预测急性缺血性脑卒中患者机械取栓术后 90 天预后的临床模型:回顾性研究。

Yu Huang, Chuyue Wu, Cuiping Du, Da Lei, Li Li, Shengli Chen
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引用次数: 0

摘要

背景:对于大血管闭塞(LVO)导致的急性缺血性卒中(AIS),通常建议在时间窗(发病后 6 小时)内进行机械取栓术(MT)。然而,急性大血管闭塞性脑卒中(MT)术后预后不佳的情况并不少见,这可能是由于缺乏适当的术后监测所致。与传统成像技术相比,经颅多普勒(TCD)超声和定量脑电图(QEEG)具有快速、方便和床旁检查的优势:我们旨在分析临床因素、经颅多普勒(TCD)超声和定量脑电图(QEEG)对因大血管闭塞(LVO)导致的急性缺血性卒中(AIS)患者出院后 90 天的预后的预测性:方法:纳入在大血管闭塞导致急性缺血性卒中发病后 6 小时内通过 MT 实现血管再通的患者。我们利用这些数据建立了四个预后预测模型,并通过曲线下面积、灵敏度和特异性对预测效果进行了比较:结果:共有 74 名患者被纳入研究。其中,47 名患者在出院时预后不良(63.5%),45 名患者在出院后 90 天预后不良(60.8%)。出院后 90 天预后不良的独立预测因素包括:年龄、入院时的 NIHSS 评分、患侧/健侧的 PI 和 RAP。在所建立的四个模型中,当年龄与入院时的 NIHSS 评分、TCD 参数(患侧 VD、患侧/健侧 PI)和 QEEG 参数(RAP)联合用于预后预测时,AUC 最高(达 0.831)。然而,四个预测模型的AUC差异不大(P>0.05):结论:年龄、入院时的 NIHSS 评分、TCD 参数和 QEEG 参数是因前循环 LVO 而接受 MT 治疗的 AIS 患者出院后 90 天预后的独立预测因素。结合上述四个参数的模型可能有助于预测此类患者的预后。
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A Clinical Model predicting the 90-Day Prognosis after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke: A Retrospective Study.

Background: Mechanical thrombectomy (MT) is usually recommended for acute ischemic stroke (AIS) due to large vessel occlusion (LVO) within the time window (6 hours after the disease onset). However, poor prognosis in acute great vascular occlusive stroke after MT, which is not an uncommon occurrence, can be attributed to an absence of appropriate postoperative monitoring. Transcranial Doppler (TCD) ultrasound and quantitative electroencephalography (QEEG) offer the advantages of fast, convenient, and bedside examinations compared with conventional imaging techniques.

Objective: We aimed to analyze the predictive performance of clinical factors, Transcranial Doppler (TCD) ultrasound and quantitative electroencephalography (QEEG) for the prognosis of patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) at 90 days after discharge.

Method: Patients achieved revascularization through MT performed within 6 hours after the onset of AIS due to LVO were included. We use the data to build four predictive models of prognosis and compared the predictive performance measured by the area under the curve, sensitivity, and specificity.

Result: A total of 74 patients were included in the study. Among them, 47 patients had a poor prognosis (63.5%) on discharge, and 45 patients had a poor prognosis (60.8%) at 90 days after discharge. Independent predictors of poor prognosis at 90 days after discharge were identified as follows: age, NIHSS score on admission, PI on the affected/healthy side, and RAP. Among the four models built, AUC was the highest (reaching 0.831) when age was combined with NIHSS score on admission, TCD parameters (VD on the affected side, PI on the affected/healthy side), and QEEG parameter (RAP) for prognostic prediction. However, AUC of the four predictive models did not differ significantly (P>0.05).

Conclusion: Age, NIHSS score on admission, TCD parameters, and QEEG parameter were independent predictors of the prognosis at 90 days after discharge in patients receiving MT for AIS due to LVO in the anterior circulation. The model combining the above four parameters may be helpful for prognostic prediction in such patients.

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