PDF(Pubmed)
Abstract：
UNASSIGNED: Just as failure to diagnose an acute ischemic stroke (AIS) in a timely manner affects the patient\'s outcome; an inaccurate and misplaced impression of the AIS diagnosis is not without its drawbacks. Here, we introduce a two-stage clinical tool to aid in the screening of AIS cases in need of imaging in the emergency department (ED).
UNASSIGNED: This was a multicenter cross-sectional study, in which suspected AIS patients who underwent a brain magnetic resonance imaging (MRI) were included. The 18 variables from nine existing AIS screening tools were extracted and a two-stage screening tool was developed based on expert opinion (stage-one or rule in stage) and multivariate logistic regression analysis (stage-two or rule out stage). Then, the screening performance characteristics of the two-stage mode was evaluated.
UNASSIGNED: Data from 803 patients with suspected AIS were analyzed. Among them, 57.4 % were male, and their overall mean age was 66.9 ± 13.9 years. There were 561 (69.9%) cases with a final confirmed diagnosis of AIS. The total sensitivity and specificity of the two-stage screening model were 99.11% (95% CI: 98.33 to 99.89) and 35.95% (95% CI: 29.90 to 42.0), respectively. Also, the positive and negative predictive values of two-stage screening model were 78.20% (95% CI: 75.17 to 81.24) and 94.57% (95% CI: 89.93 to 81.24), respectively. The area under the receiver operating characteristic (ROC) curve of the two-stage screening model for AIS was 67.53% (95% CI: 64.48 to 70.58). Overall, using the two-stage screening model presented in this study, more than 11% of suspected AIS patients were not referred for MRI, and the error of this model is about 5%.
UNASSIGNED: Here, we proposed a 2-step model for approaching suspected AIS patients in ED for an attempt to safely exclude patients with the least probability of having an AIS as a diagnosis. However, further surveys are required to assess its accuracy and it may even need some modifications.
UNASSIGNED: This was a multicenter cross-sectional study, in which suspected AIS patients who underwent a brain magnetic resonance imaging (MRI) were included. The 18 variables from nine existing AIS screening tools were extracted and a two-stage screening tool was developed based on expert opinion (stage-one or rule in stage) and multivariate logistic regression analysis (stage-two or rule out stage). Then, the screening performance characteristics of the two-stage mode was evaluated.
UNASSIGNED: Data from 803 patients with suspected AIS were analyzed. Among them, 57.4 % were male, and their overall mean age was 66.9 ± 13.9 years. There were 561 (69.9%) cases with a final confirmed diagnosis of AIS. The total sensitivity and specificity of the two-stage screening model were 99.11% (95% CI: 98.33 to 99.89) and 35.95% (95% CI: 29.90 to 42.0), respectively. Also, the positive and negative predictive values of two-stage screening model were 78.20% (95% CI: 75.17 to 81.24) and 94.57% (95% CI: 89.93 to 81.24), respectively. The area under the receiver operating characteristic (ROC) curve of the two-stage screening model for AIS was 67.53% (95% CI: 64.48 to 70.58). Overall, using the two-stage screening model presented in this study, more than 11% of suspected AIS patients were not referred for MRI, and the error of this model is about 5%.
UNASSIGNED: Here, we proposed a 2-step model for approaching suspected AIS patients in ED for an attempt to safely exclude patients with the least probability of having an AIS as a diagnosis. However, further surveys are required to assess its accuracy and it may even need some modifications.
摘要：
未经证实：正如未能及时诊断急性缺血性卒中（AIS）会影响患者的预后一样，AIS诊断的不准确和错误的印象也不是没有缺点。这里,我们引入了一个两阶段的临床工具来帮助在急诊科(ED)筛查需要影像学检查的AIS病例.
未经评估：这是一项多中心横断面研究，纳入接受脑磁共振成像(MRI)检查的疑似AIS患者.从9个现有的AIS筛选工具中提取了18个变量，并根据专家意见（第一阶段或规则阶段）和多变量逻辑回归分析（第二阶段或排除阶段）开发了两阶段筛选工具。然后，评估了两阶段模式的筛选性能特征。
UNASSIGNED：分析了803例疑似AIS患者的数据。其中,57.4%为男性，他们的总体平均年龄为66.9±13.9岁。561例（69.9％）最终确诊为AIS。两阶段筛选模型的总敏感性和特异性分别为99.11％（95％CI：98.33至99.89）和35.95％（95％CI：29.90至42.0），分别。此外，两阶段筛查模型的阳性和阴性预测值分别为78.20%(95%CI:75.17~81.24)和94.57%(95%CI:89.93~81.24),分别。AIS的两阶段筛选模型的受试者工作特征（ROC）曲线下面积为67.53％（95％CI：64.48至70.58）。总的来说,使用本研究中提出的两阶段筛选模型，超过11%的疑似AIS患者未进行MRI检查，该模型的误差约为5%。
未经评估：这里，我们提出了一个2步模型,用于对ED中的疑似AIS患者进行调查,试图安全地排除AIS作为诊断概率最小的患者.然而,需要进一步的调查来评估其准确性，甚至可能需要一些修改。
未经评估：这是一项多中心横断面研究，纳入接受脑磁共振成像(MRI)检查的疑似AIS患者.从9个现有的AIS筛选工具中提取了18个变量，并根据专家意见（第一阶段或规则阶段）和多变量逻辑回归分析（第二阶段或排除阶段）开发了两阶段筛选工具。然后，评估了两阶段模式的筛选性能特征。
UNASSIGNED：分析了803例疑似AIS患者的数据。其中,57.4%为男性，他们的总体平均年龄为66.9±13.9岁。561例（69.9％）最终确诊为AIS。两阶段筛选模型的总敏感性和特异性分别为99.11％（95％CI：98.33至99.89）和35.95％（95％CI：29.90至42.0），分别。此外，两阶段筛查模型的阳性和阴性预测值分别为78.20%(95%CI:75.17~81.24)和94.57%(95%CI:89.93~81.24),分别。AIS的两阶段筛选模型的受试者工作特征（ROC）曲线下面积为67.53％（95％CI：64.48至70.58）。总的来说,使用本研究中提出的两阶段筛选模型，超过11%的疑似AIS患者未进行MRI检查，该模型的误差约为5%。
未经评估：这里，我们提出了一个2步模型,用于对ED中的疑似AIS患者进行调查,试图安全地排除AIS作为诊断概率最小的患者.然而,需要进一步的调查来评估其准确性，甚至可能需要一些修改。
