Electrocardiographic predictors of atrial fibrillation in patients with cryptogenic stroke

Abstract Objective The main objective of our study was to analyze the incidence and predictors of atrial fibrillation (AF) in patients with cryptogenic stroke (CS) who received an implantable cardiac monitor (ICM) at our Institution. Methods From November 2013 to October 2017, a total of 133 patients who had suffered a CS were implanted with an ICM after a thorough screening process. The median time between the thromboembolic event and ICM implantation was 64 days [IQ range: 16–111]. All implanted patients were followed with remote monitoring until the first detected episode of AF or up to December 2018. Every remote monitoring transmission and related electrograms were analyzed by the dedicated Electrophysiology Nursing team and confirmed by experienced Electrophysiologists. AF was defined by any episode lasting greater than or equal to 2 minutes. Results During a median follow-up of 14.8 months [IQ range: 3.0–31.2], AF was detected in 65 out of 133 patients (48.9%). The median time from ICM implantation and AF detection was 3.5 months [IQ range: 0.9–6.7]. The prevalence of AF was 22.6%, 34.4%, 40.8% and 48.3% at 3, 6, 12 and 24 months respectively. At the multivariate analysis, high premature atrial contractions (PAC) burden and left atrium (LA) dilation were the only independent predictors of AF detection (HR 2.82, 95% CI 1.64–4.83, p<0.001 for PAC; HR 1.75, 95% CI 1.03–2.97, p=0.038 for LA dimension). Patients were dived into categories based on the probability of AF detection (low, intermediate and high risk) and a new risk stratification algorithm was implemented (Figure 1). Conclusion After a thorough screening process, AF detection in patients with CS and ILM was quite high. Having a high PAC burden and LA dilation predicted AF episodes at the multivariate analysis. A new risk stratification algorithm was developed. Figure 1 Funding Acknowledgement Type of funding source: None

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Potential Biological Markers of Atrial Fibrillation: A Chance to Prevent Cryptogenic Stroke

BioMed Research International ◽

10.1155/2017/8153024 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 6

Author(s):

István Szegedi ◽

László Szapáry ◽

Péter Csécsei ◽

Zoltán Csanádi ◽

László Csiba

Keyword(s):

Atrial Fibrillation ◽

Biological Markers ◽

Cryptogenic Stroke ◽

Biological Marker ◽

Ecg Monitoring ◽

Inflammation Markers ◽

Good Patient ◽

Markers Of Inflammation ◽

Good Patient Compliance ◽

And Function

Stroke affects millions of people all over the world, causing death and disability. The most frequent type of this disease is ischemic stroke, which can be caused by different factors. In approximately 25 percent of cases, no obvious cause can be found. Recent observations have shown that paroxysmal atrial fibrillation could be responsible for a significant number of cryptogenic stroke events. Short- or long-lasting ECG monitoring could help with the diagnosis of transient arrhythmias. Unfortunately, these techniques either are expensive or require good patient compliance. An alternative option is the identification of biological markers that are specific for atrial fibrillation and can be used to predict arrhythmia. In this review, we give a summary of the recent advances in the research of arrhythmia markers. Based on their structure and function, we differentiated four groups of biomarkers: markers of inflammation, markers of fibrosis, markers with hormonal activity, and other markers. In spite of intensive researches, the optimal biological marker is still not available, but there are some promising markers, like NT-proBNP/BNP.

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B-PO01-028 UTILIZATION OF CARDIAC MONITORING FOR ATRIAL FIBRILLATION IN CRYPTOGENIC STROKE PATIENTS

Heart Rhythm ◽

10.1016/j.hrthm.2021.06.174 ◽

2021 ◽

Vol 18 (8) ◽

pp. S62

Author(s):

Matthew R. Reynolds ◽

Candace L. Gunnarsson ◽

Michael P. Ryan ◽

Sarah Rosemas ◽

Paul D. Ziegler ◽

...

Keyword(s):

Atrial Fibrillation ◽

Cryptogenic Stroke ◽

Cardiac Monitoring ◽

Stroke Patients

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Infarct Topography and Detection of Atrial Fibrillation in Cryptogenic Stroke: Results from CRYSTAL AF

Cerebrovascular Diseases ◽

10.1159/000437018 ◽

2015 ◽

Vol 40 (1-2) ◽

pp. 91-96 ◽

Cited By ~ 35

Author(s):

Richard A. Bernstein ◽

Vincenzo Di Lazzaro ◽

Marilyn M. Rymer ◽

Rod S. Passman ◽

Johannes Brachmann ◽

...

Keyword(s):

Atrial Fibrillation ◽

Cox Regression ◽

Brain Infarction ◽

Cryptogenic Stroke ◽

Monitoring Methods ◽

Brain Images ◽

Kaplan Meier ◽

Imaging Characteristics ◽

Hazard Ratios ◽

Routine Monitoring

Background: Insertable cardiac monitors (ICM) have been shown to detect atrial fibrillation (AF) at a higher rate than routine monitoring methods in patients with cryptogenic stroke (CS). However, it is unknown whether there are topographic patterns of brain infarction in patients with CS that are particularly associated with underlying AF. If such patterns exist, these could be used to help decide whether or not CS patients would benefit from long-term monitoring with an ICM. Methods: In this retrospective analysis, a neuro-radiologist blinded to clinical details reviewed brain images from 212 patients with CS who were enrolled in the ICM arm of the CRYptogenic STroke And underLying AF (CRYSTAL AF) trial. Kaplan-Meier estimates were used to describe rates of AF detection at 12 months in patients with and without pre-specified imaging characteristics. Hazard ratios (HRs), 95% confidence intervals (CIs), and p values were calculated using Cox regression. Results: We did not find any pattern of acute brain infarction that was significantly associated with AF detection after CS. However, the presence of chronic brain infarctions (15.8 vs. 7.0%, HR 2.84, 95% CI 1.13-7.15, p = 0.02) or leukoaraiosis (18.2 vs. 7.9%, HR 2.94, 95% CI 1.28-6.71, p < 0.01) was associated with AF detection. There was a borderline significant association of AF detection with the presence of chronic territorial (defined as within the territory of a first or second degree branch of the circle of Willis) infarcts (20.9 vs. 10.0%, HR 2.37, 95% CI 0.98-5.72, p = 0.05). Conclusions: We found no evidence for an association between brain infarction pattern and AF detection using an ICM in patients with CS, although patients with coexisting chronic, as well as acute, brain infarcts had a higher rate of AF detection. Acute brain infarction topography does not reliably predict or exclude detection of underlying AF in patients with CS and should not be used to select patients for ICM after cryptogenic stroke.

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Sequential approach for the detection of atrial fibrillation in patients with cryptogenic stroke

REC CardioClinics ◽

10.1016/j.rccl.2019.04.001 ◽

2019 ◽

Vol 54 (4) ◽

pp. 224-230

Author(s):

Víctor Expósito ◽

Felipe Rodríguez-Entem ◽

Enrique Palacio ◽

Susana González-Enríquez ◽

María A. Revilla ◽

...

Keyword(s):

Atrial Fibrillation ◽

Cryptogenic Stroke ◽

Sequential Approach

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Abstract P709: Risk Factors Associated With Atrial Fibrillation Detection by Mobile Cardiac Outpatient Telemetry Following Acute Ischemic Stroke

Stroke ◽

10.1161/str.52.suppl_1.p709 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Ovais Inamullah ◽

Alec McConnell ◽

Hussein Al-khalidi ◽

Gerald S Bloomfield ◽

Shreyansh Shah

Keyword(s):

Atrial Fibrillation ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Patient Selection ◽

Left Atrial ◽

Cryptogenic Stroke ◽

Left Ventricular ◽

Stepwise Logistic Regression ◽

Internal Diameter ◽

Atrial Area

Background: Mobile Cardiac outpatient telemetry (MCOT) is often used for patients (pts) with cryptogenic ischemic stroke following hospital discharge to detect atrial fibrillation (AFib) but criteria for patient selection remains a subject of debate. Methods: We identified 297 pts hospitalized with acute ischemic stroke who had an inpatient transthoracic echocardiogram (TTE) and underwent MCOT upon discharge between 2016 and 2018 at a large academic comprehensive stroke center. Pts characteristics between AFib vs. no AFib were compared by Fisher’s exact test for categorical and Wilcoxon rank-sum test for continuous variables. A multivariable stepwise logistic regression model was developed to determine the predictors of AFib detection. Statistical hypotheses were tested as two-sided at 0.05 level of significance. Results: Of the 297 pts, AFib was detected in 24 (8.1%) on 30-day MCOT. Pts with AFib detected were older, white, and have had a larger left atrial area (Table). The final logistic model demonstrated that white race (vs. non-white) (OR 4.86, 1.53-15.41), left atrial area (OR 1.15, 1.05-1.25) and left ventricular internal diameter in diastole (OR 0.33, 0.16-0.67) were associated with AFib detection by MCOT. Conclusion: Although rates of AFib detection on 30-day MCOT post-discharge was low, there are important patient characteristics and TTE features that can improve patient selection. Further studies are needed to determine if this data can be used prospectively to clinically decide which pts with cryptogenic stroke should be given 30-day MCT to detect atrial fibrillation.

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Abstract P624: High Detection of Atrial Fibrillation by 90 Days Textil Holter Monitoring in Patients With Cryptogenic Stroke

Stroke ◽

10.1161/str.52.suppl_1.p624 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Jorge Pagola ◽

Jesus Juega ◽

Jaume Francisco ◽

Maite Rodriguez ◽

Juan Antonio Cabezas ◽

...

Keyword(s):

Atrial Fibrillation ◽

Cumulative Incidence ◽

Left Atrial ◽

Cryptogenic Stroke ◽

Left Atrial Volume ◽

Holter Monitoring ◽

Cardiac Monitoring ◽

Atrial Volume ◽

Monitoring Time ◽

Number Of Patients

Introduction: External recorders allow for low-cost, non-invasive 1 to 4 weeks monitoring. However, the first 3 months of monitoring duration are the most effective to detect atrial fibrillation (AF). We show the results of the Thunder registry of patients monitored to detect AF during 90 days from the stroke. Methods: A prospective observational study was conducted with consecutive inclusion of patients with cryptogenic stroke after work up (neuroimaging, echocardiography and 24-hour cardiac monitoring) in 5 Comprenhensive Stroke Centers. Patients were continuously monitored for 90 days with a wearable Holter (Nuubo®) after the first 24 hours of the stroke onset. We analyzed the percentage of AF detection in each period (percentage of AF among those monitored), the quality of the monitoring (monitoring time), the percentage of AF by intention to monitor (detection of AF among patient included). Demographic, clinical and echocardiographic predictors of AF detection beyond one week of cardiac monitoring were assessed. Results: A total of 254 patients were included. The cumulative incidence of AF detection at 90 days was 34.84%. The monitoring time was similar among the 3 months (30 days: 544.9 hours Vs 60 days: 505.9 hours Vs 90 days: 591.25 hours) (p=0.512). The number of patients who abandoned monitoring was 7% (18/254). The cumulative percentage of intention to detect AF was 30.88% (Figure). Patients who completed monitoring beyond 30 days had higher score on the NIHSS basal scale (NIHSS 9 IQR 2-17) VS (NIHSS 3 IQR 1-9) (p=0.024). Patients with left atrial volume greater than 28.5ml/m2 had higher risk of cumulative incidence of AF according to the Kaplan Meyer curve beyond the first week of monitoring OR 2.72 (Log-rank (Mantel-Cox test) (p<0.001). Conclusions: In conclusion, intensive 90-day- Holter monitoring with textile Holter was feasible and detected high percentage of AF. Enlarged left atrial volume predicted AF beyond the first week of monitoring.

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