Multi-Center Registry Cohort Study on Prognostic Factors and Prediction Model Construction in Aneurysmal SAH

Официальное название

Multi-Center Registry Cohort Study on Prognostic Factors and Prediction Model Construction in Aneurysmal Subarachnoid Hemorrhage

Обзор

PROSAH-MPC, a collaborative research project among neurosurgical centers in China, focuses on aneurysmal subarachnoid hemorrhage (aSAH). Its aim is to identify prognostic factors and develop robust prediction models for complications, disability, and mortality in aSAH patients. By leveraging a large, multi-center, prospective cohort design, PROSAH-MPC aims to overcome limitations of past studies and provide a more comprehensive understanding of the disease.

Подробное описание

PROSAH-MPC (Prognostic Factors and Prediction Models in Aneurysmal Subarachnoid Hemorrhage Multi-Center Prospective Cohort) is an ambitious research endeavor that brings together a consortium of neurosurgical centers across various regions to comprehensively investigate the complexities of aneurysmal subarachnoid hemorrhage (aSAH). This multi-faceted study aims to unlock the prognostic factors that underpin the outcomes of patients afflicted with this severe and often life-threatening cerebrovascular disorder.

The primary objective of PROSAH-MPC is to construct and validate robust prediction models that can accurately forecast the risks of complications, disability, and mortality in aSAH patients. By leveraging the strengths of a large, multi-center, prospective cohort design, the study aims to overcome the limitations of previous single-center, limited sample size, or retrospective studies, enabling a more holistic and generalizable understanding of the disease.

Central to the study is the collection of extensive clinical and radiological data from enrolled patients, including demographics, medical histories, treatment regimens, radiological features, and follow-up outcomes. Radiomic analysis of imaging data, such as CT and MRI scans, will be employed to extract subtle but crucial features that may predict patient outcomes by deep learning. This data-rich approach ensures that the prediction models are built on a solid foundation of evidence-based knowledge.

PROSAH-MPC's ultimate goal is to transform the way we approach aSAH management by providing clinicians with reliable tools to assess individual patient risks and tailor treatment plans accordingly. The validated prediction models have the potential to enhance early recognition of high-risk patients, facilitate timely interventions, and ultimately improve patient outcomes and quality of life.

Вмешательства

• Диагностический тест Machine Leaning Models
  Area Under the Curve (ROC): Measures the overall performance of the model across all classification thresholds. A higher AUC value indicates better performance. Accuracy: The proportion of correctly predicted outcomes (both positive and negative) out of all predictions made. Precision (Positive Predictive Value, PPV): The proportion of correctly predicted positive outcomes out of all predicted positive outcomes. Sensitivity (True Positive Rate, TPR): The proportion of actual positive outcomes

Первичные конечные точки

• modified Rankin Scale (mRS) for evaluating the prognosis [Срок оценки: 12 months post-event]
• Delayed cerebral ischemia (DCI) [Срок оценки: 30 days post-event]

Вторичные конечные точки (4)

• Rebleeding [Срок оценки: 30 days post-event]
• Intracranial Aneurysm Re-Rupture [Срок оценки: 30 days post-event]
• Hydrocephalus [Срок оценки: 30 days post-event]
• Clearing Rate of Subarachnoid Hemorrhage [Срок оценки: 14 days post-admission CT scan]

Критерии участия

Критерии включения

• Subarachnoid hemorrhage confirmed by computed tomography (CT);
• Cerebral angiography (CTA) and digital subtraction angiography (DSA) examination confirming intracranial aneurysm rupture as the cause of the subarachnoid hemorrhage;
• Blood routine, biochemical function, blood coagulation function, and craniocerebral CT performed within 24 hours of symptom onset;
• Underwent aneurysm clipping by surgery or endovascular embolization within 72 hours after-onset.

Критерии исключения

• Aneurysm rupture bleeding time exceeding 24 hours before hospital admission;
• Incomplete image data or blood test information;
• Long-term use of anticoagulant medications such as aspirin or warfarin;
• Admitted to hospital with active infectious diseases;
• long-term anticoagulant drugs such as aspirin, wave dimensions;
• Presence of other intracranial vascular malformations.

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

• The Second Affiliated Hospital of Nanchang University — Nanchang

Публикации

• Du S, Wu Y, Tao J, Shu L, Yan T, Xiao B, Lv S, Ye M, Gong Y, Zhu X, Hu P, Wu M. Development and Validation of Machine Learning Models for Outcome Prediction in Patients with Poor-Grade Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment. Ther Clin Risk Manag. 2025 Mar 7;21:293-307. doi: 10.2147/TCRM.S504745. eCollection 2025. PMID 40071129
• Shu L, Xiao B, Jiang Y, Tang S, Yan T, Wu Y, Wu M, Lv S, Lai X, Zhu X, Hu P, Ye M. Comparison of LVIS and Enterprise stent-assisted coiling embolization for ruptured intracranial aneurysms: a propensity score-matched cohort study. Neurosurg Rev. 2024 Sep 7;47(1):560. doi: 10.1007/s10143-024-02756-8. PMID 39242449
• Hu P, Wu Y, Yan T, Shu L, Liu F, Xiao B, Ye M, Wu M, Lv S, Zhu X. Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage. J Neurosurg. 2024 Mar 29;141(2):343-354. doi: 10.3171/2024.1.JNS232280. Print 2024 Aug 1. PMID 38552240

Идентификаторы

NCT: NCT05738083 · IIT-O-2023-011

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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