Duke University School of Medicine, Durham, North Carolina.
Department of Medicine (Neurology), Duke University Medical Center, Durham, North Carolina.
J Stroke Cerebrovasc Dis. 2014 May-Jun;23(5):910-8. doi: 10.1016/j.jstrokecerebrovasdis.2013.07.034. Epub 2013 Oct 8.
The aim of this study was to develop an adjunctive, peripheral biomarker test to differentiate ischemic strokes, intracranial hemorrhages (ICHs), and stroke mimics in the acute setting.
Serum samples were collected from 167 patients who presented with an acute neurologic deficit within 24 hours of symptom onset. Patients were adjudicated to ischemic stroke, ICH, and mimic pathology groups based on clinical and radiographic findings. Samples were tested for levels of 262 potential markers. A multivariate Cox proportional hazards regression model of 5 biomarkers was built by stepwise selection and validated by bootstrapping. Its discriminative capacity was quantified by C index and net reclassification improvement (NRI).
The final model consisted of eotaxin, epidermal growth factor receptor, S100A12, metalloproteinase inhibitor-4, and prolactin. It demonstrated a discriminative capacity for ischemic stroke versus mimic (C = .92), ischemic stroke and ICH versus mimic (C = .93), and ischemic stroke versus ICH (C = .82). The inclusion of biomarkers to a model consisting of age, race, and gender resulted in an NRI of 161% when detecting ischemic stroke versus mimic (P < .0001), an improvement of 171% when detecting ischemic strokes plus ICH versus mimic (P < .0001), and an improvement of 56% when detecting ischemic strokes versus ICH (P = .1419).
These results suggest that information obtained from a 5-biomarker panel may add valuable information in the early evaluation and management of patients with stroke-like symptoms.
本研究旨在开发一种辅助性的外周生物标志物检测方法,以在急性发病期区分缺血性脑卒中、颅内出血(ICH)和脑卒中样发作。
从 167 例在症状发作后 24 小时内出现急性神经功能缺损的患者中采集血清样本。根据临床和影像学检查结果,将患者判定为缺血性脑卒中、ICH 和脑卒中样发作的病理组。对 262 种潜在标志物的水平进行了检测。通过逐步选择构建了一个包含 5 种生物标志物的多变量 Cox 比例风险回归模型,并通过自举法进行验证。通过 C 指数和净重新分类改善(NRI)来量化其判别能力。
最终的模型包括嗜酸性粒细胞趋化因子、表皮生长因子受体、S100A12、金属蛋白酶抑制剂-4 和催乳素。它显示出区分缺血性脑卒中与脑卒中样发作(C 指数=0.92)、缺血性脑卒中与 ICH 与脑卒中样发作(C 指数=0.93)以及缺血性脑卒中与 ICH(C 指数=0.82)的能力。在包含年龄、种族和性别等因素的模型中加入生物标志物后,当检测缺血性脑卒中与脑卒中样发作时,NRI 为 161%(P<0.0001),当检测缺血性脑卒中与 ICH 与脑卒中样发作时,NRI 为 171%(P<0.0001),当检测缺血性脑卒中与 ICH 时,NRI 为 56%(P=0.1419)。
这些结果表明,从一个 5 种生物标志物面板获得的信息可能在早期评估和管理具有脑卒中样症状的患者中提供有价值的信息。