From the Institute for Technology Assessment, Massachusetts General Hospital, Boston (A.A., P.C.E., C.H.).
Department of Medicine, Massachusetts General Hospital, Boston (A.A., P.C.E., C.H.).
Stroke. 2018 Oct;49(10):2532-2535. doi: 10.1161/STROKEAHA.118.022041.
Background and Purpose- Prehospital routing algorithms for patients with suspected stroke because of large vessel occlusions should account for likelihood of benefit from endovascular therapy (EVT), risk of alteplase delays, and transport times. We built a mathematical model to give a real-time, location-based optimal emergency medical service routing location based on local resources, transport times, and patient characteristics. Methods- Using location, onset time, age, sex, and prehospital stroke severity, we calculated odds of a favorable outcome for a patient with suspected large vessel occlusions under 2 scenarios: direct to EVT-capable hospital versus transport to the nearest alteplase-capable hospital with transfer to EVT-capable hospital if appropriate. We project lifetime outcomes incorporating disability, quality of life utility, and cost. Multiple parameter sets of center-specific times (eg, door to alteplase) were randomly selected within a clinically plausible range to account for the model sensitivity to these estimates; for each iteration, the optimal strategy was defined as the most cost-effective outcome (threshold, $100 000 per quality-adjusted life-years gained). After 1000 simulations, the most frequently occurring optimal strategy was the final recommendation, with its strength measured as the proportion of runs for which it was optimal. Results- Routing recommendations were highly sensitive to small changes in model input parameters. Under many scenarios, the recommendations for direct transfer to the EVT site increased with increasing stroke severity and geographic proximity but did not vary substantially with respect to sex, age, or onset time. Conclusions- We present a mathematical decision model that determines ideal prehospital routing recommendations for patients with suspected stroke because of large vessel occlusions, with consideration of patient characteristics and location at onset. This model may be further refined by incorporating real-time data on traffic patterns and actual EVT and alteplase timeliness performance. Further studies are needed to verify model predictions.
背景与目的-对于疑似大血管闭塞引起的卒中患者，在进行血管内治疗（EVT）前应考虑到获益的可能性、阿替普酶延迟的风险和转运时间。我们构建了一个数学模型，以便根据当地资源、转运时间和患者特征，实时提供基于位置的最佳紧急医疗服务转运方案。
方法-使用位置、发病时间、年龄、性别和发病前的卒中严重程度，我们计算了疑似大血管闭塞的患者在以下两种情况下获得良好预后的可能性：直接转运至有 EVT 能力的医院与转运至最近的有阿替普酶能力的医院，如有必要再转运至有 EVT 能力的医院。我们预测了终身结局，包括残疾、生活质量效用和成本。在临床合理范围内随机选择中心特定时间（如阿替普酶给药前的时间）的多个参数集，以考虑模型对这些估计的敏感性；对于每个迭代，最佳策略定义为最具成本效益的结局（阈值为每获得一个质量调整生命年的成本为 10 万美元）。经过 1000 次模拟，最常出现的最佳策略是最终建议，其强度通过该策略为最佳策略的比例来衡量。
结果-转运建议对模型输入参数的微小变化非常敏感。在许多情况下，直接转至 EVT 站点的建议随着卒中严重程度和地理接近度的增加而增加，但与性别、年龄或发病时间关系不大。
结论-我们提出了一种数学决策模型，用于确定疑似大血管闭塞引起的卒中患者的理想院前转运建议，同时考虑了患者特征和发病时的位置。通过纳入实时交通模式数据以及实际 EVT 和阿替普酶及时性表现，该模型可以进一步改进。需要进一步的研究来验证模型的预测。
