Characterizing clinical and biologic features of persistent hypoxemic respiratory failure

持续性低氧性呼吸衰竭的临床和生物学特征

• 批准号: 10690151
• 负责人: Neha Alhad Sathe
• 金额: $ 0.25万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-16 至 2023-05-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10690151
• 关键词: Academic Medical Centers; Acute; Acute Respiratory Distress Syndrome; Acute respiratory failure; Address; Admission activity; Advanced Development; Age; Alveolar; Angiopoietin-2; Apoptosis; Award; Biologic Characteristic; Biological; Biological Factors; Biological Markers; Biological Process; Caring; Classification; Clinical; Clinical Data; Critical Care; Critical Illness; Data; Disease; Doctor of Philosophy; Endothelium; Enrollment; Environment; Epithelial; Event; Funding; Future; Heterogeneity; Hypoxemia; Hypoxemic Respiratory Failure; Inflammation; Injury; Interleukin-6; Investigational Therapies; Knowledge; Learning; Longitudinal cohort; Lung; Measurement; Measures; Mechanical ventilation; Mentored Patient-Oriented Research Career Development Award; Molecular; Molecular Probes; Morbidity - disease rate; National Heart, Lung, and Blood Institute; Outcome; Pathologic; Pathway interactions; Patients; Pharmacology; Phenotype; Plasma; Pneumonia; Population; Prognosis; Prospective cohort; Research; Research Priority; Resource Allocation; Respiratory Failure; Risk; Risk Factors; Scientist; Severity of illness; Syndrome; Testing; Therapeutic; Time; Training; Universities; Washington; Work; acute hypoxemic respiratory failure; biological heterogeneity; career; circulating biomarkers; cohort; cost; endothelial dysfunction; high risk; improved; inflammatory marker; longitudinal analysis; lung injury; machine learning method; male; mortality; mortality risk; new therapeutic target; novel; participant enrollment; patient subsets; predictive modeling; prevent; prognostication; prospective; respiratory; response; sex; skills; targeted treatment; translational physician; treatment response

PROJECT SUMMARY/ABSTRACT Research: Acute hypoxemic respiratory failure (AHRF) requiring mechanical ventilation is a common, costly condition with high mortality, yet treatment remains supportive. Identifying effective targeted therapeutics in heterogeneous conditions like AHRF depends on characterizing subsets, or sub-phenotypes, of patients with high likelihood of disease related events or response to therapy. This project will characterize a novel sub- phenotype called persistent hypoxemic respiratory failure (PHRF) among mechanically ventilated AHRF patients, with PHRF defined by ongoing mechanical ventilation and hypoxemia on ICU day 3. Using clinical trajectory to define sub-phenotypes in other heterogeneous syndromes has helped delineate patients with distinct prognosis and highlight biologic mechanisms contributing to trajectories. With large, independent prospective ICU cohorts from the University of Washington and Vanderbilt University, Dr. Sathe will address the following aims: (1) identify clinical factors on ICU day 1 associated with PHRF (2) determine biologic features of PHRF by analyzing ICU day 1 and day 3 circulating biomarkers of lung injury and (3) develop and validate a multivariable model that predicts PHRF on ICU day 3. Understanding risk factors for PHRF will help hone in on the early mechanisms important for pathologic responses to lung injury. Advantages to sub- phenotyping within AHRF rather than ARDS (where prior efforts were focused) include expanding the scope of patients we target for therapy and improving reliability of study definitions. In addition, discriminating between patients who will and will not develop PHRF will aid clinical prognostication, resource allocation, and targeted trial enrollment of patients unlikely to improve with existing treatment. The results will fill key knowledge gaps prioritized by the NHLBI regarding which factors determine risk for persistent hypoxemia, and the degree to which these factors overlap across ARDS and other conditions in AHRF. Candidate/Environment: With the support of the University of Washington, Dr. Mark Wurfel, Dr. Catherine “Terri” Hough, and biostatistician Leila Zelnick, PhD, this award will help establish Dr. Sathe’s career as a translational physician-scientist practicing Pulmonary and Critical Care. Through the proposed research, she will develop fundamental skills for analysis of longitudinal cohort data, contemporary machine learning methods for prediction, and high-quality measurement and analysis of lung injury biomarkers. This work will identify biologic pathways for more in-depth study in prospective AHRF cohorts, which she will pursue in a future K23. She plans to establish a career examining the heterogeneity of acute respiratory failure and other ICU syndromes, to advance the development of targeted therapeutics for critically ill patients.

项目摘要/摘要 研究：需要机械通气的急性低氧性呼吸衰竭(AHRF)是一种常见的、昂贵的 病死率很高，但治疗仍然是支持性的。确定有效的靶向治疗方法 像AHRF这样的异质性疾病取决于患者亚群或亚表型的特征 与疾病相关的事件或治疗反应的可能性很高。这个项目将描述一种新的亚 机械通气AHRF患者的持续性低氧性呼吸衰竭(PHRF)表型 根据持续机械通气和ICU第3天低氧血症定义的PHRF患者。使用临床 在其他异质综合征中确定亚型的轨迹有助于描绘出患有 明确的预后和突出的有助于轨迹的生物机制。拥有大型的、独立的 来自华盛顿大学和范德比尔特大学的未来ICU队列，Sathe博士将发表演讲 以下目标：(1)确定与PHRF相关的ICU第一天的临床因素(2)确定生物学因素 通过分析ICU第1天和第3天肺损伤的循环生物标志物来分析PHRF的特点 验证预测ICU第3天PHRF的多变量模型。了解PHRF的风险因素将有所帮助 研究肺损伤病理反应的重要早期机制。SUB的优势 在AHRF而不是ARDS(以前的工作重点)中进行表型鉴定包括扩大 我们的治疗目标是患者，并提高研究定义的可靠性。此外，区分 将会和不会发生PHRF的患者将有助于临床预测、资源分配和有针对性的 对现有治疗不太可能改善的患者进行试验招募。结果将填补关键的知识空白 由NHLBI确定哪些因素决定了持续性低氧血症的风险，以及 这些因素在ARDS和AHRF的其他情况下是重叠的。 候选人/环境：由华盛顿大学、Mark Wurfel博士、Catherine博士支持 特里·霍夫和生物统计学家莱拉·泽尔尼克博士，这一奖项将有助于确立萨斯博士作为 转化型内科医生--从事肺部和重症护理的科学家。通过拟议的研究，她 将开发分析纵向队列数据、当代机器学习的基本技能 肺损伤生物标志物的预测方法和高质量的测量和分析。这项工作将 确定生物学途径，以便在未来的AHRF队列中进行更深入的研究，她将在 未来的K23。她计划建立一个研究急性呼吸衰竭和其他疾病的异质性的职业 ICU综合征，以促进危重患者靶向治疗的发展。

项目成果

Alveolar Biomarker Profiles in Subphenotypes of the Acute Respiratory Distress Syndrome.

急性呼吸窘迫综合征亚表型的肺泡生物标志物概况。

• DOI: 10.1097/ccm.0000000000005704
• 发表时间: 2023
• 期刊: Critical care medicine
• 影响因子: 8.8
• 作者: Sathe,NehaA;Morrell,EricD;Bhatraju,PavanK;Fessler,MichaelB;Stapleton,ReneeD;Wurfel,MarkM;Mikacenic,Carmen
• 通讯作者: Mikacenic,Carmen