Understanding Response Shift in Acute Respiratory Distress Syndrome (ARDS) survivors

了解急性呼吸窘迫综合征 (ARDS) 幸存者的反应转变

• 批准号: 9925813
• 负责人: Alison Turnbull
• 金额: $ 17.08万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-12 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9925813
• 关键词: Acute; Acute respiratory failure; Address; Adult Respiratory Distress Syndrome; Advisory Committees; Age; American; Anxiety; Area; Big Data to Knowledge; Characteristics; Chest; Climacteric; Clinical Research; Clinical Trials Design; Cognitive; Cohort Studies; Critical Care; Data; Data Element; Data Science; Data Set; Doctor of Philosophy; Educational workshop; Enrollment; Epidemiological trend; Epidemiologist; Epidemiology; Evaluation; Exhibits; Funding; Future; Goals; Grant; Hospital Mortality; Impaired health; Impairment; Individual; Intensive Care Units; Intervention; Intervention Studies; K-Series Research Career Programs; Knowledge; Learning; Longitudinal Studies; Machine Learning; Measures; Mechanical ventilation; Mental Health; Methodology; Methods; Modernization; National Heart, Lung, and Blood Institute; Operative Surgical Procedures; Outcome; Outcome Study; Patient-Focused Outcomes; Patients; Perceived quality of life; Phase; Physiological; Pilot Projects; Population; Population Sciences; Positioning Attribute; Preparation; Professional Organizations; Prospective cohort study; Psychosocial Factor; Psychosocial Influences; Publishing; Quality of life; Recommendation; Recovery; Recovery of Function; Reporting; Research; Research Personnel; Research Priority; Scientist; Self Care; Site; Social support; Societies; Socioeconomic Status; Source; Survivors; Techniques; Time; Training; United States National Institutes of Health; analytical tool; career; cohort; comorbidity; cost; design; expectation; experience; functional disability; health data; health related quality of life; improved; innovation; insight; intervention cost; lung injury; novel; patient expectation; patient subsets; prospective; resilience; response; satisfaction; sex; skills; statistical and machine learning; survivorship; therapy design; trait; working group

Project Summary / Abstract Acute respiratory distress syndrome (ARDS) is a severe lung injury usually requiring mechanical ventilation in an intensive care unit (ICU). While the number of ICU patients requiring mechanical ventilation is steadily increasing, in-hospital mortality is declining, creating a growing population of ARDS survivors. Such survivorship comes at a high “cost,” with ARDS patients frequently experiencing new or worsening physical, cognitive, and/or mental health impairments that last for years after ARDS. NHLBI and professional societies identify improving quality of life for ARDS survivors as a key research priority. Some ARDS survivors may adapt to new impairments over time and report improving quality of life not explained by improvements in objective measures of their physical, cognitive, and mental health. This adaptation phenomenon is known as “response shift.” We hypothesize that ARDS survivors demonstrate widely varying degrees of response shift, and that patients' baseline characteristics prior to ARDS have important associations with the magnitude of response shift after ICU discharge. We also investigate how psychosocial factors, including trait anxiety, social support, resilience, and survivor expectations for functional recovery, impact quality of life during recovery as a first step toward designing and evaluating new interventions for ARDS survivors. This proposal will exploit a unique, pre-existing cohort of very well-characterized ARDS survivors from the NHLBI ARDS Network Long Term Outcome Study (ALTOS) containing hundreds of data elements per patient. Using modern data science methods, I will empirically evaluate the association between baseline patient characteristics and response shift between 6 and 12 months after ARDS [Aim 1], and identify the changes in specific aspects of physical, cognitive, and mental health, from among ~165 candidate measures, that best predict changes in quality of life [Aim 2]. To investigate how psychosocial factors impact quality of life, I will conduct a new, prospective, ICU cohort study of ARDS survivors to collect data for these novel analyses [Aim 3]. The results from these three Aims will generate new knowledge regarding empirically-derived, testable hypotheses about important determinants of quality of life, and provide essential data for designing future studies of interventions aimed at improving the quality of life of ARDS survivors. This career development award provides training in data science, patient outcomes-oriented clinical research, and machine learning statistical techniques for the applicant who is a PhD-trained epidemiologist without these skills. Immediate, short-term, and long-term career goals include: (1) publishing results of the proposed research, (2) successfully competing for R-level funding to explore whether addressing psychosocial issues, including setting appropriate patient expectations for recovery, is a potentially modifiable, low-cost intervention to improve ARDS survivor's quality of life, and (3) becoming an NHLBI-funded independent research scientist who conducts innovative and methodologically rigorous data science research on ARDS outcomes.

项目总结/摘要 急性呼吸窘迫综合征（ARDS）是一种严重的肺损伤，通常需要机械通气， 重症监护室（ICU）。虽然需要机械通气的ICU患者数量稳步增加， 增加，住院死亡率下降，造成越来越多的ARDS幸存者。这样的生存 具有高“成本”，其中ARDS患者经常经历新的或恶化的身体、认知和/或 在ARDS后持续数年的心理健康损害。NHLBI和专业协会确定改善 ARDS幸存者的生活质量作为一个关键的研究重点。一些ARDS幸存者可能会适应新的 随着时间的推移，报告生活质量的改善不能用客观措施的改善来解释 他们的身体认知和心理健康这种适应现象被称为“反应转移”。我们 假设ARDS幸存者表现出不同程度的反应变化， ARDS前的基线特征与ARDS后的反应变化幅度有重要的相关性。 ICU出院。我们还调查了心理社会因素，包括特质焦虑，社会支持，弹性， 和幸存者对功能恢复的期望，影响恢复期间的生活质量， 为ARDS幸存者设计和评估新的干预措施。 这项提案将利用一个独特的，预先存在的非常明确的ARDS幸存者队列， NHLBI ARDS网络长期结局研究（阿尔托斯），包含数百个数据元素， 病人使用现代数据科学方法，我将根据经验评估基线患者 ARDS后6至12个月的特征和反应变化[目的1]，并确定 身体、认知和心理健康的具体方面，从165个候选指标中， 预测生活质量的变化[目标2]。为了研究心理社会因素如何影响生活质量，我将 对ARDS幸存者进行一项新的、前瞻性的ICU队列研究，以收集这些新分析的数据[目的 3]。从这三个目标的结果将产生新的知识， 关于生活质量的重要决定因素的假设，并为设计未来的研究提供必要的数据 旨在改善ARDS幸存者生活质量的干预措施。 该职业发展奖提供数据科学培训，以患者结果为导向的临床 研究和机器学习统计技术的申请人谁是博士培训的流行病学家 没有这些技能。近期、短期和长期的职业目标包括：（1）发表 拟议的研究，（2）成功地竞争R级资金，以探讨是否解决心理社会问题 问题，包括设定适当的患者康复期望，是一个潜在的可修改的，低成本的 改善ARDS幸存者生活质量的干预措施，（3）成为NHLBI资助的独立研究 对ARDS结果进行创新和方法严谨的数据科学研究的科学家。