Machine Learning Identification of Modifiable Access Barriers in Acute Ischemic Stroke: A Multimodal "Digital Phenotyping" Approach
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 发起方
- 入组人数
- 250
- 试验地点
- 1
- 主要终点
- Correlation of SABI Score with Infarct Core Volume (The Biological Anchor)
研究概览
简要总结
This study aims to identify and quantify the non-clinical barriers (social, transport, and knowledge-based) that delay patient arrival at the hospital during an Acute Ischemic Stroke. By utilizing a multimodal approach that combines a validated patient questionnaire (SABI Tool), Geographic Information Systems (GIS) analysis, and biological markers (infarct volume), the investigators seek to develop a Machine Learning model capable of predicting high-risk phenotypes for pre-hospital delay. The ultimate goal is to validate "Social Determinants of Health" against objective biological outcomes.
详细描述
Despite advances in stroke reperfusion therapies (thrombectomy and thrombolysis), pre-hospital delays remain the primary cause of preventable disability. Current triage systems rely heavily on clinical severity scales but fail to account for Social Determinants of Health (SDOH) that dictate onset-to-door times.
This is a prospective, observational, single-center cohort study designed to validate the "Stroke Access Barrier Identification" (SABI) tool using a "Triangulation Strategy."
The study employs three distinct data sources:
Subjective: Administration of the SABI questionnaire to assess cognitive, physical, and structural barriers.
Geospatial (Objective): Network-based GIS analysis to calculate precise drive-time isochrones and public transit density, validating patient reports of transport difficulty.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Diagnosis of Acute Ischemic Stroke (AIS) confirmed by neuroimaging (CT or MRI). Age $\geq$ 18 years. Presentation to the Emergency Department within 7 days of symptom onset (to ensure recall accuracy).
- •Patient or Legally Authorized Representative (LAR) able to provide informed consent.
- •Verifiable residential address (required for GIS analysis).
排除标准
- •In-hospital stroke onset. Stroke mimics (e.g., seizure, complex migraine, hypoglycemia). Hemorrhagic stroke. Homelessness or lack of fixed address (precludes geospatial analysis). Severe aphasia or cognitive deficit without an available surrogate/caregiver to complete the questionnaire.
结局指标
主要结局
Correlation of SABI Score with Infarct Core Volume (The Biological Anchor)
时间窗: Baseline (Admission Imaging)
To validate if subjective barriers correlate with objective physiological damage. The total score on the SABI questionnaire (Scale 0-100, higher scores indicate higher barriers) will be correlated with the admission Infarct Core Volume (measured in milliliters via automated CT-Perfusion software).
次要结局
- Predictive Accuracy of ML Model for "High-Risk" Delay(Baseline through Study Completion (12 months))
- Agreement between Subjective Transport Barriers and GIS Metrics(Baseline)
- Functional Outcome (mRS) at 90 Days(90 Days post-discharge)
研究者
Ossama Mansour
Prof of Neurology and Neuroradiology Alexandria university
Middle East North Africa Stroke and Interventional Neurotherapies Organization