ALI/ARDS Clinical Sub-phenotyping Study

Официальное название

Acute Lung/ Acute Respiratory Distress Syndrome and Extra-pulmonary Organ Injury Clinical Sub-phenotyping Study

Обзор

1. Construct a structured clinical data and biosample information platform for Chinese patients with acute lung injury/ acute respiratory distress syndrome. 2. By deciphering the heterogeneity of patients with acute lung injury/ acute respiratory distress syndrome, achieve clinical, longitudinal physiological, and biological sub-phenotyping to guide individualized precision treatment and improve prognosis.

Подробное описание

Acute lung injury/ acute respiratory distress syndrome is one of the most common and complex critical illnesses in clinical practice, with a high mortality rate of 45% to 50%. Currently, effective therapeutic strategies for this condition are still lacking. Increasing evidence suggests that the significant heterogeneity of this disease plays a crucial role in the poor treatment outcomes and high mortality rates observed in patients. Therefore, this study aims to analyze the heterogeneity of acute lung injury/ acute respiratory distress syndrome patients and establish a clinical classification system for acute lung and extrapulmonary organ injuries.

The objectives of this study include establishing a nationwide clinical database and biobank for acute lung injury / acute respiratory distress syndrome by collecting clinical data and biological samples from various provinces. By overcoming the barriers posed by diverse and heterogeneous data sources, mathematical and machine learning models will be utilized to construct clinical, physiological, and biological classification systems for acute lung and extrapulmonary organ injuries. The proposed classification model will be validated multiple times using international public databases and prospective acute lung injury/acute respiratory distress syndrome cohorts to ensure its stability and generalizability. The mapping relationship between different classifications and patient prognosis as well as treatment responsiveness will be explored.

Moreover, a machine learning-based supervised technique will be applied to develop a bedside simplified model (Point-of-Care model) and establish a bedside clinical classification decision system. Ultimately, this research aims to provide a foundation for standardized and precision-guided clinical diagnostic and therapeutic pathways, promoting improved treatment outcomes and overall prognosis in acute lung injury/ acute respiratory distress syndrome.

Вмешательства

• Процедура Collect peripheral blood and bronchoalveolar lavage fluid
  Peripheral venous blood will be collected and stored from the study participants at a total of five time points: Day 0, Day 1, Day 2, Day 3 after admission to the ICU, and the day of ICU discharge/death. The collection will be conducted after assessing the patients' eligibility for ARDS diagnosis. Each time point will involve the collection of one tube of peripheral venous blood, totaling 5 mL per sample. Within 24 hours after patients' admission to the ICU and meeting the assessment criteria f

Первичные конечные точки

• ICU mortality [Срок оценки: up to 12 weeks]
• hospital mortality [Срок оценки: up to 24 weeks]

Вторичные конечные точки (4)

• 28 days without mechanical ventilation [Срок оценки: up to 28 days]
• length of stay in the ICU [Срок оценки: up to 12 weeks]
• Total length of hospital stay [Срок оценки: up to 24 weeks]
• Mortality at 1 year after discharge [Срок оценки: through study completion, an average of 1 year]

Критерии участия

Критерии включения

• Meet the diagnostic criteria for Acute Respiratory Distress Syndrome (ARDS) according to the updated global definition in 2023.
• The patient or their legal representative signs an informed consent form.

Критерии исключения

• Individuals aged less than 18 years old.
• Those who refuse to participate in the study.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 1 центр

• Jingen Xia — Пекин

Публикации

• Thompson BT, Chambers RC, Liu KD. Acute Respiratory Distress Syndrome. N Engl J Med. 2017 Aug 10;377(6):562-572. doi: 10.1056/NEJMra1608077. No abstract available. PMID 28792873
• Huang X, Zhang R, Fan G, Wu D, Lu H, Wang D, Deng W, Sun T, Xing L, Liu S, Wang S, Cai Y, Tian Y, Zhang Y, Xia J, Zhan Q; CHARDSnet group. Incidence and outcomes of acute respiratory distress syndrome in intensive care units of mainland China: a multicentre prospective longitudinal study. Crit Care. 2020 Aug 20;24(1):515. doi: 10.1186/s13054-020-03112-0. PMID 32819400
• Reilly JP, Calfee CS, Christie JD. Acute Respiratory Distress Syndrome Phenotypes. Semin Respir Crit Care Med. 2019 Feb;40(1):19-30. doi: 10.1055/s-0039-1684049. Epub 2019 May 6. PMID 31060085
• Shah FA, Meyer NJ, Angus DC, Awdish R, Azoulay E, Calfee CS, Clermont G, Gordon AC, Kwizera A, Leligdowicz A, Marshall JC, Mikacenic C, Sinha P, Venkatesh B, Wong HR, Zampieri FG, Yende S. A Research Agenda for Precision Medicine in Sepsis and Acute Respiratory Distress Syndrome: An Official American Thoracic Society Research Statement. Am J Respir Crit Care Med. 2021 Oct 15;204(8):891-901. doi: 1 PMID 34652268
• Calfee CS, Delucchi K, Parsons PE, Thompson BT, Ware LB, Matthay MA; NHLBI ARDS Network. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014 Aug;2(8):611-20. doi: 10.1016/S2213-2600(14)70097-9. Epub 2014 May 19. PMID 24853585

Идентификаторы

NCT: NCT06123962 · 2022YFC2504401

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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