Introduction

Endovascular thrombectomy (EVT) is a well-established treatment of acute ischemic stroke. Variability in outcomes among thrombectomy patients results in a need for patient centered approaches to recovery. Identifying key factors that are associated with outcomes can help prognosticate and direct resources for continued improvement post-treatment. Thus, we developed a comprehensive predictive model of short-term outcomes post-thrombectomy.

Methods

This is a retrospective chart review of adult patients who underwent EVT at our institution over the last four years. Primary outcome was dichotomized 90-day mRS (mRS 0–2 v mRS 3–6). Bivariate analyses were conducted, followed by logistic regression modelling via a backward-elimination approach to identify the best fit predictive model.

Results

326 thrombectomies were performed; 230 cases were included in the model. In the final predictive model, adjusting for age, gender, race, diabetes, and presenting NIHSS, pre-admission mRS = 0–2 (OR 18.1; 95% 3.44–95.48; p < 0.001) was the strongest predictor of a good outcome at 90-days. Other independent predictors of good outcomes included being a non-smoker (OR 5.4; 95% CI 1.53–19.00; p = 0.01) and having a post-thrombectomy NIHSS<10 (OR 9.7; 95% CI 3.90–24.27; p < 0.001). A decompressive hemicraniectomy (DHC) was predictive of a poor outcome at 90-days (OR 0.07; 95% CI 0.01–0.72; p = 0.03). This model had a Sensitivity of 79%, a Specificity of 89% and an AUC=0.89.

Conclusion

Our model identified low pre-admission mRS score, low post-thrombectomy NIHSS, non-smoker status and not requiring a DHC as predictors of good functional outcomes at 90-days. Future works include developing a prognostic scoring system.

中文翻译：

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接受血管内血栓切除术的急性缺血性卒中患者功能结果的预测模型

介绍

血管内血栓切除术 (EVT) 是一种成熟的急性缺血性卒中治疗方法。血栓切除术患者结局的差异导致需要以患者为中心的恢复方法。确定与结果相关的关键因素可以帮助预测和指导资源，以实现治疗后的持续改善。因此，我们开发了血栓切除术后短期结果的综合预测模型。

方法

这是过去四年在我们机构接受 EVT 的成年患者的回顾性图表回顾。主要结果是 90 天 mRS 的二分法（mRS 0-2 v mRS 3-6）。进行了双变量分析，然后通过向后消除方法进行逻辑回归建模，以确定最佳拟合预测模型。

结果

进行了 326 次血栓切除术；模型中包含 230 个案例。在最终的预测模型中，调整年龄、性别、种族、糖尿病和 NIHSS，入院前 mRS = 0-2（OR 18.1；95% 3.44-95.48；p  < 0.001）是良好结果的最强预测因子在 90 天。其他良好结果的独立预测因素包括不吸烟（OR 5.4；95% CI 1.53-19.00；p  = 0.01）和血栓切除术后 NIHSS<10（OR 9.7；95% CI 3.90-24.27；p  <0.001 ）。去骨瓣减压术 (DHC) 可预测 90 天的不良结果（OR 0.07；95% CI 0.01–0.72；p  = 0.03）。该模型的敏感性为 79%，特异性为 89%，AUC=0.89。

结论

我们的模型确定了入院前 mRS 评分低、血栓切除术后 NIHSS 低、非吸烟状态和不需要 DHC 作为 90 天良好功能结果的预测因子。未来的工作包括开发预后评分系统。