Data Management and Statistical Analysis Core (Core C)

数据管理和统计分析核心（核心C）

• 批准号: 10405116
• 负责人: Thomas Glenn Travison
• 金额: $ 42.85万
• 依托单位: HEBREW REHABILITATION CENTER FOR AGED
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10405116
• 关键词: Address; Aging; Algorithms; Alzheimer' s Disease; Area; Biological; Biological Assay; Biological Markers; Biometry; Brain; Cohort Analysis; Cohort Studies; Collaborations; Complex; Data; Data Analyses; Data Analytics; Data Science; Data Security; Data Storage and Retrieval; Databases; Delirium; Dementia; Development; Enrollment; Ensure; Environment; Experimental Designs; Faculty; Funding; Goals; Human Resources; Image; Image Analysis; Incidence; Information Management; Information Resources; Infrastructure; Interview; Leadership; Machine Learning; Maintenance; Manuscripts; Matched Case-Control Study; Medical Records; Metadata; Methodology; Methods; Modeling; Modernization; Multivariate Analysis; Observational Study; Operations Research; Operative Surgical Procedures; Outcome; Participant; Physical Function; Play; Prevention strategy; Procedures; Production; Productivity; Protocols documentation; Publications; Quality Control; Reporting; Reproducibility; Research; Research Design; Research Personnel; Resources; Risk; Role; Safety; Sample Size; Sampling; Schedule; Science; Scientist; Seasons; Secure; Source; Specimen; Standardization; Statistical Data Interpretation; Structure; Supervision; System; Testing; Time; Visit; Work; case control; clinically significant; cognitive development; cognitive function; cognitive reserve; cohort; computing resources; cost effective; data cleaning; data infrastructure; data management; data quality; design; experience; innovation; method development; multiple chronic conditions; novel; operation; participant enrollment; peer support; preservation; programs; safety study; success; therapy development; tool; web-enabled

ABSTRACT The study of delirium, and its relationship to dementia and Alzheimer's Disease, presents distinct quantitative challenges, including elevated risk of participant attrition and confounding of associations via the influences of surgery and multimorbidity. The Data Management and Statistical Analysis (DMSA) Core (Core C) has been developed to address these challenges. The overall goal of the DMSA Core is to provide data management and biostatistical resources and expertise promoting best statistical and scientific practices within this Program Project. DMSA activities are directed toward the three mutually reinforcing Specific Aims: (1) to develop infrastructure for data capture and metadata management; (2) to develop and maintain secure data management infrastructure; and (3) to provide comprehensive statistical and data management support, including novel methods development, to each of the five projects. The DMSA's leadership has substantial expertise in observational studies, experimental design, longitudinal multivariate analysis, biomarker analysis, scale development, machine learning, and missing data, and is seasoned in the leadership of data science teams. Its skilled staff are substantially experienced in the acquisition and management of high quality data, as illustrated by the extremely successful data capture and completeness initiatives developed in the initial funding cycle. Core faculty maintain active and highly productive collaborative relationships with the SAGES investigators. Additionally, the DMSA provides key venues for collaboration, supervision and peer support of its faculty and personnel; maintenance of efficiency and productivity; and surety of quality control around data and analytic issues. The DMSA has embedded continuous innovation in its operations; examples of this innovation include novel scale development for cognitive and physical function; extended matching algorithms in case/control design, and the development of novel and integrated web-enabled data management and analysis tools, which enhance the reproducibility of scientific findings. The DMSA will provide the venue for efficient and cost effective information management and data analysis of the five projects proposed here; the feasibility of this ambitious effort is demonstrated by our success in the initial funding cycle and our well- developed research operations model. This Program Project has tremendous potential to advance the science of delirium, leading ultimately to the development of interventions targeting its incidence and sequelae. Ultimately, this Program Project holds tremendous potential to advance our understanding of delirium, and to develop more effective strategies for prevention and treatment of delirium and associated conditions and complications. The DMSA will play a critical role in its success.

抽象的 对谵妄及其与痴呆和阿尔茨海默氏病的关系的研究提出了不同的定量研究 挑战，包括参与者流失的风险增加以及由于以下因素的影响而混淆协会 手术和多种疾病。数据管理和统计分析 (DMSA) 核心（核心 C）已 为应对这些挑战而开发。 DMSA Core 的总体目标是提供数据管理 以及生物统计资源和专业知识，促进本计划内的最佳统计和科学实践 项目。 DMSA 活动旨在实现三个相辅相成的具体目标：(1) 制定 数据采集​​和元数据管理基础设施； (2) 开发和维护安全数据 管理基础设施； (3) 提供全面的统计和数据管理支持， 包括五个项目中每一个项目的新方法开发。 DMSA 的领导力具有重大意义 观察研究、实验设计、纵向多变量分析、生物标志物分析方面的专业知识， 规模开发、机器学习和缺失数据，并且在数据科学的领导方面经验丰富 团队。其技术精湛的员工在高质量数据的获取和管理方面拥有丰富的经验， 最初开发的极其成功的数据捕获和完整性计划就说明了这一点 资金周期。核心教师与 SAGES 保持积极且高效的合作关系 调查人员。此外，DMSA 为其协作、监督和同行支持提供了重要场所。 教职员工；维持效率和生产力；以及数据和质量控制的保证 分析问题。 DMSA 在其运营中融入了持续创新；这项创新的例子 包括针对认知和身体功能的新颖量表开发；扩展匹配算法 案例/控制设计，以及新颖且集成的网络数据管理和开发 分析工具，提高科学发现的可重复性。 DMSA 将提供场地 对这里提出的五个项目进行高效且具有成本效益的信息管理和数据分析；这 我们在初始融资周期中的成功以及我们良好的 开发了研究运营模型。该计划项目具有推动科学发展的巨大潜力 谵妄的发生率，最终导致针对其发生率和后遗症的干预措施的开发。 最终，这个项目具有巨大的潜力，可以增进我们对谵妄的理解，并 制定更有效的策略来预防和治疗谵妄及相关病症， 并发症。 DMSA 将在其成功中发挥关键作用。