Abstract：
OBJECTIVE: We evaluated the on-scene time of emergency medical services (EMS) for cases where discrimination between acute stroke and epileptic seizures at the initial examination was difficult and identified factors linked to delays in such scenarios.
METHODS: A retrospective review of cases with suspected seizure using the EMS database of fire departments across six Japanese cities between 2016 and 2021 was conducted. Patient classification was based on transport codes. We defined cases with stroke-suspected seizure as those in whom epileptic seizure was difficult to differentiate from stroke and evaluated their EMS on-scene time compared to those with epileptic seizures.
RESULTS: Among 30,439 cases with any seizures, 292 cases of stroke-suspected seizure and 8,737 cases of epileptic seizure were included. EMS on-scene time in cases of stroke-suspected seizure was shorter than in those with epileptic seizure after propensity score matching (15.1±7.2 min vs. 17.0±9.0 min; p = 0.007). Factors associated with delays included transport during nighttime (odds ratio [OR], 1.73, 95 % confidence interval [CI] 1.02-2.93, p = 0.041) and transport during the 2020-2021 pandemic (OR, 1.77, 95 % CI 1.08-2.90, p = 0.022).
CONCLUSIONS: This study highlighted the difference between the characteristics in EMS for stroke and epileptic seizure by evaluating the response to cases with stroke-suspected seizure. Facilitating prompt and smooth transfers of such cases to an appropriate medical facility after admission could optimize the operation of specialized medical resources.
METHODS: A retrospective review of cases with suspected seizure using the EMS database of fire departments across six Japanese cities between 2016 and 2021 was conducted. Patient classification was based on transport codes. We defined cases with stroke-suspected seizure as those in whom epileptic seizure was difficult to differentiate from stroke and evaluated their EMS on-scene time compared to those with epileptic seizures.
RESULTS: Among 30,439 cases with any seizures, 292 cases of stroke-suspected seizure and 8,737 cases of epileptic seizure were included. EMS on-scene time in cases of stroke-suspected seizure was shorter than in those with epileptic seizure after propensity score matching (15.1±7.2 min vs. 17.0±9.0 min; p = 0.007). Factors associated with delays included transport during nighttime (odds ratio [OR], 1.73, 95 % confidence interval [CI] 1.02-2.93, p = 0.041) and transport during the 2020-2021 pandemic (OR, 1.77, 95 % CI 1.08-2.90, p = 0.022).
CONCLUSIONS: This study highlighted the difference between the characteristics in EMS for stroke and epileptic seizure by evaluating the response to cases with stroke-suspected seizure. Facilitating prompt and smooth transfers of such cases to an appropriate medical facility after admission could optimize the operation of specialized medical resources.
摘要：
目的：我们评估了急诊医疗服务（EMS）的现场时间，这些病例在初次检查时很难区分急性中风和癫痫发作，并确定了与这种情况下的延误有关的因素。
方法：使用EMS数据库对2016年至2021年日本六个城市的消防部门的疑似癫痫发作病例进行了回顾性审查。患者分类基于运输代码。我们将怀疑有中风发作的病例定义为癫痫发作难以与中风区分的病例，并与癫痫发作的病例相比评估了其EMS现场时间。
结果：在30,439例癫痫发作患者中，纳入292例疑似中风发作和8,737例癫痫发作。倾向评分匹配后，疑似卒中癫痫发作的EMS现场时间短于癫痫发作的患者（15.1±7.2minvs.17.0±9.0分钟；p=0.007）。与延误相关的因素包括夜间运输(赔率比[OR]，1.73，95%置信区间[CI]1.02-2.93，p=0.041）和2020-2021年大流行期间的运输（OR，1.77，95%CI1.08-2.90，p=0.022）。
结论：本研究通过评估对怀疑有卒中发作的病例的反应，强调了卒中和癫痫发作的EMS特征之间的差异。促进此类病例在入院后迅速顺利地转移到适当的医疗机构，可以优化专业医疗资源的运作。
方法：使用EMS数据库对2016年至2021年日本六个城市的消防部门的疑似癫痫发作病例进行了回顾性审查。患者分类基于运输代码。我们将怀疑有中风发作的病例定义为癫痫发作难以与中风区分的病例，并与癫痫发作的病例相比评估了其EMS现场时间。
结果：在30,439例癫痫发作患者中，纳入292例疑似中风发作和8,737例癫痫发作。倾向评分匹配后，疑似卒中癫痫发作的EMS现场时间短于癫痫发作的患者（15.1±7.2minvs.17.0±9.0分钟；p=0.007）。与延误相关的因素包括夜间运输(赔率比[OR]，1.73，95%置信区间[CI]1.02-2.93，p=0.041）和2020-2021年大流行期间的运输（OR，1.77，95%CI1.08-2.90，p=0.022）。
结论：本研究通过评估对怀疑有卒中发作的病例的反应，强调了卒中和癫痫发作的EMS特征之间的差异。促进此类病例在入院后迅速顺利地转移到适当的医疗机构，可以优化专业医疗资源的运作。
