Enabling Comparative Effectiveness Research in Silent Brain Infarction Through Natural Language Processing and Big Data

在常规的临床护理过程中，神经影像扫描是一种常见的临床现象 在没有中风或短暂性脑缺血发作病史的患者中发现先前的脑梗塞。的确， 流行病学研究表明，无症状性脑梗塞(SBI)远比中风更常见；MRI- 在约20%的健康老年人中可以检测到明确的SBI。在这些基于筛查患者的研究中， 研究结果已被证明与细微的、通常未被认识到的生理和心理缺陷有关 认知功能。这些影像表现也是未来中风的强烈、独立的危险因素 痴呆症。尽管在接受筛查的人群中，SBI的患病率很高，而且其后果很严重， 当偶然发现时，人们对SBI的意义或适当的管理知之甚少 常规护理。虽然有强有力的证据表明抗血小板治疗和他汀类药物治疗对 预防既往卒中患者的复发，这些结果在多大程度上适用于有 印度国家石油公司目前还不清楚。因为SBI患者定义的人群介于原发和继发之间 中风预防，对这些患者的方法具有不确定性和实践差异，使其成为一种 观察性比较有效性研究的理想条件。尽管如此，仍有严重的 履行机构研究面临的挑战。由于患者没有明显的症状，招募进入试验可能是 这是个问题。关于履行机构的比较有效性研究，使用常规收集的数据并利用 这些患者的护理差异受到以下事实的阻碍，即没有针对SBI的ICD代码，而且 通常不包括在电子健康记录(EHR)的结构化字段中，因为它通常被认为是 偶然发现。为了在很大程度上确定履行机构治疗策略的比较有效性， 对于异质种群，我们建议开发自然语言处理(NLP)算法来识别 通过对神经放射学报告的自动审查，可以帮助患者更好地了解自己的情况。我们已经进行了初步的表演 努力证明这种方法是可行的。然后我们将应用最先进的科学观测技术 在具有链接的EHR和索赔数据的海量数据库中的比较有效性方法，以检查 他汀类药物和抗血小板药物在预防未来中风和痴呆方面的有效性。因此，我们的目标是： 目标1：我们将开发能够准确识别SBI和白质疾病病例的NLP算法 (大规模杀伤性武器)在两个不同的卫生系统。目标2：我们将移植、改进和验证大规模的NLP算法 包括600多家医院和6500家诊所的异类数据库，并确定了一大群 常规发现的SBI和WMD患者。目标3：我们将根据年龄来描述队列的特征- 与以下因素相关的特定的SBI患病率、管理模式以及未来中风和痴呆的风险 履行机构和大规模杀伤性武器。目标4：我们将评估预防性治疗(他汀类药物和他汀类药物)的比较有效性 抗血小板药物)对偶然发现的SBI患者未来中风和痴呆症的风险。

It is a common clinical occurrence that neuroimaging scans obtained in the course of routine clinical care discover a prior brain infarction in patients with no history of stroke or transient ischemic attack. Indeed, epidemiologic studies indicate that silent brain infarctions (SBI) are far more common than strokes; MRI- defined SBI can be detected in ~20% of the healthy elderly. In these studies based on screened patients, the findings have been shown to be associated with subtle, typically unrecognized, deficits in physical and cognitive function. These imaging findings are also strong, independent risk factors for future stroke and dementia. Despite the very high prevalence of SBI in screened populations, and their serious consequences, little is known about the significance or the appropriate management of SBI when discovered incidentally in routine care. While there is strong evidence that antiplatelet therapy and statin therapy are effective in preventing recurrent stroke in patients with prior stroke, the degree to which these results apply to patients with SBI is unclear. Because patients with SBI define a population that falls in between primary and secondary stroke prevention, the approach to these patients is marked by uncertainty and practice variation, making it an ideal condition for observational comparative effectiveness research. Nonetheless, there are serious challenges for the study of SBI. As patients have no overt symptoms, recruitment into a trial can be problematic. Comparative effectiveness research on SBI, using routinely collected data and leveraging the variation in care of these patients, is impeded by the fact that there are no ICD codes for SBI, and it is generally not included in structured fields of electronic health records (EHR) as it is typically considered an incidental finding. In order to establish the comparative effectiveness of treatment strategies for SBI in a large, heterogeneous population, we propose to develop Natural Language Processing (NLP) algorithms to identify individuals with SBI through the automated review of neuroradiology reports. We have performed preliminary work to demonstrate that such an approach is feasible. We will then apply state-of-the-science observational comparative effectiveness methods in a massive database with linked EHR and claims data to examine the effectiveness of statins and antiplatelet agents in preventing future stroke and dementia. Thus, our aims are: Aim 1: We will develop NLP algorithms that can accurately identify cases of SBI and white matter disease (WMD) in two different health systems. Aim 2: We will port, refine, and validate the NLP algorithm in a large heterogeneous database including more than 600 hospitals and 6500 clinics and identify a large cohort of patients with routinely-discovered SBI and WMD. Aim 3: We will characterize the cohort with respect to age- specific prevalence of SBI, management patterns, and the risk of future stroke and dementia associated with SBI and WMD. Aim 4: We will estimate the comparative effectiveness of preventive therapies (statins and antiplatelet agents) on the risk of future stroke and dementia in patients with incidentally-discovered SBI.