Data Management and Statistical Core

数据管理与统计核心

• 批准号: 10641031
• 负责人: HIROKO Hayama DODGE
• 金额: $ 42.36万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10641031
• 关键词: Aged, 80 and over; Alzheimer' s Disease; Alzheimer' s Disease Core Center; Area; Authorization documentation; Award; Biological Markers; Biomedical Engineering; Biometry; Clinical; Collaborations; Communities; Computer software; Consensus; Consultations; Data; Data Coordinating Center; Data Files; Database Management Systems; Databases; Dementia; Detection; Diagnosis; Early Diagnosis; Education; Electronics; Ensure; Fostering; Generations; Goals; Grant; Health Insurance Portability and Accountability Act; Home; Information Distribution; Institutional Review Boards; International; Internet; Intranet; Investigation; Knowledge; Leadership; Mediating; Medical Informatics; Newsletter; Oregon; Play; Procedures; Research; Research Personnel; Research Project Grants; Role; Sampling; Science; Secure; Source; Specific qualifier value; Statistical Data Interpretation; Statistical Models; Structure; Time; Training; aging brain; authority; collaborative environment; data integrity; data management; data sharing; dementia risk; design; digital technology; effective therapy; environmental enrichment for laboratory animals; innovation; meetings; mild cognitive impairment; neuroimaging; neuropathology; novel; outreach; prevent; programs; recruit; repository; response; sensor; success

Project Summary: Data Management and Statistical Core! The Data Management and Statistical Core (DMSC) is aligned to support the overall goal of the Oregon ADRC’s two overarching aims: (1) to focus on early detection of change in order to define mechanisms supporting healthy brain aging and the transition to MCI and early dementia, and (2) to facilitate developing effective therapies to prevent or mediate these transitions. Fostering research directed toward the pre-symptomatic to early MCI spectrum, risk factors of dementia among the oldest old and novel treatments, the OADC’s DMSC supports an array of distinct investigations ranging from statistical modeling of longitudinal biomarker data to real-time change detection through automated in- home activity sensor assessments. These activities advance OADRC research goals directed toward innovation and discovery in the areas of the pre-symptomatic to early Mild Cognitive Impairment (MCI) spectrum, risk factors of dementia among the oldest old and novel treatments. This research is optimally conducted as team science across multiple units, centers and departments including the biomedical engineering and medical informatics departments. In this exceptionally collaborative and interactive environment, the OADRC DMSC is required more than ever to ensure the integrity of the data coming from multiple sources and to provide prompt distribution of customized data files as well as statistically thoughtful and appropriate analyses and consultations for a wide range of researchers. Within this context and in response to the RFA, the DMSC’s Specific Aims are to: 1. Develop and maintain a functional longitudinal research database and share the data 2. Collaborate with the National Alzheimer’s Coordinating Center (NACC) and related centers 3. Provide biostatistical analyses and consultation 4. Provide an enriched environment that increases statistical knowledge for early-stage investigators, trainees and OADC affiliates.

项目摘要：数据管理和统计核心！ 数据管理和统计核心（DMSC）与支持俄勒冈州的总体目标相一致 ADRC的两个首要目标：（1）专注于早期发现变化，以确定机制 支持健康的大脑老化和向MCI和早期痴呆症的过渡，以及（2）促进发展 有效的治疗方法来预防或调解这些转变。 促进针对症状前至早期MCI谱的研究， 作为最古老的古老和新颖的治疗方法，OADC的DMSC支持一系列不同的研究， 从纵向生物标志物数据的统计建模到通过自动化的 家庭活动传感器评估。这些活动推进了OADRC的研究目标， 在症状前至早期轻度认知障碍（MCI）领域的创新和发现 谱，老年痴呆症的危险因素和新的治疗方法。这项研究是最佳的 作为跨多个单位，中心和部门的团队科学进行，包括生物医学 工程和医学信息学系。在这个特别协作和互动的 环境中，OADRC DMSC比以往任何时候都更需要确保来自 多个来源，并提供定制的数据文件以及统计周到的迅速分发 并为广泛的研究人员提供适当的分析和咨询。在这方面， 作为对RFA的回应，DMSC的具体目标是： 1.开发和维护一个功能性纵向研究数据库，并分享数据 2.与国家阿尔茨海默病协调中心（NACC）和相关中心合作 3.提供生物统计分析和咨询 4.提供丰富的环境，增加早期研究人员的统计知识， 学员和OADC附属机构。