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Each year, 7.8 million people worldwide experience an ischemic stroke, often caused by atrial fibrillation (AF). AF is a major contributor to severe, disabling, and deadly strokes. About 20% to 30% of ischemic stroke patients have AF before their stroke. Of the remaining 70% to 80% without known arrhythmias, up to 24% are newly diagnosed with AF after intensive cardiac monitoring, totaling 1.3 to 1.5 million new AF cases detected after stroke globally each year. Oral anticoagulants (OACs) can reduce stroke risk related to AF by 64% and lead to milder strokes with lower disability and mortality. Neurologists use cardiac monitoring to detect AF in stroke patients.
This study focuses on patients who have had an ischemic stroke and are newly diagnosed with AF. The goal is to understand how AF progresses over time. The investigators will track changes in AF severity and frequency, monitor biomarkers related to heart health, assess the size and function of the left atrium, and observe new risk factors like hypertension. Patients will be grouped based on their AF diagnosis method: ECG, a portable device recording heart activity for less than 7 days, or one recording for 7 to 30 days.
The investigators hypothesize that AF burden will increase, new risk factors will emerge, biomarkers will rise, and the left atrium will worsen over time. Participants will be followed for up to 24 months with regular assessments. The study aims to provide insights into AF progression in stroke patients, potentially improving treatments and prevention strategies.
Globally, 7.8 million individuals experience an ischemic stroke each year.1, 2 Atrial fibrillation (AF) is one of the most frequent causes of ischemic stroke, resulting in the most severe, disabling, and lethal events.1, 2 Around 20% to 30% of ischemic stroke patients have AF before stroke occurrence.13, 14 Among the remaining 70% to 80% without known arrhythmias, up to 24% can be newly diagnosed with AF after intensive cardiac monitoring (Figure 1), yielding a rough estimate of 1.3 to 1.5 million new cases of AF detected after stroke (AFDAS) globally each year.15-17 Most AFs are diagnosed before a stroke ever occurs. Among persons with additional stroke risk factor, OACs reduce AF-related stroke risk by 64% compared to no treatment.18 Also, patients who have ischemic strokes despite receiving OACs have milder19 and smaller strokes20, resulting in reduced disability21 and mortality21. Neurologists use cardiac monitoring in patients with ischemic stroke to look for AF.
The main goal of this study is to observe and understand how AF progresses over time in patients with AFDAS. Specifically, the investigators aim to track changes in the severity and frequency of AF episodes, monitor biomarkers (substances in the blood that indicate disease) related to heart health, measure changes in the size and function of the left atrium (a chamber of the heart), and analyze changes in risk factors such as new diagnoses of hypertension (high blood pressure). Patients will be grouped based on how their AF was diagnosed: using an electrocardiogram (ECG-based diagnosis), using a portable device that records heart activity for less than 7 days (<7-day Holter monitor), or using a portable device that records heart activity for 7 to 30 days (7-30-day Holter monitor).
The investigators hypothesize that the burden of AF (severity and frequency of AF episodes) will increase over time, risk factors such as newly diagnosed hypertension will emerge, biomarkers indicating heart stress and damage will increase, and the left atrium will show signs of worsening function and increased size. The underlying idea is that patients with initially low AF burden might have a "young" form of AF that gradually worsens, increasing their risk of stroke. Therefore, the investigators will evaluate the progression of AF burden over time. Throughout the study, the investigators will regularly measure AF burden (frequency and severity of episodes), levels of specific biomarkers (e.g., MR-proANP, 0troponin), blood pressure, weight, and development of risk factors. Participants will be followed up to 24 months.
To gather data, the investigators will use recording of AF burden, echocardiography (imaging to assess heart structure and function), plasma biomarkers (blood tests to measure substances indicating heart health), and cardiac CT scans at the beginning and end of the study to assess heart health. This study aims to provide valuable insights into how AF evolves in stroke patients, potentially leading to better treatments and prevention strategies for reducing stroke risk.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Participants with AF Detected After Stroke | Experimental | Participants with AF detected after stroke undergo implantation of an insertable cardiac monitor (loop recorder) for continuous cardiac rhythm monitoring to detect and characterize atrial fibrillation burden, biomarkers, and left atrial characteristics over time. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Implantable Loop Recorder | Device | Patients will be implanted with a loop recorder. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Progression of AF burden | Difference in the total duration of AF during the first quartile of available follow-up compared to the last quartile of follow-up. We hypothesize that AF burden will progress at a different pace in different types of AF: KAF>ECG-AF>PCM-AFDAS. As a sensitivity analysis AF burden will be compared at the first and 12 months of follow-up. | 12-months |
| Total AF burden | Total AF burden We will compare different measures of AF burden between the 3 types of AF: (1) Total AF burden at 3, 6, and 12 months post-ILR insertion (sum of the duration of all AF episodes, HH:MM:SS), (2) Maximum duration of the longest AF episode, (3) Relative AF burden (total AF burden/net monitoring time), (4) AF Pattern (number of AF episodes and time of occurrence), (5) Time to first AF diagnosis (DD:HH), and (6) Other ECG monitoring findings (premature atrial complexes, interatrial block, etc.). Characterizing these measures will allow us to choose the best AF burden definition for a larger RCT. We hypothesize that the burden of AF will be different across types of AF: KAF>ECG-AF>PCM-AFDAS. | 12-months |
| Measure | Description | Time Frame |
|---|---|---|
| Progression of biomarkers | Difference in the levels of biomarkers between the enrollment visit and the visit at 12 months. We hypothesize that baseline biomarker levels and their increase throughout time will differ across AF groups: KAF>ECG-AF>PCM-AFDAS | 12-months |
| Progression in the number of diagnosed risk factors |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Diana Ayan, Pharm MSc | Contact | 519-685-8500 | 35826 | diana.ayan@lhsc.on.ca |
| Jennifer Moussa | Contact | 519-685-8500 | 33110 | jennifer.moussa@lhsc.on.ca |
| Name | Affiliation | Role |
|---|---|---|
| Luciano A Sposato, MD | Western University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Heart and Brain Lab, Western University | Recruiting | London | Ontario | N6A 5A5 | Canada |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25908460 | Background | Yaghi S, Moon YP, Mora-McLaughlin C, Willey JZ, Cheung K, Di Tullio MR, Homma S, Kamel H, Sacco RL, Elkind MS. Left atrial enlargement and stroke recurrence: the Northern Manhattan Stroke Study. Stroke. 2015 Jun;46(6):1488-93. doi: 10.1161/STROKEAHA.115.008711. Epub 2015 Apr 23. | |
| 30958508 | Background | Healey JS, Gladstone DJ, Swaminathan B, Eckstein J, Mundl H, Epstein AE, Haeusler KG, Mikulik R, Kasner SE, Toni D, Arauz A, Ntaios G, Hankey GJ, Perera K, Pagola J, Shuaib A, Lutsep H, Yang X, Uchiyama S, Endres M, Coutts SB, Karlinski M, Czlonkowska A, Molina CA, Santo G, Berkowitz SD, Hart RG, Connolly SJ. Recurrent Stroke With Rivaroxaban Compared With Aspirin According to Predictors of Atrial Fibrillation: Secondary Analysis of the NAVIGATE ESUS Randomized Clinical Trial. JAMA Neurol. 2019 Jul 1;76(7):764-773. doi: 10.1001/jamaneurol.2019.0617. |
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| ID | Term |
|---|---|
| D020521 | Stroke |
| D001281 | Atrial Fibrillation |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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Difference in the levels of biomarkers between the enrollment visit and the visit at 12 months. We hypothesize that number of risk factors will differ across AF groups: KAF>ECG-AF>PCM-AFDAS. |
| 12-months |
| Slow left atrial appendage flow and/or thrombus on follow-up CT Heart | We will assess the presence of slow left atrial appendage flow and/or thrombus on CT imaging of the heart at 1 month and 12 months. If possible, a CT heart will be done at the last follow-up visit beyond 12 months. We hypothesize that the prevalence at baseline, and incidence at the end of follow-up, of slow left atrial appendage flow and/or thrombus will differ across AF groups: KAF>ECG-AF>PCM-AFDAS. | 12-months |
| Left atrial size | We will assess the differences in the size of the left atrium on CT imaging of the heart at 1 month and 12 months. We hypothesize that baseline left atrial size and the progression of LA size will differ across AF groups: KAF>ECG-AF>PCM-AFDAS. | 12-months |
| 30753246 | Background | Vafaie M, Giannitsis E, Mueller-Hennessen M, Biener M, Makarenko E, Yueksel B, Katus HA, Stoyanov KM. High-sensitivity cardiac troponin T as an independent predictor of stroke in patients admitted to an emergency department with atrial fibrillation. PLoS One. 2019 Feb 12;14(2):e0212278. doi: 10.1371/journal.pone.0212278. eCollection 2019. |
| 33982599 | Background | Scheitz JF, Lim J, Broersen LHA, Ganeshan R, Huo S, Sperber PS, Piper SK, Heuschmann PU, Audebert HJ, Nolte CH, Siegerink B, Endres M, Liman TG. High-Sensitivity Cardiac Troponin T and Recurrent Vascular Events After First Ischemic Stroke. J Am Heart Assoc. 2021 May 18;10(10):e018326. doi: 10.1161/JAHA.120.018326. Epub 2021 May 13. |
| 25459239 | Background | Shibazaki K, Kimura K, Aoki J, Sakai K, Saji N, Uemura J. Brain natriuretic peptide level on admission predicts recurrent stroke after discharge in stroke survivors with atrial fibrillation. Clin Neurol Neurosurg. 2014 Dec;127:25-9. doi: 10.1016/j.clineuro.2014.09.028. Epub 2014 Oct 5. |
| 28253498 | Background | Maruyama K, Uchiyama S, Shiga T, Iijima M, Ishizuka K, Hoshino T, Kitagawa K. Brain Natriuretic Peptide Is a Powerful Predictor of Outcome in Stroke Patients with Atrial Fibrillation . Cerebrovasc Dis Extra. 2017;7(1):35-43. doi: 10.1159/000457808. Epub 2017 Mar 2. |
| 26764429 | Background | Kaatz S, Ahmad D, Spyropoulos AC, Schulman S; Subcommittee on Control of Anticoagulation. Definition of clinically relevant non-major bleeding in studies of anticoagulants in atrial fibrillation and venous thromboembolic disease in non-surgical patients: communication from the SSC of the ISTH. J Thromb Haemost. 2015 Nov;13(11):2119-26. doi: 10.1111/jth.13140. No abstract available. |
| 11588306 | Background | Jones WJ, Williams LS, Meschia JF. Validating the Questionnaire for Verifying Stroke-Free Status (QVSFS) by neurological history and examination. Stroke. 2001 Oct;32(10):2232-6. doi: 10.1161/hs1001.096191. |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D001145 | Arrhythmias, Cardiac |
| D006331 | Heart Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |