An Observational Acute Stroke Model for Decision Support and Comparing Outcomes

描述(由申请人提供)：据估计，每年有超过795,000名美国人中风。在美国，中风仍然是主要的死亡原因，仅次于心血管疾病和癌症；而且是导致长期残疾的主要原因，只有25%的成年人从这种疾病中恢复到正常健康。由于急性中风导致的神经损伤的严重程度通过早期恢复到受影响区域的血流而得到缓解；现在，更多的人通过早期使用溶栓剂和介入性血栓取回设备进行干预，在中风中存活下来。不幸的是，这一领域新药和设备的快速发展使得为特定患者提供治疗指导变得困难，并且缺乏用于比较治疗组之间结果的指标。这项建议的重点是创建一个观察性数据库，随后用于支持急性卒中治疗的影响图。该数据库是以中风及其治疗的统一信息模型的规范为基础的：到目前为止，还没有建立全面的框架来使用标准化表示和/或受控词汇来合并这些变量。我们利用我们机构的当前数据；以及即将通过美国心脏协会(AHA)发布的国家数据集来实例化这个数据库。从该数据库中建立影响图，使用关于患者介绍、病史、成像和可用的治疗药物/设备的信息来计算最大化结果和其他考虑因素(例如，生活质量)的最佳治疗决策。通过推算和倾向得分处理缺失数据的方法被用来帮助计算影响图背后所需的条件概率表。在探索健康结果和成本之间的权衡的过程中，将考虑一系列效用函数。利用数据库和影响图，支持基于病例的相似性检索，从而能够发现相关的过去病例以审查治疗决定和结果；并将其作为定义和比较分组(及其结果)的一种手段。将开发图形用户界面(图形用户界面)，用于查询影响图和执行基于案例的检索。评价的重点是评估影响图相对于已知结果的表现，并与其他传统统计模型(例如，逻辑回归、决策树)进行比较；以及系统对影响决策的整体影响。该R01利用了加州大学洛杉矶分校中风中心在急性中风治疗方面的国家认可的临床专业知识，以及一个长期的医疗信息学研究小组。这一努力的最终结果将是一套信息学驱动的建模工具和一个用于急性中风治疗的数据库。 与公共卫生相关：在美国，中风仍然是主要的死亡原因，仅次于心血管疾病和癌症；而且是导致长期残疾的主要原因，只有25%的成年人从这种疾病中恢复到正常健康。在开发新的溶栓剂和介入性血栓取回设备方面的最新进展正在帮助更多的人通过将神经损伤降至最低来帮助更多的人存活下来；然而，医生们几乎没有指导方针来选择将优化给定个体结果的药物/设备。这项研究的重点是创建一个影响图，它将提供对急性中风的洞察，建立一个工具来帮助关于不同治疗方案的医疗决策。

DESCRIPTION (provided by applicant): Annually, it is estimated that more than 795,000 Americans experience a stroke. Stroke remains a major cause of death in the United States, behind only cardiovascular disease and cancer; and is the leading cause of long- term disability, with only 25% of adults recovering to normal health from this condition. The severity of neurological damage due to an acute stroke is mitigated by the early restoration of blood flow to the affected area; and more people are now surviving strokes through earlier intervention with thrombolytic agents and interventional clot retrieval devices. Unfortunately, the rapid development of new drugs and devices in this area has made it difficult to provide treatment guidance for a given patient, and metrics for comparing outcomes between treatment groups are lacking. This proposal focuses on the creation of an observational database that is subsequently used to support an influence diagram for acute stroke treatment. The database is predicated on the specification of a unified in- formation model for stroke and its treatment: thus far, no comprehensive framework has been established to incorporate these variables using standardized representations and/or controlled vocabularies. We take ad- vantage of current data at our institution; and a forthcoming national dataset through the American Heart Association (AHA) to instantiate this database. From this database, an influence diagram is established, using in- formation on patient presentation, medical history, imaging, and available treatment drugs/devices to compute an optimal treatment decision maximizing outcomes and other considerations (e.g., quality of life). Methods to handle missing data via imputation and propensity scores are used to help compute the required conditional probability tables underlying the influence diagram. A spectrum of utility functions will be considered over the course of this effort to explore the trade-offs between health outcomes and cost. Using the database and influence diagram, case-based similarity retrieval is supported, enabling discovery of related past cases to review treatment decisions and outcomes; and as a means to define and compare subgroups (and their outcomes). A graphical user interface (GUI) for querying the influence diagram and performing case-based retrieval will be developed. Evaluation focuses on assessing the performance of the influence diagram relative to known out- comes and compared to other conventional statistical models (e.g., logistic regression, decision trees); and the overall impact of the system to impact decision-making. This R01 leverages nationally-recognized clinical expertise in acute stroke treatment from the UCLA Stroke Center; as well as a longstanding medical informatics research group. The ultimate result of this effort will be a set of informatics-driven modeling tools and a database for acute stroke treatment. PUBLIC HEALTH RELEVANCE: Stroke remains a major cause of death in the United States, behind only cardiovascular disease and cancer; and is the leading cause of long-term disability, with only 25% of adults recovering to normal health from this condition. Recent progress in the development of new thrombolytic agents and interventional clot retrieval de- vices is helping more people survive strokes by minimizing neurological damage; however, physicians have few guidelines for selecting the drugs/devices that will optimize a given individual's outcomes. The focus of this research is the creation of an influence diagram that will provide insight into acute stroke, establishing a tool to aid medical decision making regarding the different treatment options.