Discovery and Prediction of Novel Functional Outcome Phenotypes for ARDS

描述（由申请人提供）：在本项目中，我们旨在提高对急性呼吸窘迫综合征（ARDS）后长期功能结局模式（“表型”）的科学理解。ARDS是一种危及生命的肺损伤，通常需要在重症监护病房（ICU）进行机械通气。许多急性呼吸窘迫综合征（ARDS）患者在多个领域存在严重损害，包括身体功能、认知状态和精神健康。对许多患者来说，急性呼吸窘迫综合征（ARDS）后的生存意味着新发病或慢性健康状况恶化，通常影响多个领域。在明显的异质性中，我们假设ARDS幸存者存在不同的亚组或表型。这些表型可能具有不同的潜在生理异常和致病机制；不同表型的患者可能需要不同的治疗方法来改善其整体健康状况。在这个项目中，我们建议在ARDS后6个月发现并预测这些临床表型。利用统计遗传学领域常用的“大数据”分析技术，我们将在ARDS发病后6个月确定幸存者功能结局的表型，然后根据ARDS发病前3天内常规的临床信息推导并验证这种表型的预测模型。在这项工作中，我们将使用研究者独特的预先存在的NHLBI ARDS网络长期结局研究（ALTOS）数据集，这是最大和最全面的ARDS幸存者多中心随访研究。我们预计本研究将有助于a)通过前瞻性识别可能从特定干预中获益最多的相关患者亚组来改进临床试验设计，b)支持针对特定患者亚组制定个性化治疗策略，以及c)提高对ARDS后长期功能结局因果机制的理解。该项目旨在为NHLBI和重症监护学术和专业协会反复强调的研究任务取得重要进展，以提高我们对ARDS后长期功能结局的理解。

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.