Discovery and Prediction of Novel Functional Outcome Phenotypes for ARDS

ARDS 新功能结果表型的发现和预测

基本信息

批准号：
8748032
负责人：
Samuel Morris Brown
金额：
$ 10.92万
依托单位：
IHC HEALTH SERVICES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-07-18 至 2016-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8748032
关键词：
Address Adopted Adult Respiratory Distress Syndrome Affect Americas Asthma BMP8 Gene Big Data Categories Cessation of life Chronic Clinical Clinical Trials Clinical Trials Design Cognitive Complex Critical Care Data Data Set Development Disability phenotype Disabled Persons Disease Enrollment Foundations Genetic Genomics Goals HIV Infections Health Health Status Heterogeneity Impairment Incidence Individual Inflammatory Intensive Care Units Intervention Knowledge Life Lung Measures Mechanical ventilation Mental Health Modeling Morbidity - disease rate National Heart, Lung, and Blood Institute Outcome Outcome Study Outcomes Research Pancreatitis Pathway Analysis Patients Pattern Phenotype Physical Function Physiological Pneumonia Psyche structure Public Health Randomized Research Research Personnel Sampling Societies Solid Subgroup Survivors Techniques Testing United States National Institutes of Health Weight Work base bone morphogenetic protein 7 clinical phenotype cohort design disability experience follow-up functional outcomes improved lung injury malignant breast neoplasm member mortality novel prospective public health relevance therapy design trait treatment strategy

项目摘要

DESCRIPTION (provided by applicant): In this project, we aim to improve the scientific understanding of patterns ("phenotypes") of long-term functional outcomes after Acute Respiratory Distress Syndrome (ARDS). ARDS is a life-threatening lung injury that commonly requires mechanical ventilation in an intensive care unit (ICU). Many patients survive ARDS with substantial impairments across multiple domains, including physical functioning, cognitive status, and mental health. For many patients, survival after ARDS represents a new-onset or worsening chronic health condition often affecting multiple domains. Within the apparent heterogeneity, we hypothesize that there are distinct subgroups or phenotypes of ARDS survivors. Those phenotypes may have different underlying physiological abnormalities and causative mechanisms; patients with different phenotypes may require different therapies to improve their overall health status. In this project, we propose to discover and then predict such clinical phenotypes at six months after ARDS. Using novel adaptations of "big data" analytic techniques frequently applied in the field of statistical genetics, we will identify phenotypes of survivors' functional outcomes at 6 months after ARDS and then derive and validate a prediction model for such phenotypes based on clinical information routinely available within the first 3 days of ARDS onset. For this work, we will use the investigators' unique pre-existing dataset of the NHLBI ARDS Network Long Term Outcome Study (ALTOS), the largest and most comprehensive multi-center follow-up study of ARDS survivors. We anticipate that this research will assist with a) improving clinical trial design through prospective identification of relevant patient subgroups who may benefit most from a specific intervention, b) supporting development of personalized treatment strategies for specific patient subgroups, and c) improving understanding of causal mechanisms for long-term functional outcomes after ARDS. This project aims to make important advancement towards a research mandate, repeatedly emphasized by the NHLBI and critical care academic and professional societies, of improving our understanding of long-term functional outcomes after ARDS.

描述（由申请人提供）：在本项目中，我们旨在改善急性呼吸遇险综合征（ARDS）后长期功能结果模式的科学理解（“表型”）。 ARDS是一种威胁生命的肺损伤，通常需要在重症监护病房（ICU）中进行机械通气。许多患者在多个领域，包括身体功能，认知状况和心理健康，在各个领域的障碍中幸存下来。对于许多患者而言，ARDS后的生存代表了一种新的或恶化的慢性健康状况，通常会影响多个领域。在明显的异质性中，我们假设ARDS幸存者有不同的亚组或表型。这些表型可能具有不同的潜在生理异常和致病机制。具有不同表型的患者可能需要不同的疗法来改善其整体健康状况。在这个项目中，我们建议在ARDS六个月后发现并预测此类临床表型。使用经常在统计遗传学领域应用的“大数据”分析技术的新型适应，我们将在ARDS后6个月的6个月内确定幸存者功能结果的表型，然后在ARDS发作的前3天内基于临床信息提供此类表型的预测模型。对于这项工作，我们将使用研究人员对NHLBI ARDS网络长期结果研究（ALTOS）的独特既有数据集，这是ARDS幸存者的最大，最全面的多中心后续研究。我们预计这项研究将有助于a）通过前瞻性鉴定相关的患者亚组来改善临床试验设计，这些患者亚组可能受益于特定干预措施，b）支持针对特定患者亚组的个性化治疗策略的发展，c）提高对ARDS后长期功能的因果机制的理解。该项目旨在使NHLBI和重症监护学术和专业社会一再强调的研究任务迈出重要的进步，以提高我们对ARDS之后的长期功能结果的理解。