Optimal Timing and Duration of Continuous Electrocardiographic Monitoring for Detecting Atrial Fibrillation in Stroke Patients

Can we collect health-related quality of life information from anticoagulated atrial fibrillation participants who have recently experienced a bleed? An observational feasibility study in primary and secondary care in Wales and through a UK online forum

OBJECTIVE

To evaluate the feasibility of recruiting participants diagnosed with atrial fibrillation (AF) taking oral anticoagulation therapies (OATs) and recently experiencing a bleed to collect health-related quality of life (HRQoL) information.

DESIGN

Observational feasibility study. The study aimed to determine the feasibility of recruiting participants with minor and major bleeds, the most appropriate route for recruitment and the appropriateness of the patient-reported outcome measures (PROMs) selected for collecting HRQoL information in AF patients, and the preferred format of the surveys.

SETTING

Primary care, secondary care and via an online patient forum.

PARTICIPANTS

The study population was adult patients (≥18) with AF taking OATs who had experienced a recent major or minor bleed within the last 4 weeks.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes - PROMs: EuroQol 5 Dimensions-5 Levels, Perception of Anticoagulant Treatment Questionnaire, part 2 only (part 2), atrial fibrillation effect on quality of life. Secondary outcomes - Location of bleed, bleed severity, current treatment, patient perceptions of HRQoL in relation to bleeding events.

RESULTS

We received initial expressions of interest from 103 participants. We subsequently recruited 32 participants to the study-14 from primary care and 18 through the AF forum. No participants were recruited through secondary care. Despite 32 participants consenting, only 26 initial surveys were completed. We received follow-up surveys from 11 participants (8 primary care and 3 AF forum). COVID-19 had a major impact on the study.

CONCLUSIONS

Primary care was the most successful route for recruitment. Most participants recruited to the study experienced a minor bleed. Further ways to recruit in secondary care should be explored, especially to capture more serious bleeds.

TRIAL REGISTRATION NUMBER

The study is registered in the Clinicaltrials.gov database, NCT04921176.

Comparison of the 11-Day Adhesive ECG Patch Monitor and 24-h Holter Tests to Assess the Response to Antiarrhythmic Drug Therapy in Paroxysmal Atrial Fibrillation

Accurate assessment of the response to the antiarrhythmic drug (AAD) in atrial fibrillation (AF) is crucial to achieve adequate rhythm control. We evaluated the effectiveness of extended cardiac monitoring using an adhesive ECG patch in the detection of drug-refractory paroxysmal AF. Patients diagnosed with paroxysmal AF and receiving AAD therapy were enrolled. The subjects simultaneously underwent 11-day adhesive ECG patch monitoring and a 24-h Holter test. The primary study outcome was a detection rate of drug-refractory AF or atrial tachycardia (AT) lasting ≥30 s. A total of 59 patients were enrolled and completed the study examinations. AF or AT was detected in 28 (47.5%) patients by an 11-day ECG patch monitor and in 8 (13.6%) patients by a 24-h Holter test (p < 0.001). The 11-day ECG patch monitor identified an additional 20 patients (33.8%) with drug-refractory AF not detected by the 24-h Holter, and as a result, the treatment plan was changed in 11 patients (10 catheter ablations, one medication change). In conclusion, extended cardiac rhythm monitoring using an adhesive ECG patch in patients with paroxysmal AF under AAD therapy led to over a threefold higher detection of drug-refractory AF episodes, compared to the 24-h Holter test.

ECG Smart Monitoring versus Implantable Loop Recorders for Atrial Fibrillation Detection after Cryptogenic Stroke-An Overview for Decision Making

Up to 20% of patients with ischemic stroke or transient ischemic attack have a prior history of known atrial fibrillation (AF). Additionally, unknown AF can be detected by different monitoring strategies in up to 23% of patients with cryptogenic or non-cardioembolic stroke. However, most studies had substantial gaps in monitoring time, especially early after the index event. Following this, AF rates would be higher if patients underwent continuous monitoring early after stroke, avoiding any gaps in monitoring. The few existing randomized studies focused on patients with cryptogenic stroke but did not focus otherwise specifically on prevention strategies in patients at high risk for AF (patients at higher age or with high CHA2DS2-VASC scores). Besides invasive implantable loop recorders (ILRs), external loop recorders (ELRs) and mobile cardiac outpatient telemetry (MCOT) are non-invasive tools that are commonly used for long-term ECG monitoring in cryptogenic-stroke patients in the ambulatory setting. The role of MCOT and hand-held devices within ECG smart monitoring in the detection of AF for the prevention of and after cryptogenic stroke is currently unclear. This intense review provides an overview of current evidence, techniques, and gaps in knowledge and aims to advise which patients benefit most from the current available devices.

Contemporary prevalence estimates of undiagnosed and diagnosed atrial fibrillation in the United States

BACKGROUND

Atrial fibrillation (AF) prevalence estimates vary and have been based on cohorts with clinically established or diagnosed disease. Undiagnosed AF prevalence estimates are less certain as they are based on nongeneralizable convenience samples.

HYPOTHESIS

Because AF is often asymptomatic, it my remain undiagnosed until the development of complications such as stroke or heart failure. Consequently, the observed prevalence of diagnosed AF from the literature may underestimate total disease burden. We therefore sought to estimate the total prevalence of both diagnosed and undiagnosed AF.

METHODS

We performed a retrospective cohort study from 2012 to 2017 using data from five US medical claims data sets. Undiagnosed AF prevalence was estimated based on the observed incidence of ischemic stroke, systemic embolism (SE), and AF incidence after a stroke/SE. The diagnosed AF cohort included AF patients between Q1 2014 and Q3 2015. The undiagnosed AF cohort were patients with assumed undiagnosed AF in the year before a stroke/SE and who were newly diagnosed with AF in the 3-month poststroke/SE. Stroke/SE incidence was calculated among all AF patients and the ratio of number of undiagnosed AF patients to stroke rate was created. Age- and sex-adjusted estimates were stratified by period of assumed undiagnosed AF before poststroke/SE AF diagnosis (1 or 2 years).

RESULTS

The estimated US prevalence of AF (diagnosed and undiagnosed) in Q3 2015 was 5 628 000 cases, of which 591 000 cases (11%) were undiagnosed. The assumed 2-year undiagnosed AF prevalence was 23% (1 531 000) of the total prevalent patients with AF (6 568 000). Undiagnosed (vs. diagnosed) AF patients were older and had higher CHA2DS2-VASc scores. Of undiagnosed AF, 93% had CHA2DS2-VASc ≥2 and met OAC criteria.

CONCLUSIONS

These contemporary estimates demonstrate the high prevalence of undiagnosed AF in the United States. Undiagnosed AF patients are composed of primarily elderly individuals who if diagnosed, would meet criteria for stroke prevention therapy.

Initial In-Hospital Visit-to-Visit Heart Rate Variability Is Associated with Higher Risk of Atrial Fibrillation in Patients with Acute Ischemic Stroke

BACKGROUND

To evaluate the association between the visit-to-visit heart rate variability and the risk of atrial fibrillation (AF) in acute ischemic stroke (AIS).

METHODS

We analyzed the data of 8179 patients with AIS. Patients without AF on 12-lead electrocardiography underwent further 24 h Holter monitoring. They were categorized into four subgroups according to the visit-to-visit heart rate variability expressed as the coefficient of variation in heart rate (HR-CV). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using the HR-CV < 0.08 subgroup as a reference.

RESULTS

The adjusted OR of paroxysmal AF was 1.866 (95% CI = 1.205-2.889) for the HR-CV ≥ 0.08 and <0.10 subgroup, 1.889 (95% CI = 1.174-3.038) for the HR-CV ≥ 0.10 and <0.12 subgroup, and 5.564 (95% CI = 3.847-8.047) for the HR-CV ≥ 0.12 subgroup. The adjusted OR of persistent AF was 2.425 (95% CI = 1.921-3.062) for the HR-CV ≥ 0.08 and <0.10 subgroup, 4.312 (95% CI = 3.415-5.446) for the HR-CV ≥ 0.10 and <0.12 subgroup, and 5.651 (95% CI = 4.586-6.964) for the HR-CV ≥ 0.12 subgroup.

CONCLUSIONS

HR-CV can facilitate the identification of patients with AIS at a high risk of paroxysmal AF.

14-day Holter monitoring for atrial fibrillation after ischemic stroke: The yield of guideline-recommended monitoring duration

Introduction:

Current European Stroke Organisation (ESO) guidelines recommend >48 h of continuous electrocardiographic monitoring for atrial fibrillation (AF) in all patients with ischemic stroke or transient ischemic attack (TIA) with undetermined origin. We assessed the yield of the guideline-recommended monitoring for AF, as well as of extending monitoring up to 14 days.

Patients and methods:

We included consecutive patients with stroke/TIA without AF in an academic hospital in The Netherlands. We reported AF incidence and number needed to screen (NNS) in the overall sample after 48 h and 14 days of Holter monitoring.

Results:

Among 379 patients with median age 63 years (IQR 55–73), 58% male, Holter monitoring detected 10 cases of incident AF during a median of 13 (IQR 12–14) days of monitoring. Seven AF cases were detected within the first 48 hours (incidence 1.85%, 95% CI 0.74–3.81; NNS 54), and three additional AF cases were recorded among the 362 patients with >48 h of monitoring and without AF ⩽ 48 h (incidence 0.83%, 95% CI: 0.17–2.42; NNS 121). All AF cases were detected within the first 7 days of monitoring. Our sample was subject to sampling bias favoring inclusion of participants with low AF risk.

Discussion:

Strengths of this work were the broad inclusion criteria as recommended by ESO guidelines, and high Holter adherence among participants. The analysis was limited by inclusion of lower-risk cases and a relatively small sample size.

Conclusion:

In low-risk patients with recent stroke or TIA, ESO guideline-recommended screening for AF resulted in a low AF yield, with limited additional value of monitoring up to 14 days. Our results underline the need for a personalized approach in determining a patient’s optimum duration for post-stroke non-invasive ambulatory monitoring.

Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke

Atrial fibrillation (AF)—whether paroxysmal or sustained—increases the risk of stroke. We developed and validated a risk score for identifying patients at risk of paroxysmal atrial fibrillation (pAF) after acute ischemic stroke (AIS). A total of 6033 patients with AIS who received 24 h Holter monitoring were identified in the Chang Gung Research Database. Among the identified patients, 5290 with pAF and without AF were included in the multivariable logistic regression analysis to develop the pAF prediction model. The ABCD-SD score (Age, Systolic Blood pressure, Coronary artery disease, Dyslipidemia, and Standard Deviation of heart rate) comprises age (+2 points for every 10 years), systolic blood pressure (−1 point for every 20 mmHg), coronary artery disease (+2 points), dyslipidemia (−2 points), and standard deviation of heart rate (+2 points for every 3 beats per minute). Overall, 5.2% (274/5290) of patients had pAF. The pAF risk ranged from 0.8% (ABCD-SD score ≤ 7) to 18.3% (ABCD-SD score ≥ 15). The model achieved an area under the receiver operating characteristic curve (AUROCC) of 0.767 in the model development group. The ABCD-SD score could aid clinicians in identifying patients with AIS at risk of pAF for advanced cardiac monitoring.

Determinants of Use of Long-term Continuous Electrocardiographic Monitoring for Acute Ischemic Stroke Patients without Atrial Fibrillation at Baseline

BACKGROUND

Atrial fibrillation (AF) is the most common cardiac rhythm disorder associated with stroke. Increased risk of stroke is the same regardless of whether the AF is permanent or paroxysmal. However, detecting paroxysmal AF is challenging and resource intensive. We aimed to develop a predictive model for AF in patients with acute ischemic stroke, which could improve the detection rate of paroxysmal AF.

METHODS

We analyzed 10,034 adult patients with acute ischemic stroke. Differences in clinical characteristics between the patients with and without AF were analyzed in order to develop a predictive model of AF. The associated factors for AF were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses. We used another dataset, which enrolled 860 acute ischemic stroke patients without AF at baseline, to test whether the developed model could improve the detection rate of paroxysmal AF. Among the study population, 1,658 patients (16.5%) had AF.

RESULTS

Multivariate logistic regression revealed that sex, age, body weight, hypertension, diabetes mellitus, hyperlipidemia, pulse rate at admission, respiratory rate at admission, systolic blood pressure at admission, diastolic blood pressure at admission, National Institute of Health Stroke Scale (NIHSS) score at admission, total cholesterol level, triglyceride level, aspartate transaminase level, and sodium level were major factors associated with AF. CART analysis identified NIHSS score at admission, age, triglyceride level, and aspartate transaminase level as important factors for AF to classify the patients into subgroups.

CONCLUSION

When selecting the high-risk group of patients (with an NIHSS score >12 and age >64.5 years, or with an NIHSS score ≤12, age >71.5 years, and triglyceride level ≤61.5 mg/dL) according to the CART model, the detection rate of paroxysmal AF was approximately double in the acute ischemic stroke patients without AF at baseline.

Potential of machine learning methods to identify patients with nonvalvular atrial fibrillation

Aim: Nonvalvular atrial fibrillation (NVAF) is associated with an increased risk of stroke however many patients are diagnosed after onset. This study assessed the potential of machine-learning algorithms to detect NVAF. Materials & methods: A retrospective database study using a Japanese claims database. Patients with and without NVAF were selected. 41 variables were included in different classification algorithms. Results: Machine learning algorithms identified NVAF with an area under the curve of >0.86; corresponding sensitivity/specificity was also high. The stacking model which combined multiple algorithms outperformed single-model approaches (area under the curve ≥0.90, sensitivity/specificity ≥0.80/0.82), although differences were small. Conclusion: Machine-learning based algorithms can detect atrial fibrillation with accuracy. Although additional validation is needed, this methodology could encourage a new approach to detect NVAF.

The value of STAF (Score for the Targeting of Atrial Fibrillation) in Patients with Cryptogenic Embolic Stroke

Introduction

The aim of the present study was to predict paroxysmal atrial fibrillation (PAF) in acute ischemic stroke patients with presumed cryptogenic embolic etiology.

Methods

In this retrospective cohort study, demographics, blood tests, data of neuroimaging studies such as non-contrast computed tomography (NCCT), magnetic resonance imaging (MRI), standard 12-lead electrocardigraphy (ECG), 24-hour Holter ECG, echocardiography was collected. The diagnostic work-up to detect atrial fibrillation (AF) was either medical history of the patient or 12-lead ECG or 24-hour Holter ECG or continuous ECG monitoring. Score for the targeting of atrial fibrillation (STAF) was calculated for all patients. Cryptogenic ischemic stroke (CS) patients with and without documented AF were recorded.

Results

Between July 2014 and December 2015, a total of 133 of the 258 patients with CS were included in this study. Overall, 133 patients were enrolled and AF was detected in 30 (22.6%) patients. In univariate analysis gender (p<0.001), age (p=0.001), smoking habit (p=0.004), aortic and mitral valve insufficiency (p=0.014 and p=0.021), left ventricular systolic dysfunction (p=0.04), and left atrial dilatation (p=0.03) were predictors of AF but multivariate analysis showed that only gender and age were independent predictors of AF in patients with presumed cryptogenic ischemic stroke. According to ROC analysis, area under the curve was 70% and the sensitivity and specificity of STAF score of ≥5 was 86% and 71% respectively.

Conclusion

STAF score predicted with fair accuracy, and has a limited use for the risk of PAF in stroke patients.

Atrial fibrillation detection using single lead portable electrocardiographic monitoring: a systematic review and meta-analysis

OBJECTIVES

Recent technology advances have allowed for heart rhythm monitoring using single-lead ECG monitoring devices, which can be used for early diagnosis of atrial fibrillation (AF). We sought to investigate the AF detection rate using portable ECG devices compared with Holter monitoring.

SETTING, PARTICIPANTS AND OUTCOME MEASURES

We searched the Medline, Embase and Scopus databases (conducted on 8 May 2017) using search terms related to AF screening and included studies with adults aged >18 years using portable ECG devices or Holter monitoring for AF detection. We excluded studies using implantable loop recorders and pacemakers. Using a random-effects model we calculated the overall AF detection rate. Meta-regression analysis was performed to explore potential sources for heterogeneity. Quality of reporting was assessed using the tool developed by Downs and Black.

RESULTS

Portable ECG monitoring was used in 18 studies (n=117 436) and Holter monitoring was used in 36 studies (n=8498). The AF detection rate using portable ECG monitoring was 1.7% (95% CI 1.4 to 2.1), with significant heterogeneity between studies (p<0.001). There was a moderate linear relationship between total monitoring time and AF detection rate (r=0.65, p=0.003), and meta-regression identified total monitoring time (p=0.005) and body mass index (p=0.01) as potential contributors to heterogeneity. The detection rate (4.8%, 95% CI 3.6% to 6.0%) in eight studies (n=10 199), which performed multiple ECG recordings was comparable to that with 24 hours Holter (4.6%, 95% CI 3.5% to 5.7%). Intermittent recordings for 19 min total produced similar AF detection to 24 hours Holter monitoring.

CONCLUSION

Portable ECG devices may offer an efficient screening option for AF compared with 24 hours Holter monitoring.

PROSPERO REGISTRATION NUMBER

CRD42017061021.

Estimated prevalence of undiagnosed atrial fibrillation in the United States

Introduction

As atrial fibrillation (AF) is often asymptomatic, it may remain undiagnosed until or even after development of complications, such as stroke. Consequently the observed prevalence of AF may underestimate total disease burden.

Methods

To estimate the prevalence of undiagnosed AF in the United States, we performed a retrospective cohort modeling study in working age (18–64) and elderly (≥65) people using commercial and Medicare administrative claims databases. We identified patients in years 2004–2010 with incident AF following an ischemic stroke. Using a back-calculation methodology, we estimated the prevalence of undiagnosed AF as the ratio of the number of post-stroke AF patients and the CHADS₂-specific stroke probability for each patient, adjusting for age and gender composition based on United States census data.

Results

The estimated prevalence of AF (diagnosed and undiagnosed) was 3,873,900 (95%CI: 3,675,200–4,702,600) elderly and 1,457,100 (95%CI: 1,218,500–1,695,800) working age adults, representing 10.0% and 0.92% of the respective populations. Of these, 698,900 were undiagnosed: 535,400 (95%CI: 331,900–804,400) elderly and 163,500 (95%CI: 17,700–400,000) working age adults, representing 1.3% and 0.09% of the respective populations. Among all undiagnosed cases, 77% had a CHADS₂ score ≥1, and 56% had CHADS₂ score ≥2.

Conclusions

Using a back-calculation approach, we estimate that the total AF prevalence in 2009 was 5.3 million of which 0.7 million (13.1% of AF cases) were undiagnosed. Over half of the modeled population with undiagnosed AF was at moderate to high risk of stroke.

Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis

Background

Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk of thromboembolic events. Anticoagulation therapy to prevent AF-related stroke has been shown to be cost-effective. A national screening programme for AF may prevent AF-related events, but would involve a substantial investment of NHS resources.

Objectives

To conduct a systematic review of the diagnostic test accuracy (DTA) of screening tests for AF, update a systematic review of comparative studies evaluating screening strategies for AF, develop an economic model to compare the cost-effectiveness of different screening strategies and review observational studies of AF screening to provide inputs to the model.

Design

Systematic review, meta-analysis and cost-effectiveness analysis.

Setting

Primary care.

Participants

Adults.

Intervention

Screening strategies, defined by screening test, age at initial and final screens, screening interval and format of screening {systematic opportunistic screening [individuals offered screening if they consult with their general practitioner (GP)] or systematic population screening (when all eligible individuals are invited to screening)}.

Main outcome measures

Sensitivity, specificity and diagnostic odds ratios; the odds ratio of detecting new AF cases compared with no screening; and the mean incremental net benefit compared with no screening.

Review methods

Two reviewers screened the search results, extracted data and assessed the risk of bias. A DTA meta-analysis was perfomed, and a decision tree and Markov model was used to evaluate the cost-effectiveness of the screening strategies.

Results

Diagnostic test accuracy depended on the screening test and how it was interpreted. In general, the screening tests identified in our review had high sensitivity (> 0.9). Systematic population and systematic opportunistic screening strategies were found to be similarly effective, with an estimated 170 individuals needed to be screened to detect one additional AF case compared with no screening. Systematic opportunistic screening was more likely to be cost-effective than systematic population screening, as long as the uptake of opportunistic screening observed in randomised controlled trials translates to practice. Modified blood pressure monitors, photoplethysmography or nurse pulse palpation were more likely to be cost-effective than other screening tests. A screening strategy with an initial screening age of 65 years and repeated screens every 5 years until age 80 years was likely to be cost-effective, provided that compliance with treatment does not decline with increasing age.

Conclusions

A national screening programme for AF is likely to represent a cost-effective use of resources. Systematic opportunistic screening is more likely to be cost-effective than systematic population screening. Nurse pulse palpation or modified blood pressure monitors would be appropriate screening tests, with confirmation by diagnostic 12-lead electrocardiography interpreted by a trained GP, with referral to a specialist in the case of an unclear diagnosis. Implementation strategies to operationalise uptake of systematic opportunistic screening in primary care should accompany any screening recommendations.

Limitations

Many inputs for the economic model relied on a single trial [the Screening for Atrial Fibrillation in the Elderly (SAFE) study] and DTA results were based on a few studies at high risk of bias/of low applicability.

Future work

Comparative studies measuring long-term outcomes of screening strategies and DTA studies for new, emerging technologies and to replicate the results for photoplethysmography and GP interpretation of 12-lead electrocardiography in a screening population.

Study registration

This study is registered as PROSPERO CRD42014013739.

Funding

The National Institute for Health Research Health Technology Assessment programme.

Electrocardiographic and Echocardiographic predictors of paroxysmal atrial fibrillation detected after ischemic stroke

BACKGROUND

Detection of atrial fibrillation after ischemic stroke is challenging due to its paroxysmal nature. We aimed to assess predictors of paroxysmal atrial fibrillation using non-invasive surface ECG and transthoracic echocardiography to select candidates for atrial fibrillation screening.

METHODS

Ischemic stroke patients without documented atrial fibrillation (n = 110, 67 ± 10 years, 40 female) and a control group of age- and gender-matched patients with history of paroxysmal atrial fibrillation prior to stroke (n = 55, 67 ± 10 years, 19 female) comprised the study sample. Using non-invasive ECG monitoring for three weeks, short episodes of paroxysmal atrial fibrillation were detected in 24 of 110 patients (22 %). The standard 12-lead ECG with sinus rhythm at stroke onset was digitally processed and analyzed. Transthoracic echocardiography data were reviewed for these patients.

RESULTS

Atrial fibrillation history was independently associated with P terminal force in lead V 1 > 40 mm*ms (OR 4.04 95 % CI 1.34-12.14, p = 0.013) and left atrial volume index (OR 1.08 95 % CI 1.03-1.13, p = 0.002; for LAVI > 40 mL/m² OR 6.40 95 % CL 1.47-27.91, p = 0.013). Among patients without atrial fibrillation history, no ECG characteristics were predictive of atrial fibrillation detected after stroke. Left atrial volume index remained an independent predictor of atrial fibrillation detected after stroke (OR 1.09 95 % CI 1.02-1.16, p = 0.017). A cutoff of <40 mL/m² had an 84 % negative predictive value for ruling out atrial fibrillation on ambulatory monitoring with a sensitivity of 50 % and a specificity of 86 %.

CONCLUSION

In a post hoc analysis, left atrial dilatation assessed by left atrial volume index independently predicted atrial fibrillation after stroke in patients without prior atrial fibrillation history, while the other clinical or ECG markers were not predictive of atrial fibrillation detected early after ischemic stroke.

TRIAL REGISTRATION

This study is a post hoc analysis from the prospective case-control study registered in December 2011, ClinicalTrials.gov ID: NCT01325545 .

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.

Predictors of new onset atrial fibrillation during 10-year follow-up after first-ever ischemic stroke

BACKGROUND

Paroxysmal atrial fibrillation (AF) may be underdiagnosed in ischemic stroke patients but may be pivotal for initiation of oral anticoagulation therapy. We assessed clinical and ECG predictors of new-onset AF during 10-year follow-up (FU) in ischemic stroke patients.

METHODS

The study sample comprised of 227 first-ever ischemic stroke patients without AF (median age 73, interquartile range 25%-75% 63-80years, 92 female) and 1:1 age- and gender-matched controls without stroke and AF enrolled in the Lund Stroke Register from March 2001 to February 2002. New-onset AF during FU was assessed by screening through regional ECG database and by record linkage with Swedish National Patient Register. The standard 12-lead sinus rhythm ECGs at stroke admission were retrieved from electronic database and digitally processed. Clinical baseline characteristics were studied using medical records.

RESULTS

During FU, AF was found in 39 stroke patients and 30 controls, p=0.296. In stroke patients in multivariate Cox regression analysis AF was associated with hypertension (HR 3.45 CI 95% 1.40-3.49, p=0.007) and QRS duration (HR 1.02 CI 95% 1.00-1.03, p=0.049). High cardiovascular risk was predictive for AF development: for CHADS2≥4 HR 2.46 CI 95% 1.45-4.18, p=0.001 and for CHA2DS2-VASc≥5 HR 2.29 CI 95% 1.43-3.68, p=0.001. New onset AF was not associated with baseline ischemic stroke: HR 1.46 95% CI 0.90-2.35, p=0.121.

CONCLUSION

High CHADS2 and CHA2DS2-VASc scores, but not baseline ischemic stroke, predict new onset AF in FU. QRS duration might be considered a potential risk marker for prediction of AF after ischemic stroke.

Electrocardiographic monitoring for detecting atrial fibrillation after ischemic stroke or transient ischemic attack: systematic review and meta-analysis

BACKGROUND

Atrial fibrillation (AF) is a major cause of stroke. Although standard investigations after an event include electrocardiographic monitoring, the optimal duration to detect AF is unclear. We performed a systematic review and meta-analysis to determine whether the duration of electrocardiographic monitoring after an ischemic event is related to the detection of AF.

METHODS AND RESULTS

Prospective studies that reported the proportion of new AF diagnosed using electrocardiographic monitoring for > 12 hours in patients with recent stroke or transient ischemic attack were analyzed. Studies were excluded if the stroke was hemorrhagic or AF was previously diagnosed. A total of 31 articles met inclusion criteria. Longer duration of monitoring was associated with an increased detection of AF when examining monitoring time as a continuous variable (P < 0.001 for metaregression analysis). When dichotomizing studies based on monitoring duration, studies with monitoring lasting ≤ 72 hours detected AF in 5.1%, whereas monitoring lasting ≥ 7 days detected AF in 15%. The proportion of new diagnosis increased to 29.15% with extended monitoring for 3 months. Significant heterogeneity within studies was detected for both groups (≤ 72 hours, I(2) = 91.3%; ≥ 7 days, I(2) =7 5.8). When assessing the odds of AF detection in the 3 randomized controlled trial, there was a 7.26 increased odds of AF with long-term monitoring (95% confidence intervals [3.99-12.83]; P value < 0.001).

CONCLUSIONS

Longer duration of electrocardiographic monitoring after cryptogenic stroke is associated with a greater detection of AF. Future investigation is needed to determine the optimal duration of long-term monitoring.

Documentation of atrial fibrillation prior to first-ever ischemic stroke

OBJECTIVES

We assessed the prevalence of atrial fibrillation (AF) prior to first-ever ischemic stroke by examining a comprehensive electronic ECG archive.

METHODS

The study sample comprised 336 consecutive stroke patients (median age 76 (IQ16) y, 200 men) enrolled in Lund Stroke Register from March 2001 to February 2002 and 336 age- and gender-matched controls without stroke history. AF prior to admission was studied using the regional electronic ECG database and record linkage with the National Swedish Hospital Discharge Register (SHDR). Medical records were reviewed for AF documentation and CHA2 DS2-VASc risk score.

RESULTS

Atrial fibrillation before or at stroke onset was detected in 109 (32.4%) stroke patients and 44 (13.1%) controls, P<0.001. Twenty-five of 109 stroke patients had AF detected only on previous ECG (n=14) or through the SHDR (n=11). The most prevalent type of AF in stroke group was non-permanent AF (59.6%). AF prevalence among patients admitted with sinus rhythm at hospital admission (n=266) was higher in those with CHA2 DS2 -VASc score≥6 (28.6%) than with CHA2 DS2-VASc score<6 (13.0%), P=0.043.

CONCLUSION

Comprehensive approach for AF screening allows detecting AF in one-third of patients admitted with first-ever ischemic stroke. Patients with high cardiovascular risk are more likely to have non-permanent AF.

Screening of Paroxysmal Atrial Fibrillation after Ischemic Stroke: 48-Hour Holter Monitoring versus Prolonged Intermittent ECG Recording

Aims. Screening of paroxysmal atrial fibrillation (PAF) after ischemic stroke and TIA is important. The ideal method is not known and studies of intermittent screening methods in particular are lacking. In this retrospective study we compared a shorter continuous screening method with an intermittent screening method. Methods. Since early 2011 our stroke unit has used two different methods of screening: either a 48-hour continuous screening with Holter monitor or a 21-day twice daily intermittent screening with a hand-held ECG recorder. Through the Swedish National Stroke Registry and medical records reviewing all screening episodes between 2011-02-01 and 2013-01-31 were collected and analysed.   Results. Of 386 screenings, 26 screenings were excluded leaving 360 screenings for the final analysis of which 114 screenings were made with hand-held ECG recorder and 246 with Holter monitoring. No significant difference between the groups concerning basic characteristics was observed. In the hand-held ECG recorder group a total of 13 PAF screenings (11.4%) were detected compared with 7 (2,8%) in the Holter group (P=0.001). Conclusions. A prolonged intermittent screening is a better method than a shorter continuous screening in terms of detecting PAF after ischemic stroke and TIA.

[Atrial fibrillation and stroke]

BACKGROUND

More than 70,000 Norwegians have atrial fibrillation, which is a major risk factor for ischemic stroke. A large proportion of ischemic strokes caused by atrial fibrillation could be prevented if patients receive optimal prophylactic treatment. This article describes the risk for ischemic stroke in patients with atrial fibrillation, and discusses who should receive prophylactic treatment and which therapy provides the best prevention.

METHOD

The article is based on recently published European, American and Canadian guidelines, a search in PubMed and the authors' own clinical experience.

RESULTS

The new risk score CHA2DS2-VASc is better than the CHADS2 score for identifying patients with atrial fibrillation who have a truly low risk of ischemic stroke and are not in need of antithrombotic treatment. Oral anticoagulation therapy is recommended for patients with two or more risk factors for thromboembolism in addition to atrial fibrillation (CHA2DS2-VASc ≥ 2). Patients with atrial fibrillation and a single additional risk factor (CHA2DS2-VASc =1) an individual assessment should be made as to who should receive oral anticoagulants, and for patients with CHA2DS2-VASc = 0 antithrombotic treatment is not recommended. New oral anticoagulants are at least as effective as warfarin for preventing ischemic stroke in patients with nonvalvular atrial fibrillation, they carry a lower risk of cerebral haemorrhage, especially intracranial haemorrhage and are more practical in use. Platelet inhibitors have a minimal role in stroke prevention in patients with atrial fibrillation.

INTERPRETATION

Risks stratifying patients using the CHA2DS2-VASc score is a better method for assessing which patients with atrial fibrillation who should receive oral anticoagulation. The introduction of new oral anticoagulants will simplify preventive treatment and hopefully lead to a more efficient anticoagulation treatment in a larger number of patients with atrial fibrillation.

Brain natriuretic peptide: a relevant marker to rule out delayed atrial fibrillation in stroke patient

Detection of new atrial fibrillation (AF) after ischemic stroke is challenging. The aim of the TARGET-AF study was to identify relevant markers for ruling out delayed AF in stroke patients. Early and prolonged Holter electrocardiography (ECG) monitoring during hospitalization was performed systematically in consecutive acute stroke patients naive to AF (no history of AF or no AF on baseline ECG). All clinical and paraclinical data for routine etiologic assessment were collected. The diagnostic value of all parameters significantly associated with AF was assessed by comparison of area under the receiver operating characteristic curve (AUC). Of the 300 stroke patients enrolled (mean age, 62.5 ± 15.5 years; sex ratio: 1.7; mean National Institutes of Health Stroke Scale score, 7.1 ± 7.9, median duration of Holter ECG monitoring, 6.8 days), 52 (17.3%) had newly diagnosed AF. Parameters significantly associated with AF were classified by increasing AUC: anterior circulation localization (AUC, 0.604; 95% confidence interval [CI], 0.546-0.660), P-wave initial force (AUC, 0.608; 95% CI, 0.545-0.669), left atrial dilatation (AUC, 0.657; 95% CI, 0.600-0.711), National Institutes of Health Stroke Scale score (AUC, 0.667; 95% CI, 0.611-0.720), sex (AUC, 0.683; 95% CI, 0.627-0.736), age (AUC, 0.755; 95% CI, 0.707-0.797), CHA2DS2-VASc score (AUC, 0.796; 95% CI, 0.746-0.841), STAF (score for the targeting of AF) score (AUC, 0.842; 95% CI, 0.796-0.882), and plasma brain natriuretic peptide (BNP) level (AUC, 0.868; 95% CI, 0.825-0.904). The use of all parameters combined (AUC, 0.910; 95% CI, 0.872-0.940) was not significantly more efficient in diagnosing AF than BNP alone (P = .248). At the Youden plot, the diagnostic properties for BNP >131 pg/mL were sensitivity, 98.1% (95% CI, 89.7-99.7); specificity, 71.4% (95% CI, 65.3-76.9); and negative predictive value, 99.4% (95% CI, 96.9-99.9). Our data indicate that a BNP level ≤ 131 pg/mL might rule out delayed AF in stroke survivors and could be included in algorithms for AF detection.