW and MPV have certain diagnostic value for the prognosis of acute cerebral infarction, and the two are combined The diagnostic value is high.

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更新日期/Last Update: 1900-01-01