Predictors of newly diagnosed atrial fibrillation in cryptogenic stroke: a cohort study

Stroke as the index presentation of traditional cardiovascular risk factors and Human Immunodeficiency Virus in a South African population

OBJECTIVES

We sought to identify what proportion of each cardiovascular risk factor and Human Immunodeficiency Virus (HIV) was first diagnosed at the time of stroke, compared to those that were diagnosed prior to the event, and to explore if this had any impact on the severity of stroke.

METHODS

Adult patients presenting with a new stroke to a quaternary hospital in Johannesburg between 2014 and 2017 were prospectively recruited. Patients were investigated for undiagnosed traditional cardiovascular risk factors (hypertension, diabetes mellitus, dyslipidaemia, atrial fibrillation, obesity and smoking), as well as HIV infection. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS).

RESULTS

346 patients were included. Stroke was the index presentation for at least one risk factor in 199 (57.5 %) patients. Dyslipidaemia was newly diagnosed in 76.0 % of all dyslipidaemics (95 out of 125). Newly-diagnosed dyslipidaemia was associated with a more severe neurological deficit (Median NIHSS of 12 (8-16) vs 7 (4-12), p=0.0007) and younger age on presentation (53 (44-63) years vs 62 (51-71) years, p=0.02) as compared to previously-diagnosed dyslipidaemia.

CONCLUSIONS

More than half of patients had previously undiagnosed modifiable risk factors at the time of their stroke. Dyslipidaemia was undiagnosed in a very high proportion, and this was associated with a higher stroke severity and younger age of presentation.

Undiagnosed major risk factors in acute ischaemic stroke patients: frequency, profile, stroke mechanisms and outcome

BACKGROUND AND PURPOSE

There is scarce clinical information about the clinical profile of patients with acute ischaemic stroke with previously undiagnosed major vascular risk factors (UMRFs).

METHODS

This was a retrospective analysis of data from the Acute Stroke Registry and Analysis of Lausanne registry between 2003 and 2018 with univariate and multivariate logistic regression analyses comparing clinical profiles of patients with UMRFs to patients with at least one previously diagnosed MRF (DMRF).

RESULTS

In all, 4354 patients (median age 70 years [interquartile range 15.2], 44.7% female) were included after excluding 763 (14.9%) for lack of consent and three for missing information. Amongst 1125 (25.8%) UMRF patients, 69.7% (n = 784) had at least one newly diagnosed MRF and the others none. The newly detected MRFs were dyslipidaemia (61.4%), hypertension (23.7%), atrial fibrillation (10.2%), diabetes mellitus (5.2%), ejection fraction <35% (2.0%) and coronary disease (1.0%). Comparing UMRF patients to DMRF patients, multivariate analysis showed a positive association with lower age, non-Caucasian ethnicity, contraceptive use (<55 years old), smoking (≥55 years old) and patent-foramen-ovale-related stroke mechanism. A negative association was found with pre-stroke antiplatelet use and higher body mass index. Functional outcome did not differ. Cerebrovascular recurrences were similar between groups.

CONCLUSIONS

In this large single-centre cohort, 69.7% of patients with acute ischaemic stroke and UMRF were newly diagnosed with at least one new MRF, the most common being dyslipidaemia, hypertension or atrial fibrillation. Patients of the UMRF group were younger, more often smokers and on contraceptives, and had more patent-foramen-ovale-related strokes.

Atrial fibrillation and stroke: State-of-the-art and future directions

Atrial fibrillation (AF) and stroke remain a major cause of morbidity and mortality. The two conditions shared common co-morbidities and risk factors. AF-related strokes are associated with worse clinical outcomes and higher mortality compared to non-AF-related. Early detection of AF is vital for prevention. While various scores have been developed to predict AF in such a high-risk group, they are yet to incorporated into clinical guidelines. Novel markers and predictors of AF including coronary and intracranial arterial calcification have also been studied. There are also ongoing debates on the management of acute stroke in patients with AF, and those who experienced breakthrough stroke while on oral anticoagulants. We provided an overview of the complex interplay between AF and stroke, as well as the treatment and secondary prevention of stroke in AF. We also comprehensively discussed the current evidence and the ongoing conundrums, and highlighted the future directions on the topic.

Atrial fibrillation in embolic stroke of undetermined source: role of advanced imaging of left atrial function

AIMS

Atrial fibrillation (AF) is detected in over 30% of patients following an embolic stroke of undetermined source (ESUS) when monitored with an implantable loop recorder (ILR). Identifying AF in ESUS survivors has significant therapeutic implications, and AF risk is essential to guide screening with long-term monitoring. The present study aimed to establish the role of left atrial (LA) function in subsequent AF identification and develop a risk model for AF in ESUS.

METHODS AND RESULTS

We conducted a single-centre retrospective case-control study including all patients with ESUS referred to our institution for ILR implantation from December 2009 to September 2019. We recorded clinical variables at baseline and analysed transthoracic echocardiograms in sinus rhythm. Univariate and multivariable analyses were performed to inform variables associated with AF. Lasso regression analysis was used to develop a risk prediction model for AF. The risk model was internally validated using bootstrapping. Three hundred and twenty-three patients with ESUS underwent ILR implantation. In the ESUS population, 293 had a stroke, whereas 30 had suffered a transient ischaemic attack as adjudicated by a senior stroke physician. Atrial fibrillation of any duration was detected in 47.1%. The mean follow-up was 710 days. Following lasso regression with backwards elimination, we combined increasing lateral PA (the time interval from the beginning of the P wave on the surface electrocardiogram to the beginning of the A' wave on pulsed wave tissue Doppler of the lateral mitral annulus) [odds ratio (OR) 1.011], increasing Age (OR 1.035), higher Diastolic blood pressure (OR 1.027), and abnormal LA reservoir Strain (OR 0.973) into a new PADS score. The probability of identifying AF can be estimated using the formula. Model discrimination was good [area under the curve (AUC) 0.72]. The PADS score was internally validated using bootstrapping with 1000 samples of 150 patients showing consistent results with an AUC of 0.73.

CONCLUSION

The novel PADS score can identify the risk of AF on prolonged monitoring with ILR following ESUS and should be considered a dedicated risk stratification tool for decision-making regarding the screening strategy for AF in stroke.

Risk Stratification Tools to Guide a Personalized Approach for Cardiac Monitoring in Embolic Stroke of Undetermined Source

Current recommendations support a personalized sequential approach for cardiac rhythm monitoring to detect atrial fibrillation after embolic stroke of undetermined source. Several risk stratification scores have been proposed to predict the likelihood of atrial fibrillation after embolic stroke of undetermined source. This systematic review aimed to provide a comprehensive overview of the field by identifying risk scores proposed for this purpose, assessing their characteristics and the cohorts in which they were developed and validated, and scrutinizing their predictive performance. We identified 11 risk scores, of which 4 were externally validated. The most frequent variables included were echocardiographic markers and demographics. The areas under the curve ranged between 0.70 and 0.94. The 3 scores with the highest area under the curve were the Decryptoring (0.94 [95% CI, 0.88-1.00]), newly diagnosed atrial fibrillation (0.87 [95% CI, 0.79-0.94]), and AF-ESUS (Atrial Fibrillation in Embolic Stroke of Undetermined Source) (0.85 [95% CI, 0.80-0.87]), of which only the latter was externally validated. Risk stratification scores can guide a personalized approach for cardiac rhythm monitoring after embolic stroke of undetermined source.

Prediction of underlying atrial fibrillation in patients with a cryptogenic stroke: results from the NOR-FIB Study

BACKGROUND

Atrial fibrillation (AF) detection and treatment are key elements to reduce recurrence risk in cryptogenic stroke (CS) with underlying arrhythmia. The purpose of the present study was to assess the predictors of AF in CS and the utility of existing AF-predicting scores in The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study.

METHOD

The NOR-FIB study was an international prospective observational multicenter study designed to detect and quantify AF in CS and cryptogenic transient ischaemic attack (TIA) patients monitored by the insertable cardiac monitor (ICM), and to identify AF-predicting biomarkers. The utility of the following AF-predicting scores was tested: AS5F, Brown ESUS-AF, CHA₂DS₂-VASc, CHASE-LESS, HATCH, HAVOC, STAF and SURF.

RESULTS

In univariate analyses increasing age, hypertension, left ventricle hypertrophy, dyslipidaemia, antiarrhythmic drugs usage, valvular heart disease, and neuroimaging findings of stroke due to intracranial vessel occlusions and previous ischemic lesions were associated with a higher likelihood of detected AF. In multivariate analysis, age was the only independent predictor of AF. All the AF-predicting scores showed significantly higher score levels for AF than non-AF patients. The STAF and the SURF scores provided the highest sensitivity and negative predictive values, while the AS5F and SURF reached an area under the receiver operating curve (AUC) > 0.7.

CONCLUSION

Clinical risk scores may guide a personalized evaluation approach in CS patients. Increasing awareness of the usage of available AF-predicting scores may optimize the arrhythmia detection pathway in stroke units.

Use of the insertable Holter with remote detection in the etiological diagnosis of cryptogenic stroke: Analysis of 73 patients

INTRODUCTION

Cryptogenic stroke constitutes 25% of all ischemic strokes, of which 20-30% are due to atrial fibrillation (AF). With the aim of increasing the detection rate, implantable long-term monitoring devices have emerged. The study of the profile of the ideal candidate subsidiary to such monitoring would provide a better understanding of the mechanisms underlying this subtype of stroke.

OBJECTIVE

To determine which variables are related and can predict the detection of silent AF in patients with cryptogenic stroke.

PATIENTS AND METHODS

This is a longitudinal cohort with recruitment from March 2017 to May 2022. They are patients with an implantable monitoring device and cryptogenic stroke with a minimum monitoring of one year.

RESULTS

The total number of patients included was 73, with a mean age of 58.8 years, 56.2% were male. AF was detected in 21 patients (28.8%). The most frequent cardiovascular risk factors were hypertension (47.9%) and dyslipidemia (45.2%). The most frequent topography was cortical (52%). Regarding the echocardiographic parameters, 22% had a dilated left atrium, 19% had a patent foramen ovale, and 22% had high-density supraventricular tachycardia (>1%) on Holter monitoring. In the multivariate analysis, the only variable that predicts AF is the presence of high-density supraventricular tachycardia, with an area under the curve of 0.726 (CI 0.57-0.87, p=0.04), sensitivity of 47.6%, specificity of 97.5%, positive predictive value of 90.9%, negative predictive value of 78.8%, and accuracy of 80.9%.

CONCLUSIONS

The presence of high-density supraventricular tachycardia can be indicative for predicting silent AF. No other variables have been observed that allow us to predict detection of AF in these patients.

Probability of Cardioembolic vs. Atherothrombotic Pathogenesis of Cryptogenic Strokes in Older Patients

Some clinical, laboratory, ECG, and echocardiographic parameters could provide useful indications to assess the probability of cardioembolism or atherothrombosis in cryptogenic strokes. We retrospectively examined 290 patients with ischemic stroke aged ≥60 years, divided into 3 groups: strokes originating from large artery atherothrombosis (n = 92), cardioembolic strokes caused by paroxysmal atrial fibrillation (n = 88) and cryptogenic strokes (n = 110). In addition to echocardiographic and routine clinical-laboratory variables, neutrophil:lymphocyte ratio, red blood cell distribution width, mean platelet volume, P wave and PR interval duration and biphasic inferior P waves, both on admission and after 7 to 10 days, were also considered. By multiple logistic regression, cardioembolic strokes were compared with large artery atherothrombosis strokes, and beta coefficients were rounded to produce a scoring system. Late PR interval ≥188 ms, left atrium ≥4 cm, left ventricular end-diastolic volume <65 ml, and posterior circulation syndrome were associated with paroxysmal atrial fibrillation (positive scores). In contrast, male gender, hypercholesterolemia, and initial platelet count ≥290 × 10⁹/L were associated with atherothrombosis of large arteries (negative scores). The algebraic sum of these scores produced values indicative of cardioembolism if >0 (positive predictive value 89.1%), or of atherothrombosis, if ≤0 (positive predictive value 72.5%). The area under the receiver operating characteristic curve was 0.85. Among cryptogenic strokes, 41.5% had a score >0 (probable atrial fibrillation) and 58.5% had a score ≤0 (possible atherothrombosis). In conclusion, a scoring system based on electrocardiogram, laboratory, clinical and echocardiographic parameters can provide useful guidance for further investigations and secondary prevention in older patients with cryptogenic stroke.

Post-Stroke Detection of Subclinical Paroxysmal Atrial Fibrillation in Patients With Embolic Stroke of Undetermined Source in the Real World Practice: The Empoli ESUS Atrial Fibrillation (E 2 AF) Study

BACKGROUND

Subclinical paroxysmal atrial fibrillation (AF) is one of the main occult causative mechanisms of embolic stroke of undetermined source (ESUS). Aim of this study was to identify AF predictors, and to develop a score to predict the probability of AF detection in ESUS.

METHODS

We retrospectively analyzed ESUS patients undergoing 2-week external electrocardiographic monitoring. Patients with and without AF detection were compared. On the basis of multivariate analysis, predictors of AF were identified and used to develop a predictive score, which was then compared with other existing literature scores.

RESULTS

Eighty-two patients, 48 females, mean age±SD 72±10 years, were included. In 36 patients (43.9%) AF was detected. The frequency of age 75 years or above and arterial hypertension, and the median CHA 2 DS 2 -VASc score were significantly higher in patients with AF compared with those without. National Institutes of Health Stroke Scale (NIHSS) score ≥8 was the only independent variable associated with AF detection. We derived the Empoli ESUS-AF (E 2 AF) score (NIHSS ≥8 5 points, arterial hypertension 3 points, age 75 years or above 2 points, age 65 to 74 years 1 point, history of coronary/peripheral artery disease 1 point, left atrial enlargement 1 point, posterior lesion 1 point, cortical or cortical-subcortical lesion 1 point), whose predictive power in detecting AF was good (area under the curve: 0.746, 95% confidence interval: 0.638-0.836) and higher than that of CHA 2 DS 2 -VASc and other scores.

CONCLUSIONS

In our study NIHSS score ≥8 was the only independent predictor of post-ESUS-AF detection. The E 2 AF score appears to have a good predictive power for detecting AF. External validations are required.

Atrial fibrillation and stroke

INTRODUCTION

Stroke is one of the leading causes of mortality and morbidity globally. Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. It is set to reach epidemic proportions. AF is associated with a five-fold increase in risk of stroke. Strokes caused by AF more often are fatal or result in severe disability. Even though the incidence of stroke has been significantly reduced by oral anticoagulation, AF is thought to account for a significant proportion of cryptogenic strokes where no etiology is identified.

AREAS COVERED

This article reviews the literature related to AF and stroke, pathophysiological insights, diagnosis of AF in stroke patients, and its management (Graphical Abstract).

EXPERT OPINION

The pathophysiology of thrombogenesis that links AF and stroke is not well understood and is an area of active research to identify new therapeutic targets to prevent AF and stroke. As the nature of AF and stroke is multifaceted, an integrated care approach to managing AF and stroke is increasingly essential.

Long-Term Cardiac Monitoring After Embolic Stroke of Undetermined Source: Search Longer, Look Harder

Embolic stroke of undetermined source (ESUS) represents a heterogeneous subgroup of patients with cryptogenic stroke, in which despite an extensive diagnostic workup the cause of stroke remains uncertain. Identifying covert atrial fibrillation among patients with ESUS remains challenging. The increasing use of cardiac implanted electronic devices (CIED), such as pacemakers, implantable defibrillators, and implantable loop recorders (ILR), has provided important information on the burden of subclinical atrial fibrillation. Accumulating evidence indicate that long-term continuous monitoring, especially in selected patients with ESUS, significantly increases the possibility of atrial fibrillation detection, suggesting it may be a cost-effective tool in secondary stroke prevention. This review summarizes available evidence related to the use of long-term cardiac monitoring and the use of implantable cardiac monitoring devices in patients with ESUS.

Predictors of Atrial Fibrillation Development in Patients With Embolic Stroke of Undetermined Source: An Analysis of the RE-SPECT ESUS Trial

BACKGROUND

A proportion of patients with embolic stroke of undetermined source have silent atrial fibrillation (AF) or develop AF after the initial evaluation. Better understanding of the risk for development of AF is critical to implement optimal monitoring strategies with the goal of preventing recurrent stroke attributable to underlying AF. The RE-SPECT ESUS trial (Randomized, Double-Blind Evaluation in Secondary Stroke Prevention Comparing the Efficacy and Safety of the Oral Thrombin Inhibitor Dabigatran Etexilate Versus Acetylsalicylic Acid in Patients With Embolic Stroke of Undetermined Source) provides an opportunity to assess predictors for developing AF and associated recurrent stroke.

METHODS

RE-SPECT ESUS was a randomized, controlled trial (564 sites, 42 countries) assessing dabigatran versus aspirin for the prevention of recurrent stroke in patients with embolic stroke of undetermined source. Of 5390 patients enrolled and followed for a median of 19 months, 403 (7.5%) were found to develop AF reported as an adverse event or using cardiac monitoring per standard clinical care. Univariable and multivariable regression analyses were performed to define predictors of AF.

RESULTS

In the multivariable model, older age (odds ratio for 10-year increase, 1.99 [95% CI, 1.78-2.23]; P<0.001), hypertension (odds ratio, 1.36 [95% CI, 1.03-1.79]; P=0.0304), diabetes (odds ratio, 0.74 [95% CI, 0.56-0.96]; P=0.022), and body mass index (odds ratio for 5-U increase, 1.29 [95% CI, 1.16-1.43]; P<0.001) were independent predictors of AF during the study. In a sensitivity analysis restricted to 1117 patients with baseline NT-proBNP (N-terminal prohormone of brain natriuretic peptide) measurements, only older age and higher NT-proBNP were significant independent predictors of AF. Performance of several published predictive models was assessed, including HAVOC (AF risk score based on hypertension, age ≥75 years, valvular heart disease, peripheral vascular disease, obesity, congestive heart failure, and coronary artery disease) and CHA₂DS₂-VASc (stroke risk score based on congestive heart failure, hypertension, age ≥75 years [doubled], diabetes, previous stroke, transient ischemic attack or thromboembolism [doubled], vascular disease, age 65 to 74 years, and sex category [female]) scores, and higher scores were associated with higher rates of developing AF.

CONCLUSIONS

Besides age, the most important variable, several other factors, including hypertension, higher body mass index, and lack of diabetes, are independent predictors of AF after embolic stroke of undetermined source. When baseline NT-proBNP was available, only older age and elevation of this biomarker were predictive of subsequent AF. Understanding who is at higher risk of developing AF will assist in identifying patients who may benefit from more intense, long-term cardiac monitoring. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02239120.

[Remote monitoring of implantable monitors : Towards coverage ? Evaluation of the procedure by the French National Authority for Health]

Implantable cardiac monitors are recommended and reimbursed in two specific cases: the etiological diagnosis of unexplained recurrent syncope and the etiological diagnosis of a cryptogenic ischemic stroke. According to the French National Authority for Health (HAS), remote monitoring "leads to early diagnosis and therapeutic care". However, remote tracking of these devices for diagnostic purposes is not included in the ETAPES program, which will end soon. This article presents a summary of the evaluation by HAS of the remote monitoring of implantable cardiac monitors. It also addresses the question of its reimbursement, as for therapeutic implantable devices.

Use of risk scores for predicting new atrial fibrillation after ischemic stroke or transient ischemic attack-A systematic review

BACKGROUND

Newly detected atrial fibrillation (NDAF) following an ischemic stroke or transient ischemic attack is often paroxysmal in nature. While challenging to detect, extended electrocardiographic (ECG) monitoring is often used to identify NDAF which has resource implications. Prognostic risk scores have been derived which may stratify the risk of NDAF and inform patient selection for ECG monitoring approaches after ischemic stroke/transient ischemic attack.

AIM

The overall aim was to identify risk scores that were derived and/or validated to predict NDAF after ischemic stroke/transient ischemic attack and evaluate their performance.

SUMMARY OF REVIEW

A systematic literature review was undertaken in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, with application of the Quality Assessment of Diagnostic Accuracy-2 tool. Published studies, which derived and validated clinical risk scores in patients with ischemic stroke/transient ischemic attack, or externally validated an existing score to predict NDAF after ischemic stroke/transient ischemic attack, were considered and independently screened by two reviewers. Twenty-one studies involving 23 separate cohorts were analyzed from which 17 integer-based risk scores were identified. The overall frequency of NDAF was 9.7% (95% confidence intervals 8%-11.5%; I²= 98%). The performance of the scores varied widely among derivation and validation cohorts (area under the receiver operating characteristic curve (AUC) 0.54-0.94); scores derived from stroke cohorts (12 scores) appeared to perform better (AUC 0.7-0.94) than those derived from non-stroke cohorts (five scores; AUC 0.53-0.79). The scores also varied considerably in their complexity, ascertainment, component variables, participant characteristics, outcome definition, and ease of application limiting their generalizability and utility.

CONCLUSION

Overall, the risk scores identified performed variably in their discriminative ability and the utility of these scores to predict NDAF in clinical practice remains uncertain. Further studies are required using larger prospective cohorts and randomized control trials to evaluate the usefulness of such scores for clinical decision making and preventative intervention.

Identification of patients with embolic stroke of undetermined source and low risk of new incident atrial fibrillation: The AF-ESUS score

Background and aims

Only a minority of patients with Embolic Stroke of Undetermined Source (ESUS) receive prolonged cardiac monitoring despite current recommendations. The identification of ESUS patients who have low probability of new diagnosis of atrial fibrillation (AF) could potentially support a strategy of more individualized allocation of available resources and hence, increase their diagnostic yield. We aimed to develop a tool that can identify ESUS patients who have low probability of new incident AF.

Methods

We performed multivariate stepwise regression in a pooled dataset of consecutive ESUS patients from three prospective stroke registries to identify predictors of new incident AF. The coefficient of each independent covariate of the fitted multivariable model was used to generate an integer-based point scoring system.

Results

Among 839 patients (43.1% women, median age 67.0 years) followed-up for a median of 24.3 months (2999 patient-years), 125 (14.9%) had new incident AF. The proposed score assigns 3 points for age ≥ 60 years; 2 points for hypertension; −1 point for left ventricular hypertrophy reported at echocardiography; 2 points for left atrial diameter >40 mm; −3 points for left ventricular ejection fraction <35%; 1 point for the presence of any supraventricular extrasystole recorded during all available 12-lead standard electrocardiograms performed during hospitalization for the ESUS; −2 points for subcortical infarct; −3 points for the presence of non-stenotic carotid plaques. The rate of new incident AF during follow-up was 1.97% among the 42.3% of the cohort who had a score of ≤0, compared to 26.9% in patients with > 0 (relative risk: 13.7, 95%CI: 5.9--31.5). The area under the curve of the score was 84.8% (95%CI: 79.9--86.9%). The sensitivity and negative predictive value of a score of ≤0 for new incident AF during follow-up were 94.9% (95%CI: 89.3--98.1%) and 98.0% (95%CI: 95.8--99.3%), respectively.

Conclusions

The proposed AF-ESUS score has high sensitivity and high negative predictive value to identify ESUS patients who have low probability of new incident AF. Patients with a score of 1 or more may be better candidates for prolonged automated cardiac monitoring.

Clinical trial registration

URL: https://www.clinicaltrials.gov / Unique identifier: NCT02766205.

Characteristics and outcomes of Embolic Stroke of Undetermined Source according to stroke severity

Background and aims

Patients with embolic strokes of undetermined source (ESUS) usually present with mild symptoms. We aimed to compare the baseline characteristics between mild and severe ESUS, identify predictors for severe ESUS, and assess outcomes of patients with severe ESUS.

Methods

In the AF-ESUS (AF-ESUS) dataset, we stratified ESUS severity using the median National Institutes of Health Stroke Scale (NIHSS) score on admission as cut-off. We performed multivariable stepwise regression analyses to identify independent predictors of severe ESUS and to assess the association between ESUS severity and stroke recurrence, death, and new incident atrial fibrillation (AF) on follow-up. The 10-year cumulative probabilities of outcome incidence were estimated by the Kaplan–Meier product limit method.

Results

In 772 patients (median NIHSS: 6 (interquartile range: 3–12)), 414 (53.6%) patients had severe ESUS (i.e. NIHSS ≥6). Female sex was the only independent predictor for severe ESUS (odds ratio: 1.72 (1.27–2.33)). The rates of recurrence (3.3%/year vs. 3.4%/year, adjusted-hazard ratio: 1.09 (0.73–1.62)) and new incident AF (13.5% vs. 17.0%, adjusted odds ratio: 0.67 (0.44–1.03)) were similar between severe and mild ESUS, but mortality was higher (5.4%/year vs. 3.7%/year, adjusted-hazard ratio: 1.51 (1.05–2.16)) in severe ESUS. The 10-year cumulative probability for stroke recurrence was similar between severe and mild ESUS (38.1% (29.2–48.6) vs. 36.6% (27.8–47.0), log-rank test: 0.01, p = 0.920). The 10-year cumulative probability of death was higher in patients with severe ESUS compared with mild ESUS (40.5% (32.5–50.0) vs. 34.0% (26.0–43.6) respectively; log-rank test: 4.54, p = 0.033).

Conclusions

Women have more severe ESUS compared with men. Patients with severe ESUS have similar rates of stroke recurrence and new incident AF, but higher mortality compared with mild ESUS.

Usefulness of the ACTEL Score to Predict Atrial Fibrillation in Patients with Cryptogenic Stroke

INTRODUCTION

To assess the probability of undetected atrial fibrillation (AF) in patients with ischemic stroke, we previously compared patients who were first diagnosed with AF with patients with large or small artery disease and obtained the MrWALLETS 8-item scoring system. In the present study, we utilized cryptogenic strokes (CS) as the control group, as AF is normally sought among CS patients.

METHODS

We retrospectively examined 191 ischemic stroke patients (72.5 ± 12.6 years), 68 with first diagnosed AF and 123 with CS, who had undergone 2 brain CT scans, echocardiography, carotid/vertebral ultrasound, continuous electrocardiogram monitoring and anamnestic/laboratory search for cardiovascular risk factors.

RESULTS

In logistic regression, 5 variables were independently associated with AF, forming the "ACTEL" score: Age ≥75 years (OR 2.42, 95% CI 1.18-4.96, p = 0.02; +1 point); hyperCholesterolemia (OR 0.38, 95% CI 0.18-0.78, p = 0.009; -1 point); Tricuspid regurgitation ≥ mild-to-moderate (OR 4.99, 95% CI 1.63-15.27, p = 0.005; +1 point); left ventricular End-diastolic volume <65 mL (OR 7.43, 95% CI 2.44-22.6, p = 0.0004; +1 point); Left atrium ≥4 cm (OR 4.57, 95% CI 1.97-10.62, p = 0.0004; +1 point). The algebraic sum of these points may range from -1 to +4. For AF identification, the area under the receiver operating characteristic curve was 0.80 (95% CI 0.73-0.87). With a cutoff of ≥2, positive predictive value was 80.8%, specificity 92.7% and sensitivity 55.9%.

CONCLUSIONS

The ACTEL score, a simplified and improved version of the MrWALLETS score, allows the identification of patients with first diagnosed AF, in the context of CSs, with a high positive predictive value.

Evaluation of a clinical score for predicting atrial fibrillation in cryptogenic stroke patients with insertable cardiac monitors: results from the CRYSTAL AF study

Background

The HAVOC score was previously developed to predict the risk of atrial fibrillation (AF) after cryptogenic stroke (CS) or transient ischemic attack (TIA). The purpose of this study was to apply the HAVOC score to patients who received insertable cardiac monitors (ICMs) in the CRYSTAL AF study.

Methods

All patients from the CRYSTAL AF study who received an ICM were included. HAVOC score (one point each for peripheral vascular disease and obesity with body mass index >30, two points each for hypertension, age ⩾ 75, valvular heart disease, and coronary artery disease, 4 points for congestive heart failure) was computed for all patients. The primary endpoint was AF detection by 12 months of ICM monitoring.

Results

A total of 214 patients who received ICM were included. AF was detected in 40 patients while the remaining 174 patients were AF negative. The HAVOC score was significantly higher among patients with AF [median 3.0 with interquartile range (IQR) 2-4] than those without AF [median 2.0 (IQR 0-3)], p = 0.01. AF increased significantly across the three HAVOC score groups: 11% in Group A (score 0-1), 18% in Group B (score 2-3), and 32 % in Group C (score ⩾ 4) with p = 0.02.

Conclusions

The HAVOC score was shown in this post hoc analysis of CRYSTAL AF to successfully stratify AF risk post CS or TIA. The 11% AF rate in the lowest HAVOC score group highlights the significance of nontraditional contributors to AF and ischemic stroke.

Stroke occurrence while on antiplatelet therapy may predict atrial fibrillation detected after stroke

BACKGROUND AND AIMS

Stroke occurrence while on antiplatelet therapy, i.e., a breakthrough stroke, is often conveniently attributed to antiplatelet resistance. However, undetected paroxysmal atrial fibrillation (AF) may underlie breakthrough strokes. We hypothesized that a breakthrough stroke may be a clinical marker for patients at risk of having AF detected after stroke (AFDAS).

METHODS

Consecutive patients without known AF hospitalized for ischemic stroke between 2000 and 2013 were identified from nationwide claims data. The independent variable of interest was continued use of antiplatelet therapy within 30 days before stroke. The diagnosis of AF and comorbidities were ascertained using validated algorithms. Stroke severity (National Institutes of Health Stroke Scale [NIHSS]) was estimated using a validated claims-based method. Univariable and multivariable Cox regression analyses were used to determine the effect of breakthrough strokes on the occurrence of AFDAS separately in patients with mild and severe stroke (estimated NIHSS ≤10 versus >10).

RESULTS

Among 17,076 patients (40% female, mean age 69 years), 3314 (19%) were on antiplatelet therapy before stroke. In patients with mild stroke, prior antiplatelet use was significantly associated with the occurrence of AFDAS (adjusted hazards ratio, 1.26; 95% confidence interval, 1.08-1.48). In contrast, no association existed between prior antiplatelet use and the risk of AFDAS in those with severe stroke.

CONCLUSIONS

Patients with a breakthrough stroke of mild severity while on antiplatelet therapy carried an increased risk of AFDAS compared to those not on antiplatelet therapy. Our findings may help prioritize patients for advanced cardiac monitoring in daily practice.

Development and validation of a score to detect paroxysmal atrial fibrillation after stroke

OBJECTIVE

Prolonged monitoring times (72 hours) are recommended to detect paroxysmal atrial fibrillation (pAF) after ischemic stroke but this is not yet clinical practice; therefore, an individual patient selection for prolonged ECG monitoring might increase the diagnostic yield of pAF in a resource-saving manner.

METHODS

We used individual patient data from 3 prospective studies (n_total = 1,556) performing prolonged Holter-ECG monitoring (at least 72 hours) and centralized data evaluation after TIA or stroke in patients with sinus rhythm. Based on the TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guideline, a clinical score was developed on one cohort, internally validated by bootstrapping, and externally validated on 2 other studies.

RESULTS

pAF was detected in 77 of 1,556 patients (4.9%) during 72 hours of Holter monitoring. After logistic regression analysis with variable selection, age and the qualifying stroke event (categorized as stroke severity with NIH Stroke Scale [NIHSS] score ≤5 [odds ratio 2.4 vs TIA; 95% confidence interval 0.8-6.9, p = 0.112] or stroke with NIHSS score >5 [odds ratio 7.2 vs TIA; 95% confidence interval 2.4-21.8, p < 0.001]) were found to be predictive for the detection of pAF within 72 hours of Holter monitoring and included in the final score (Age: 0.76 points/year, Stroke Severity NIHSS ≤5 = 9 points, NIHSS >5 = 21 points; to Find AF [AS5F]). The high-risk group defined by AS5F is characterized by a predicted risk between 5.2% and 40.8% for detection of pAF with a number needed to screen of 3 for the highest observed AS5F points within the study population. Regarding the low number of outcomes before generalization of AS5F, the results need replication.

CONCLUSION

The AS5F score can select patients for prolonged ECG monitoring after ischemic stroke to detect pAF.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that the AS5F score accurately identifies patients with ischemic stroke at a higher risk of pAF.

The complexity of atrial fibrillation newly diagnosed after ischemic stroke and transient ischemic attack: advances and uncertainties

Purpose of review

Atrial fibrillation is being increasingly diagnosed after ischemic stroke and transient ischemic attack (TIA). Patient characteristics, frequency and duration of paroxysms, and the risk of recurrent ischemic stroke associated with atrial fibrillation detected after stroke and TIA (AFDAS) may differ from atrial fibrillation already known before stroke occurrence. We aim to summarize major recent advances in the field, in the context of prior evidence, and to identify areas of uncertainty to be addressed in future research.

Recent findings

Half of all atrial fibrillations in ischemic stroke and TIA patients are AFDAS, and most of them are asymptomatic. Over 50% of AFDAS paroxysms last less than 30 s. The rapid initiation of cardiac monitoring and its duration are crucial for its timely and effective detection. AFDAS comprises a heterogeneous mix of atrial fibrillation, possibly including cardiogenic and neurogenic types, and a mix of both. Over 25 single markers and at least 10 scores have been proposed as predictors of AFDAS. However, there are considerable inconsistencies across studies. The role of AFDAS burden and its associated risk of stroke recurrence have not yet been investigated.

Summary

AFDAS may differ from atrial fibrillation known before stroke in several clinical dimensions, which are important for optimal patient care strategies. Many questions remain unanswered. Neurogenic and cardiogenic AFDAS need to be characterized, as it may be possible to avoid some neurogenic cases by initiating timely preventive treatments. AFDAS burden may differ in ischemic stroke and TIA patients, with distinctive diagnostic and treatment implications. The prognosis of AFDAS and its risk of recurrent stroke are still unknown; therefore, it is uncertain whether AFDAS patients should be treated with oral anticoagulants.

A Clinical Score for Predicting Atrial Fibrillation in Patients with Cryptogenic Stroke or Transient Ischemic Attack

OBJECTIVES

Detection of atrial fibrillation (AF) in post-cryptogenic stroke (CS) or transient ischemic attack (TIA) patients carries important therapeutic implications.

METHODS

To risk stratify CS/TIA patients for later development of AF, we conducted a retrospective cohort study using data from 1995 to 2015 in the Stanford Translational Research Integrated Database Environment (STRIDE).

RESULTS

Of the 9,589 adult patients (age ≥40 years) with CS/TIA included, 482 (5%) patients developed AF post CS/TIA. Of those patients, 28.4, 26.3, and 45.3% were diagnosed with AF 1-12 months, 1-3 years, and >3 years after the index CS/TIA, respectively. Age (≥75 years), obesity, congestive heart failure, hypertension, coronary artery disease, peripheral vascular disease, and valve disease are significant risk factors, with the following respective odds ratios (95% CI): 1.73 (1.39-2.16), 1.53 (1.05-2.18), 3.34 (2.61-4.28), 2.01 (1.53-2.68), 1.72 (1.35-2.19), 1.37 (1.02-1.84), and 2.05 (1.55-2.69). A risk-scoring system, i.e., the HAVOC score, was constructed using these 7 clinical variables that successfully stratify patients into 3 risk groups, with good model discrimination (area under the curve = 0.77).

CONCLUSIONS

Findings from this study support the strategy of looking longer and harder for AF in post-CS/TIA patients. The HAVOC score identifies different levels of AF risk and may be used to select patients for extended rhythm monitoring.

Optimal Duration of Monitoring for Atrial Fibrillation in Cryptogenic Stroke: A Nonsystematic Review

Atrial fibrillation (AF) is the most common form of cardiac arrhythmias and an independent risk factor for stroke. Despite major advances in monitoring strategies, clinicians tend to miss the diagnoses of AF and especially paroxysmal AF due mainly to its asymptomatic presentation and the rather limited duration dedicated for monitoring for AF after a stroke, which is 24 hours as per the current recommended guidelines. Hence, determining the optimal duration of monitoring for paroxysmal atrial fibrillation after acute ischemic stroke remains a matter of debate. Multiple trials were published in regard to this matter using both invasive and noninvasive monitoring strategies for different monitoring periods. The data provided by these trials showcase strong evidence suggesting a longer monitoring strategy beyond 24 hours is associated with higher detection rates of AF, with the higher percentage of patients detected consequently receiving proper secondary stroke prevention with anticoagulation and thus justifying the cost-effectiveness of such measures. Overall, we thus conclude that increasing the monitoring duration for AF after a cryptogenic stroke to at least 72 hours will indeed enhance the detection rates, but the cost-effectiveness of this monitoring strategy compared to longer monitoring durations is yet to be established.

Atrial Fibrillation Monitoring in Cryptogenic Stroke: the Gaps Between Evidence and Practice

Identifying occult paroxysmal atrial fibrillation as the etiology of cryptogenic stroke has been a top research priority in the past decade. This is because prompt initiation of anticoagulation has significantly decreased subsequent stroke risk. Available evidence suggests that prolonged cardiac monitoring after stroke increases the likelihood of detecting atrial fibrillation. However, further research is required to fill in the gaps in regard to the optimal period of monitoring, candidates for monitoring, etc. Here, we review the current evidence supporting the use of prolonged monitoring for cryptogenic stroke patients and discuss the directions of future research.

Cryptogenic Stroke And Role Of Loop Recorder

Ischemic stroke is an important cause of morbidity and mortality when untreated. Identifying atrial fibrillation is important because atrial fibrillation ischemic related strokes are associated with an increased risk of disability and death compared with strokes of other etiologies and tend to recur without anticoagulation. However, atrial fibrillation detection can be difficult when it is asymptomatic and paroxistic and may be the underlying cause of some cryptogenic strokes or strokes of unknown origin. In this review, the different methods of cardiac monitoring to detect atrial fibrillation in patients with cryptogenic stroke are summarized, with a focus on loop recorder monitoring.

Score for atrial fibrillation detection in acute stroke and transient ischemic attack patients in a Brazilian population: the acute stroke atrial fibrillation scoring system

OBJECTIVE

Atrial fibrillation is a common arrhythmia that increases the risk of stroke by four- to five-fold. We aimed to establish a profile of patients with atrial fibrillation from a population of patients admitted with acute ischemic stroke or transient ischemic attack using clinical and echocardiographic findings.

METHODS

We evaluated patients consecutively admitted to a tertiary hospital with acute ischemic stroke or transient ischemic attack. Subjects were divided into an original set (admissions from May 2009 to October 2010) and a validation set (admissions from November 2010 to April 2013). The study was designed as a cohort, with clinical and echocardiographic findings compared between patients with and without atrial fibrillation. A multivariable model was built, and independent predictive factors were used to produce a predictive grading score for atrial fibrillation (Acute Stroke AF Score-ASAS).

RESULTS

A total of 257 patients were evaluated from May 2009 to October 2010 and included in the original set. Atrial fibrillation was diagnosed in 17.5% of these patients. Significant predictors of atrial fibrillation in the multivariate analysis included age, National Institutes of Health Stroke Scores, and the presence of left atrial enlargement. These predictors were used in the final logistic model. For this model, the area under the receiver operating characteristic curve was 0.79. The score derived from the logistic regression analysis was The model developed from the original data set was then applied to the validation data set, showing the preserved discriminatory ability of the model (c statistic = 0.76).

CONCLUSIONS

Our risk score suggests that the individual risk for atrial fibrillation in patients with acute ischemic stroke can be assessed using simple data, including age, National Institutes of Health Stroke Scores at admission, and the presence of left atrial enlargement.