Impact of Atrial Fibrillation Prediction Model on Prescribing Oral Anti-Coagulation in Patients With Cryptogenic Stroke
Prediction of Atrial Fibrillation in Patients With Embolic Stroke of Unknown Source
Stroke is a major cause of disability and the second leading cause of death in adults. Some strokes are linked to atrial fibrillation (AF), a type of irregular heartbeat. When AF is found, doctors usually prescribe blood-thinning medicines to help prevent another stroke. If AF is not found, patients are usually treated with antiplatelet medicines, such as aspirin.
However, AF can be difficult to detect. Because of this, doctors may not know which treatment is best.
Our research team has developed computer programs that analyze a normal electrocardiogram (EKG) and predict whether a person may develop AF in the future. These programs have been shown to be highly accurate.
The goal of this study is to see how sharing these prediction results affects treatment decisions made by patients who have had an embolic stroke of undetermined source (ESUS) and their neurologist. An ESUS is a type of stroke where the exact cause cannot be identified.
Participants in the study will have their normal EKG analyzed using the prediction program. Researchers will then evaluate whether providing these results to the neurologist influences decisions about the patient's care.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Patients presenting to outpatient or inpatient stroke services or to the inpatient cardiac procedure unit for implantation of implantable cardiac monitor at the hospitals of UPMC and who have suffered an ischemic stroke without overt clinical etiology will be considered for participation in this clinical trial. The research coordinator for the trial will screen the inpatient services and outpatient clinics and will verify that any prospective subject meets all the inclusion and none of the exclusion criteria. Once this information is ascertained, the investigator, research coordinator, or both will approach the patient to explain the rationale of the study and its requirements after a clinician known to the participant has obtained their permission to be approached. After signing written informed consent, patients will be enrolled into the study whereby the normal sinus rhythm EKG will be analyzed using the novel machine learning method to assess the patient's risk for developing AF in the following year. Participants will undergo standard of care monitoring on an outpatient basis which includes initially a wearable monitor and then an implantable monitor if the wearable monitor does not reveal AF. If any monitoring reveals AF, then the patients will be on anticoagulation, as indicated in any patient with stroke and AF. This information will be shared with the treating neurologist.
Once a patient is enrolled, their baseline normal EKG will be analyzed using the machine learning algorithm and their risk category for developing AF will be determined. The results which are classified into low, intermediate, and high risk will be presented to the stroke team. The stroke specialists will then share these risk prediction data with their patient for shared decision-making regarding anticoagulation strategy -- oral anticoagulation (OAC) vs. Aspirin. When the information from the novel learning method is shared with the treating neurologist or stroke specialist, the research team will remind them that this is a research tool and has not been fully validated.
The machine learning algorithm, referred to for research purposes as the UPMC AF Prediction Model, was developed under STUDY20030038. The algorithm performance was tested and validated on more than 26,000 patients, 23% of whom developed AF over the course of one year after their original normal EKG. The algorithm performance shows an area under the Receiver Operating Characteristic curve of 0.800 with an F1 score of 0.42. Accordingly, the risk groups in the study were defined as follows, after consultation with stroke specialists:
A. Low risk group, based on a negative predictive value of 97.5% (i.e., only 2.5% of patients classified as low risk will develop AF over 1-year of follow-up) B. High risk group, based on a positive predictive value of 30% (i.e., 30% of patients classified as high risk will develop AF over 1-year of follow-up) C. Intermediate risk group, which will include patients who do not belong in either of the two previous risk groups
Patients will be followed up for 90 days for clinical events. Follow-up at 30 and 90 days will consist of phone calls and review of electronic health records. The rate of use of OAC will be assessed at 30 and 90 days in each AF risk category.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Samir Saba, MD
- Phone Number: 412-647-2762
- Email: sabas@upmc.edu
Study Locations
-
-
Pennsylvania
-
Pittsburgh, Pennsylvania, United States, 15213
- UPMC
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Patient presenting with embolic stroke of unclear source.
- Age at least 18 years.
- Patients will be enrolled within 30 days of stroke.
Exclusion Criteria:
- Prior history of AF
- Stroke can be attributed to cancer, hypercoagulable state, or large artery non-stenotic plaque
- Contraindication to OAC or antiplatelet therapy, including the presence of hemorrhagic stroke
- Patient is already on OAC
- Patient had prior procedure or surgery to exclude or excise the left atrial appendage
- Patient unable or unwilling to provide written informed consent to participate in research
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: UPMC AF Prediction Model
Patients presenting to outpatient or inpatient stroke services or to the inpatient cardiac procedure unit for implantation of implantable cardiac monitor at the hospitals of UPMC and who have suffered an ischemic stroke without overt clinical etiology will be considered for participation in this trial. Once a patient is enrolled, their baseline normal EKG will be analyzed using the machine learning algorithm and their risk category for developing AF will be determined. The results, which are classified into low, intermediate, and high risk, will be presented to the stroke team. The stroke specialists will then share these risk prediction data with their patient for shared decision-making regarding anticoagulation strategy (OAC vs. Aspirin). Patients will be followed up for 90 days for clinical events. Follow-up at 30 and 90 days will consist of phone calls and review of electronic health records. The rate of use of OAC will be assessed at 30 and 90 days in each AF risk category. |
Enrolled patients' baseline normal EKG will be analyzed using the UPMC AF Prediction Model and their risk category for developing AF will be determined. The results, which are classified into low, intermediate, and high risk, will be presented to the stroke team. The stroke specialists will then share these risk prediction data with their patient for shared decision-making regarding anticoagulation strategy (OAC vs. Aspirin). Patients will be followed up for 90 days for clinical events. Follow-up at 30 and 90 days will consist of phone calls and review of electronic health records. The rate of use of OAC will be assessed at 30 and 90 days in each AF risk category. |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Rates of Prescribing OAC versus Antiplatelet Agent
Time Frame: From enrollment until assessment at 90 days
|
The primary endpoint of this trial is the rates of prescribing OAC versus antiplatelet agent after 30 days and after 90 days of patient enrollment, and before any diagnosis of AF is made. In the unlikely event that a patient is diagnosed with AF in the first 30 days after enrollment, their OAC status before the AF diagnosis is made will be recorded and used as the primary endpoint. Patients will be followed up for a total of 90 days for clinical events. All follow-up visits will consist of phone calls and review of electronic health records. The rate of use of OAC will be assessed at 90 days in each AF risk category. |
From enrollment until assessment at 90 days
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Samir Saba, MD, University of Pittsburgh
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- STUDY25100011
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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