Andrea Loggini, Amber Schwertman, Jessie Henson, Julie Wesler, Jonatan Hornik, Karam Dallow, Alejandro Hornik
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引用次数: 0
摘要
背景:静脉溶栓是改善急性缺血性卒中功能预后的成熟治疗方法。然而,各种急性中枢神经系统功能障碍可模拟卒中,溶栓治疗可能无益且有潜在风险。通过远程医疗评估准确区分模拟中风与中风的能力尚不确定。本研究旨在确定通过远程医疗评估疑似缺血性中风并接受溶栓治疗的患者中模拟中风的临床预测因素:我们对 2017 年至 2024 年期间在南伊利诺伊州医疗保健机构通过远程医疗接受溶栓治疗的疑似急性缺血性脑卒中患者进行了一项回顾性观察研究。研究收集了人口统计学、既往病史、临床表现、美国国立卫生研究院卒中量表(NIHSS)、卒中指标和实验室值等数据。最终诊断结果分为脑血管疾病(CD)(包括急性缺血性中风和短暂性脑缺血发作)和中风拟态(SM)。结果包括住院时间(LOS)和出院处置:结果:在通过远程医疗接受溶栓治疗的 171 名患者中,128 人(75%)被诊断为 CD,43 人(25%)被诊断为 SM,中毒性代谢性脑病是最常见的模拟病(40%,n = 17)。调整后的前向逻辑回归显示,年龄(OR:0.957,95% CI:0.931-0.984,P = .002)和 NIHSS(OR:1.098,95% CI:1.032-1.168,P = .003)仍与 SM 独立相关。预测性 TeleStroke Mimic 得分的 c 统计量为 0.61。SM的中位LOS更短(3 [2-3] vs 3 [2-6],P < .01),出院回家率更高(86% vs 55%,P < .01):结论:在我们的研究人群中,年龄越小、NIHSS 越高,接受远程医疗溶栓治疗的患者确诊 SM 的几率越高。这些变量不足以可靠地确定通过远程医疗评估的患者亚群,对这些患者可以不使用溶栓药物。远程中风模拟评分的不佳表现凸显了改进预测工具的必要性。在进行更大规模的研究之前,远程医疗溶栓应遵循现行的现场指南。
Clinical Predictors of Stroke Mimics in Code Stroke Patients Evaluated via Telemedicine and Treated With Thrombolytic Therapy.
Background: Intravenous thrombolysis is an established treatment to improve functional outcomes in acute ischemic stroke. However, various acute central nervous system dysfunctions can mimic stroke, where thrombolytic therapy may provide no benefit and carries potential risks. The ability to accurately distinguish stroke mimics vs stroke by telemedicine evaluation is uncertain. This study aims to identify clinical predictors of stroke mimics in patients evaluated via telemedicine for suspected ischemic stroke and treated with thrombolytics.
Methods: We conducted a retrospective observational study of patients treated with thrombolytics for suspected acute ischemic stroke via telemedicine at Southern Illinois Healthcare between 2017 and 2024. Data on demographics, past medical history, clinical presentation, National Institutes of Health Stroke Scale (NIHSS), stroke metrics, and laboratory values were collected. Final diagnoses were categorized as cerebrovascular disease (CD), including acute ischemic stroke and transient ischemic attack, and stroke mimic (SM). Outcomes included hospital length of stay (LOS) and discharge disposition.
Results: Of 171 patients treated with thrombolytics via telemedicine, 128 (75%) were diagnosed with CD, and 43 (25%) were SM, with toxic-metabolic encephalopathy being the most common mimic (40%, n = 17). Adjusted forward logistic regression showed age (OR: 0.957, 95% CI: 0.931-0.984, P = .002) and NIHSS (OR: 1.098, 95% CI: 1.032-1.168, P = .003) remained independently associated with SM. The predictive TeleStroke Mimic was score performed with c-statistic of 0.61. SM had shorter median LOS (3 [2-3] vs 3 [2-6], P < .01) and higher rate of discharge home (86% vs 55%, P < .01).
Conclusions: In our population, younger age and higher NIHSS were associated with higher odds of SM diagnosis in patients treated with telemedicine-administered thrombolytics. These variables are insufficient to reliably identify a subgroup of patients evaluated via telemedicine for whom thrombolytics could be withheld. The poor performance of Telestroke Mimic score highlights the need for improved predictive tools. Until larger studies are conducted, telemedicine-administered thrombolytics should adhere to current in-person guidelines.