[急性缺血性脑卒中复发的危险因素及基于Lasso回归预测复发风险的nomogram模型构建]。

Jiaxin Jin, Pengzhen Ma, Eryu Wang, Yingzhen Xie
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引用次数: 0

摘要

目的:探讨急性缺血性脑卒中(AIS) 1年内复发的危险因素,建立预测其复发风险的nomogram模型。方法:选取2021年3月至2022年3月在东直门医院(建模集)和房山医院(验证集)住院的AIS患者(≤7天)为研究对象。采用Lasso回归分析识别1年内AIS复发的重要预测因素,采用多因素Logistic回归分析分析影响AIS复发的独立因素。采用R studio构建复发风险预测模态图模型,采用ROC曲线分析和Hosmer-Lemeshow拟合优度检验评估其判别能力和校正性。结果:模型集和验证集分别包含28例(15.22%)和21例(15.00%)AIS复发病例。在建模组中,与非复发组相比,复发组患者中年龄bbb65岁、糖尿病、心律失常、卒中后便秘、FBG >7.5的比例较高,NLR、尿素、Cr、HbA1c、FIB、TT水平显著升高(P65岁、心律失常、卒中后便秘、FBG >7.5、NLR、Cr均为AIS复发的独立危险因素(PCI: 0.782-0.932),验证组为0.679 (95%CI: 0.563-0.794)。结论:以年龄> ~ 65岁、心律失常、卒中后便秘、FBG >7.5、NLR、Cr为指标建立的nomogram模型对AIS 1年内复发有较好的预测价值。
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[Risk factors of recurrence of acute ischemic stroke and construction of a nomogram model for predicting the recurrence risk based on Lasso Regression].

Objectives: To investigate the risk factors of recurrence of acute ischemic stroke (AIS) within 1 year and establish a nomogram model for predicting the recurrence risk.

Methods: This study was conducted in two cohorts of AIS patients (≤7 days) hospitalized in Dongzhimen Hospital (modeling set) and Fangshan Hospital (validation set) from March, 2021 to March, 2022. Lasso regression analysis was used to identify the important predictive factors for AIS recurrence within 1 year, and multivariate Logistic regression analysis was performed to analyze the independent factors affecting AIS recurrence. The recurrence risk prediction nomogram model was constructed using R studio, and its discriminating power and calibration were assessed using ROC curve analysis and Hosmer-Lemeshow goodness-of-fit test.

Results: The modeling and validation sets contained 28 cases (15.22%) and 21 cases (15.00%) of AIS recurrence, respectively. In the modeling set, compared with the non-relapse group, the recurrence group had higher proportions of patients with age >65 years, diabetes, arrhythmia, constipation after stroke, and FBG >7.5 and significantly higher levels of NLR, UREA, Cr, HbA1c, FIB and TT (P<0.05). Multivariate Logistic regression analysis showed that an age >65 years, arrhythmia, constipation after stroke, FBG >7.5, NLR and Cr were all independent risk factors of AIS recurrence (P<0.05). Hosmer-Lemeshow goodness-of-fit test and calibration curve analysis showed that the risk prediction model had good fitting between the modeling set and the verification set. The ROC curve showed that for predicting AIS recurrence within 1 year, the AUC of the predictive model was 0.857 (95%CI: 0.782-0.932) in the modeling set and 0.679 (95%CI: 0.563-0.794) in the validation set.

Conclusions: The nomogram model established based on age >65 years, arrhythmia, constipation after stroke, FBG >7.5, NLR and Cr has a good predictive value for AIS recurrence within 1 year.

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南方医科大学学报杂志
南方医科大学学报杂志 Medicine-Medicine (all)
CiteScore
1.50
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0.00%
发文量
208
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