Cryptogenic Stroke Clinical Trial
Official title:
Cardiac Abnormalities in Stroke Prevention and Risk of Recurrence (CASPR): A Multi-center Observational Cohort Study
This is a multi-center retrospective analysis of consecutive adult patients with cryptogenic stroke patients following a comprehensive workup for the underlying stroke etiology. Patients will be eligible for inclusion if the index stroke event occurred between 1/1/2016 and 06/30/2022.
This is an exploratory observational cohort study of existing registry-based clinical, laboratory, and radiographic data. There are multiple pre-specified hypotheses that will be tested using this data set, which include the entire cohort as well as planned subgroup analyses. The analyses center around patients with cryptogenic stroke (no clear stroke mechanism) but who are characterized by "potential embolic sources". These include but are not limited to: left atrial enlargement or dysfunction, left ventricular dysfunction /heart failure with reduced ejection fraction (HFrEF), patent foramen ovale (PFO), paroxysmal atrial fibrillation (pAF), lambl's excrescence, valvular lesions, carotid web, and nonstenotic cervical arterial plaque. A brief summary of several planned hypothesis is itemized below: 1. To evaluate treatment practices in patients with potential embolic sources. 2. To estimate the risk of recurrent stroke, major bleeding, and/or death following an incident stroke event across various potential embolic sources. 3. To compare rates of recurrent stroke, major bleeding, and/or death across various potential embolic sources, when stratified by antithrombotic treatment type. 4. To evaluate type, frequency, and findings of long-term outpatient cardiac event monitoring (for paroxysmal atrial fibrillation). And furthermore, to determine antithrombotic treatment changes following abnormalities detected with such monitoring. 5. To develop and validate a risk prediction model for later atrial fibrillation in cryptogenic stroke by integrating a machine-learning algorithm or convolutional neural network analysis of 12-lead electrocardiographic data with clinical, laboratory, and radiographic parameters. 6. To develop and validate a risk prediction model for later atrial fibrillation, atrial fibrillation burden, and recurrent stroke and/or death using a machine-learning and/or convolutional neural network and/or validated electrophysiologic biomarkers (e.g., p-wave morphology) abstracted from outpatient telemetry, when added to clinical and radiological patient profiles. 7. To compare the sensitivity of various outpatient cardiac telemetry devices for identifying atrial fibrillation. 8. To evaluate real-world treatment practices of patent foramen ovale closure, antithrombotic therapy in patent foramen ovale, and risk of stroke recurrence. 9. To evaluate real-world secondary stroke prevention strategies in patients with heart failure, with and without left ventricular dysfunction. ;
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