Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Panzhihua Central Hospital | OTHER |
| Zhujiang Hospital | OTHER |
| Southwest Hospital, China | OTHER |
| Renmin Hospital of Wuhan University |
Not provided
Not provided
Not provided
Not provided
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.
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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| aneurysmal subarachnoid hemorrhage | primary subarachnoid hemorrhage caused by intracranial ruputured aneurysm |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Machine Leaning Models | Diagnostic Test | 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 that are correctly identified by the model. Specificity (True Negative Rate, TNR): The proportion of actual negative outcomes that are correctly identified by the model. |
| Measure | Description | Time Frame |
|---|---|---|
| modified Rankin Scale (mRS) for evaluating the prognosis | A score of 3 or greater on the mRS indicates a poor prognosis, with significant disability or dependence on others for daily activities. A score less than 3 indicates a good prognosis, with the patient being able to live independently with minimal or no disability. | 12 months post-event |
| Delayed cerebral ischemia (DCI) | DCI is a common complication after aSAH and refers to a decline in neurological status or the presence of new infarctions on imaging, typically occurring days to weeks after the initial hemorrhage. | 30 days post-event |
| Measure | Description | Time Frame |
|---|---|---|
| Rebleeding | This outcome measures the occurrence of recurrent intracranial hemorrhage from the same or another aneurysm within the study period. | 30 days post-event |
| Intracranial Aneurysm Re-Rupture |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Patients with Aneurysmal Subarachnoid Hemorrhage (aSAH)
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xingen Zhu, Prof | Contact | 13803546020 | zxg2008vip@163.com | |
| Ping Hu, MD | Contact | 13207109734 | hp666edu@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Xingen Zhu, Prof | Second Affiliated Hospital of Nanchang University | Study Chair |
| Qianxue Chen, Prof | Renmin Hospital of Wuhan University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Second Affiliated Hospital of Nanchang University | Recruiting | Nanchang | Jiangxi | 330006 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40071129 | Derived | 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. | |
| 39242449 |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D013345 | Subarachnoid Hemorrhage |
| ID | Term |
|---|---|
| D020300 | Intracranial Hemorrhages |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
Not provided
Not provided
| OTHER |
Not provided
Not provided
Not provided
|
This refers to the re-rupture of the aneurysm that caused the initial aSAH or the rupture of a different aneurysm.
| 30 days post-event |
| Hydrocephalus | Hydrocephalus is the abnormal accumulation of cerebrospinal fluid in the brain's ventricles, leading to their dilation. | 30 days post-event |
| Clearing Rate of Subarachnoid Hemorrhage | This outcome measures the reduction in the volume of subarachnoid hemorrhage over time, quantified using BrainHemoAI software by comparing admission CT scans to subsequent scans (e.g., at discharge or follow-up). | 14 days post-admission CT scan |
| 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. |
| D009422 | Nervous System Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D006470 | Hemorrhage |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |