| 苏航,周志刚,李菁.临床-超声列线图预测急性缺血性脑卒中短期预后[J].中国介入影像与治疗学,2024,21(6):338-342 |
| 临床-超声列线图预测急性缺血性脑卒中短期预后 |
| Nomogram based on clinical-ultrasonic features for predicting short-term prognosis of acute ischemic stroke |
| 投稿时间：2023-03-27 修订日期：2024-04-28 |
| DOI：10.13929/j.issn.1672-8475.2024.06.006 |
| 中文关键词: 脑卒中 超声检查 预后 |
| 英文关键词:stroke ultrasonography prognosis |
| 基金项目:河南省医学科技攻关计划软科学重点项目（RKX202101007）。 |
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| 中文摘要: |
| 目的 观察临床-超声列线图预测急性缺血性脑卒中（AIS）短期预后的价值。方法 回顾性分析168例接受血管内介入治疗的AIS患者，根据治疗后3个月改良Rankin量表评分将其分为预后良好组（n=134）及预后不良组（n=34）。比较组间临床及超声资料，采用最小绝对收缩和选择算子（LASSO）算法及Cox回归方程分析AIS短期预后的独立影响因素，以之分别构建临床、超声及临床-超声列线图模型；绘制受试者工作特征曲线，计算曲线下面积（AUC），评估各模型预测AIS短期预后的效能。结果 发病至入院时间、美国国立卫生院卒中量表（NIHSS）评分、Alberta卒中项目早期CT评分（ASPECTS）、斑块时间-强度曲线强度均值（TIC-M）及峰值强度（TIC-P）和伽马拟合曲线的AUC均为AIS短期预后的独立影响因素（P均＜0.05）。临床、超声及临床-超声列线图模型预测AIS短期预后的AUC分别为0.888、0.758及0.921，以临床-超声列线图模型的预测效能最高（P均＜0.05）。结论 临床-超声列线图可有效预测AIS短期预后。 |
| 英文摘要: |
| Objective To explore the value of nomogram based on clinical-ultrasonic features for predicting short-term prognosis of acute ischemic stroke （AIS）. Methods Totally 168 patients with AIS who underwent intravascular interventional therapies were retrospectively enrolled. The patients were divided into good prognosis group （n=134） and poor prognosis group （n=34） according to the score of modified Rankin scale 3 months after treatments. Clinical and ultrasonic data were compared between groups. Least absolute shrinkage and selection operator （LASSO） algorithm and Cox regression analysis were used to screen the independent impact factors for predicting short-term prognosis of AIS， and then clinical， ultrasonic and clinical-ultrasonic nomogram models were constructed based on the above independent impact factors， respectively. Receiver operating characteristic curves were drawn， and the areas under the curves （AUC） were calculated to evaluate the efficacy of each model for predicting short-term prognosis of AIS. Results The time span from onset to admission， National Institute of Health stroke scale （NIHSS） score， Alberta stroke program early CT score （ASPECTS）， time-intensity curve-mean （TIC-M）， time-intensity curve-peak （TIC-P） and the AUC of gamma curve were all independent impact factors for predicting short-term prognosis of AIS （all P＜0.05）. The AUC of clinical， ultrasonic and clinical-ultrasonic nomogram model was 0.888， 0.758 and 0.921， respectively， among which clinical-ultrasonic nomogram model had the highest predictive efficacy （both P＜0.05）. Conclusion Clinical-ultrasonic nomogram could be used to effectively predict short-term prognosis of AIS. |
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