Core M: POPULATION PHARMACOLOGY

核心 M：群体药理学

• 批准号: 8126773
• 负责人: BRIAN LESLIE STROM
• 金额: $ 31.14万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8126773
• 关键词: Address; Biological Markers; Blood specimen; Cardiac; Case Study; Collection; Data; Data Sources; Drug user; Genomics; Interview; Medical Records; Molecular Profiling; Myocardial Infarction; Naproxen; Non-Steroidal Anti-Inflammatory Agents; Output; Patients; Population; Process; Prostaglandins; Research; Risk; Risk Factors; Specimen; Study Subject; Testing; Treatment Efficacy; Urine; base; celecoxib; innovation; insight; metabolomics; population based; prospective

Innovation The purpose of this study is to create a rigorous and population-based set of case study subjects admitted with an MI, collected prospectively over 2 years, along with a set of control subjects who have not had an MI. With degree and type of NSAID exposure being such a critical variable, we are proposing prospective subject collection, enabling more accurate recall of recently used NSAIDs as well as an accurate characterization of other known cardiac risk factors based on patient interviews and review of medical records. Urine and blood specimens will be collected on all study subjects. However, after initial processing the analyses of these specimens by the Molecular Profiling Core will be deliberately conducted as determined by the outputs of the other Cores, as described in the Overall Research Strategy, where other studies are intended as hypothesis generating, this study will be poised to be hypothesis testing, building the data and specimen capability to react quickly to the hypotheses emerging from other studies in this core and others.

创新 这项研究的目的是创建一套严格且基于人群的案例研究主题。 MI，前瞻性2年，以及一组没有MI的控制对象。和 NSAID暴露的程度和类型是如此关键的变量，我们提出了预期的主题 收集，使得更准确地召回了最近使用的NSAID以及准确的表征 基于患者访谈和医疗记录审查的其他已知心脏危险因素。尿液和血液 标本将在所有研究对象上收集。但是，在初步处理这些分析之后 通过分子分析核心的标本将被故意执行。 如“整体研究策略”中所述的其他核心，其中其他研究旨在假设 生成，这项研究将有望为假设检验，构建数据和标本能力以反应 迅速地从该核心和其他研究中的其他研究中提出的假设。