Risk Factor Assessment for Acute Pulmonary Hypertension Crisis

Официальное название

Research on the Clinical Risk Factor Assessment System for Acute Pulmonary Hypertension Crisis and Its Mortality

Обзор

The goal of this observational study is to learn about pulmonary hypertension crisis (PHC) - a severe, and often fatal complication - in patients with pulmonary hypertension (PH). The main questions this study aims to answer are: What are the clinical and hemodynamic features of PHC, and what underlying pathophysiological mechanisms cause it to develop? Can these features be used to diagnostic PHC, predict who is at risk of developing it or dying from it, and develop targeted prevention and treatment of PHC? A multi-center registry platform and biobank will be established to enroll and follow up patients with PH. Clinical data, hemodynamic measurements, and biological specimen will be collected. Risk prediction and early warning tools of PHC will be developed.

Подробное описание

Pulmonary hypertension crisis (PHC) is a severe and fatal complication of pulmonary hypertension (PH), characterized by the sudden elevation of pulmonary vascular resistance, acute right hear failure and collapse of systemic circulation. However, PHC currently lacks any internationally accepted definition or diagnostic criteria, and it is still unclear which are the clinical, pathophysiological and molecular risk factors of PHC.

This study aims to establish a large clinical cohort of patients with PH, validate the definition of PHC, identify risk factors of PHC occurrence and mortality, and develop tools for the risk-prediction and early-warning of PHC.

This is a multi-center, prospective cohort study with a retrospective component for model training. Following national health-information standards, a standardized registry dataset will be established to cover demographics, clinical features, laboratory tests, imaging, and hemodynamic profile. Existing PH cohort databases will be integrated and expanded to a target of 5,000 patients. A subset of cases with right heart catheter parameters (RHC) will be extracted. A multi-center biospecimen management platform will be established.

For PHC onset, the investigators will assemble a clinical-molecular-imaging feature set and use convolutional neural networks and tree-based algorithms for feature extraction, then build a cross-modal prediction model using multi-task learning, neural networks, and a Transformer architecture. The model will be prospectively validated and tuned against real-world performance. For PHC mortality, models will be built on patients meeting the new PHC criteria, using 28-day attributable death, all-cause death, and long-term death as endpoints. Models will be trained on a retrospective cohort and then evaluated for accuracy and generalizability on both an internal validation set and an external prospective-cohort validation set.

Первичные конечные точки

• Pulmonary hypertension crisis [Срок оценки: From enrollment to 3 years after enrollment]
• 28 day mortality attributed to pulmonary hypertension crisis [Срок оценки: From hospitalization to 28 days]

Вторичные конечные точки (2)

• All cause mortality within hospitalization [Срок оценки: From hospitalization to discharge or documented death, whichever is earlier, assessed up to 3 years]
• All cause mortality within 3 years [Срок оценки: From the diagnosis of pulmonary hypertension crisis to documented death, assessed up to 3 years]

Критерии участия

Критерии включения

• Pulmonary hypertension confirmed by mean pulmonary arterial pressure (mPAP) over 20 mmHg measured by right heart catheter
• At least once per year of follow-up data collection record

Критерии исключения

• Patients with missing baseline or follow-up data
• Complicated by other diseases with significant influence on survival, such as acute coronary syndrome, malignancy, etc.
• Complicated by other diseases with significant influence on hemodynamics, such as sepsis, acute left heart failure, and acute pulmonary embolism, etc.
• Receiving medications with significant influence on hemodynamics

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

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 4 центра

• Guangdong Province People's Hospital — Гуанчжоу
• Yan'an Affiliated Hospital of Kunming Medical University — Куньмин
• Peking Union Medical College Hospital — Пекин
• Shanghai Pulmonary Hospital — Шанхай

Публикации

• Qu J, Li M, Zhang X, Zhang M, Zuo X, Zhu P, Ye S, Zhang W, Zheng Y, Qi W, Li Y, Zhang Z, Ding F, Gu J, Liu Y, Qian J, Huang C, Zhao J, Wang Q, Liu Y, Tian Z, Wang Y, Wei W, Zeng X. A prognostic model for systemic lupus erythematosus-associated pulmonary arterial hypertension: CSTAR-PAH cohort study. Respir Res. 2023 Sep 9;24(1):220. doi: 10.1186/s12931-023-02522-2. PMID 37689662
• Qian J, Li M, Zhang X, Wang Q, Zhao J, Tian Z, Wei W, Zuo X, Zhang M, Zhu P, Ye S, Zhang W, Zheng Y, Qi W, Li Y, Zhang Z, Ding F, Gu J, Liu Y, Wang Y, Zeng X; following investigators were collaborators in the CSTAR-PAH study:. Long-term prognosis of patients with systemic lupus erythematosus-associated pulmonary arterial hypertension: CSTAR-PAH cohort study. Eur Respir J. 2019 Feb 14;53(2):1800081 PMID 30635295
• Hemnes AR, Beck GJ, Newman JH, Abidov A, Aldred MA, Barnard J, Berman Rosenzweig E, Borlaug BA, Chung WK, Comhair SAA, Erzurum SC, Frantz RP, Gray MP, Grunig G, Hassoun PM, Hill NS, Horn EM, Hu B, Lempel JK, Maron BA, Mathai SC, Olman MA, Rischard FP, Systrom DM, Tang WHW, Waxman AB, Xiao L, Yuan JX, Leopold JA; PVDOMICS Study Group. PVDOMICS: A Multi-Center Study to Improve Understanding of Pulmo PMID 29074534
• Boucly A, Song S, Keles M, Wang D, Howard LS, Humbert M, Sitbon O, Lawrie A, Thompson AAR, Frank P, Kivimaki M, Rhodes CJ, Wilkins MR. Clustering Patients with Pulmonary Hypertension Using the Plasma Proteome. Am J Respir Crit Care Med. 2025 Aug;211(8):1492-1503. doi: 10.1164/rccm.202408-1574OC. PMID 40344188

Идентификаторы

NCT: NCT07653958 · K7949 · 2024ZD0526701

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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