Department of Neurology & David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Division of Interventional Neuroradiology, Department of Radiological Sciences & David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Interv Neuroradiol. 2024 Aug;30(4):506-516. doi: 10.1177/15910199221140177. Epub 2022 Nov 18.
Telerobotic endovascular therapy (EVT) has the potential to decrease time to treatment and expand existing networks of care to more rural populations. It is currently unclear how its implementation would impact existing stroke networks.
Conditional probability models were generated to predict the probability of excellent outcome for patients with suspected large vessel occlusion (LVO). A baseline stroke network was created for California using existing intravenous thrombolysis (IVT) centers and comprehensive stroke centers (CSCs) capable of IVT and EVT. Optimal transport decisions and catchment areas were generated for the baseline model and three hypothetical scenarios through conversion of IVT centers at various distances from a CSC into centers capable of telerobotic EVT [i.e., hospitals ≥15 and <50 miles from a CSC were converted (Scenario 1), ≥50 and <100 miles (Scenario 2), and ≥100 miles (Scenario 3)]. Procedural times and success rates were varied systematically.
Telerobotic EVT centers decreased median travel time for LVO patients in all three scenarios. The estimated number of robotically treated LVOs per year in Scenarios 1, 2, and 3 were 2,172, 740, and 212, respectively. Scenario 1 (15-50 miles) was the most sensitive to robotic time delay and success rate, but all three scenarios were more sensitive to decreases in procedural success rate compared to time delay.
Telerobotic EVT has the potential to improve care for stroke patients outside of major urban centers. Compared to procedural time delays in robotic EVT, a decrease in procedural success rate would not be well tolerated.
远程机器人血管内治疗(EVT)有可能缩短治疗时间,并将现有的护理网络扩展到更多的农村地区。目前尚不清楚其实施将如何影响现有的中风网络。
生成条件概率模型来预测疑似大血管闭塞(LVO)患者获得良好预后的概率。使用现有的静脉溶栓(IVT)中心和能够进行 IVT 和 EVT 的综合卒中中心(CSC),为加利福尼亚州创建了基线卒中网络。通过将距离 CSC 不同距离的 IVT 中心转换为能够进行远程机器人 EVT 的中心,为基线模型和三个假设情景生成了最优转运决策和集水区[即,将距离 CSC 大于等于 15 英里且小于 50 英里的医院(情景 1)、大于等于 50 英里且小于 100 英里(情景 2)和大于等于 100 英里(情景 3)转换为中心]。系统地改变了手术时间和成功率。
在所有三种情况下,远程机器人 EVT 中心都缩短了 LVO 患者的中位旅行时间。情景 1、2 和 3 中每年机器人治疗的 LVO 估计数量分别为 2172、740 和 212。情景 1(15-50 英里)对机器人时间延迟和成功率最敏感,但与时间延迟相比,所有三种情景对手术成功率的降低更为敏感。
远程机器人 EVT 有可能改善主要城市中心以外的中风患者的护理。与机器人 EVT 的手术时间延迟相比,手术成功率的降低将无法得到很好的容忍。