Predicting the risk of spontaneous hemorrhage conversion after acute ischemic stroke based on a columnar graph model
10.3969/j.issn.1004-1648.2023.06.014
- VernacularTitle:基于列线图模型的急性缺血性脑卒中后自发性出血转化风险预测研究
- Author:
Yihao YANG
1
;
Huijuan LIU
;
Mengjing WU
Author Information
1. 570100 海口,海南医学院第一附属医院神经内科·海南省热带脑科学研究与转化重点实验室
- Keywords:
acute ischemic stroke;
spontaneous haemorrhagic transformation;
nomogram
- From:
Journal of Clinical Neurology
2023;36(6):441-446
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish a quantitative and visual prediction model for spontaneous hemorrhagic transformation(sHT)after acute ischemic stroke(AIS)and validate the efficacy by nomogram.Methods A total of 240 patients with AIS were selected,and the general data,serological tests and imaging findings were collected.The patients were randomly divided into modeling group(175 cases)and validation group(65 cases).The patients were also divided into non-HT group and HT group according to the imaging results.The R 4.1.1 software and the rms package were used to build the column line graph model,while Bootstrap method was applied to repeat sampling 1000 times for internal and external validation,and the H-L goodness-of-fit test,clinical decision curve and ROC curve were used to assess the calibration and discrimination of the column line graph model,respectively.Results Among 240 patients with AIS,bleeding conversion occurred in 60 cases(25.0%).In the modeling group,the results of multifactorial Logistic regression showed that the presence or absence of previous history of atrial fibrillation,NIHSS score at the onset,Hb,high-density lipoprotein(HDL)and infarct area were significant influencing factors for sHT after AIS.The x2 values of the H-L goodness-of-fit test for the modeling and validation groups were 5.61 and 0.74,respectively,corresponding to P values of 0.13 and 0.69,indicating that the established column line graph model had good prediction accuracy;the area under the ROC curve for the column line graph prediction modeling group and validation group were 0.963(95%CI:0.926-1.000)and 0.977(95%CI:0.950-1.000),and the results suggested that the model had good discrimination.Conclusions Previous history of atrial fibrillation,NIHSS score size at onset,Hb,HDL and the size of infarct area are independent influencing factors of sHT after AIS.Establishing the visual nomogram model based on the above factors can effectively predict the risk of sHT after AIS.
