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.

A nomogram for predicting atrial fibrillation detected after acute ischemic stroke

Background

Atrial fibrillation detected after stroke (AFDAS) is associated with an increased risk of ischemic stroke (IS) recurrence and death. Early diagnosis can help identify strategies for secondary prevention and improve prognosis. However, there are no validated predictive tools to assess the population at risk for AFDAS. Therefore, this study aimed to develop and validate a predictive model for assessing the incidence of AFDAS after acute ischemic stroke (AIS).

Methods

This study was a multicenter retrospective study. We collected clinical data from 5332 patients with AIS at two hospitals between 2014.01 and 2021.12 and divided the development and validation of clinical prediction models into a training cohort (n = 3173) and a validation cohort (n = 2159). Characteristic variables were selected from the training cohort using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariable logistic regression analysis. A nomogram model was developed, and its performance was evaluated regarding calibration, discrimination, and clinical utility.

Results

We found the best subset of risk factors based on clinical characteristics and laboratory variables, including age, congestive heart failure (CHF), previous AIS/transient ischemia attack (TIA), national institutes of health stroke scale (NIHSS) score, C-reactive protein (CRP), and B-type natriuretic peptide (BNP). A predictive model was developed. The model showed good calibration and discrimination, with calibration values of Hosmer-Lemeshow χ² = 4.813, P = 0.732 and Hosmer-Lemeshow χ² = 4.248, P = 0.834 in the training and validation cohorts, respectively. The area under the ROC curve (AUC) was 0.815, 95% CI (0.777–0.853) and 0.808, 95% CI (0.770–0.847). The inclusion of neuroimaging variables significantly improved the performance of the integrated model in both the training cohort (AUC. 0.846 (0.811–0.882) vs. 0.815 (0.777–0.853), P = 0.001) and the validation cohort (AUC: 0.841 (0.804–0.877) vs. 0.808 (0.770–0.847), P = 0.001). The decision curves showed that the integrated model added more net benefit in predicting the incidence of AFDAS.

Conclusion

Predictive models based on clinical characteristics, laboratory variables, and neuroimaging variables showed good calibration and high net clinical benefit, informing clinical decision-making in diagnosing and treating patients with AFDAS.

Embolic Stroke of Undetermined Source: Approaches in Risk Stratification for Cardioembolism

Ischemic stroke is a leading cause of morbidity and mortality worldwide. Embolic stroke of undetermined source has been recently proposed to categorize nonlacunar ischemic strokes without confirmed etiology after adequate investigation with a likely embolic stroke mechanism. A strategy of empirical anticoagulation for embolic stroke of undetermined source patients is attractive but may only be beneficial in a select subset of patients. Strategies which would help identify the subset of embolic stroke of undetermined source patients most likely to have cardioembolic origin of stroke, and hence benefit from anticoagulation, are needed. This article will review current evidence which may be useful in the development of a risk stratification approach based on arrhythmia monitoring, cardiac imaging, and clinical risk stratification. This approach may be beneficial in clinical practice in improving patient outcomes and reducing stroke recurrence in this population; however, further work is required with active trials underway.

Detecting Atrial Fibrillation in Patients With an Embolic Stroke of Undetermined Source (from the DAF-ESUS registry)

Atrial fibrillation (AF) causes a substantial proportion of embolic strokes of undeterminded source (ESUS). Effective detection of subclinical AF (SCAF) has important therapeutic implications. We conducted a prospective study to determine the prevalence of SCAF in patients with ESUS through of a 21-day Holter monitoring. In an early-monitoring group, Holter was initiated immediately after hospital discharge. The results were compared with a previous cohort of patients in whom the Holter was initiated at least 1 week after hospital discharge (late-monitoring group). We included 100 patients (50 each group; 69 ± 13 years, 56% male). Mean time from ESUS to Holter was 1.2 ± 1 day in the early-monitoring group and 30 ± 15 days in the late-monitoring group. SCAF was detected in 22% of patients in the early-monitoring and 6% in the late-monitoring group (p <0.05). Patients with SCAF were older (77 ± 9 vs 67 ± 11 years, p <0.05), with a higher rate of left atrial enlargement (50% vs 20%, p<0.05), renal impairment (28% vs 5%; p<0.01), and a slower mean heart rate (55 ± 6 vs 70 ± 6 beats/min; p<0.001). On multivariate analysis, the presence of persistent bradycardia (≤60 beats/min) in the 21-day Holter was a powerful and significant risk factor for SCAF. In conclusion, the sooner 21-day Holter electrocardiogram monitoring is initiated after ESUS, the more likely SCAF can be detected. Sinus bradycardia is a powerful predictor of SCAF in patients with 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.

Diagnostic accuracy of STAF, LADS, and iPAB scores for predicting paroxysmal atrial fibrillation in patients with acute cerebral infarction

BACKGROUND AND OBJECTIVE

The scoring scales scoring system for targeting atrial fibrillation (STAF), left atrial diameter, age, diagnosis of stroke, and smoking status (LADS), and identified by past history of arrhythmia or antiarrhythmic agent use, atrial dilation, and elevation of Brain natriuretic peptide (iPAB) have been proposed for predicting atrial fibrillation in patients with acute cerebral infarction, but their relative accuracies are not clear. This prospective study compared STAF, LADS, and iPAB scores for predicting paroxysmal atrial fibrillation (PAF) in patients with acute cerebral infarction.

METHODS

Patients with acute cerebral infarction (n = 744; 495 men, 249 women; aged 65 ± 12 years) were consecutively enrolled throughout the year 2016 at the Department of Neurology of Huizhou Municipal Central Hospital. Patients were followed for 3 months. The sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and best cutoff points of STAF, LADS, and iPAB scores for predicting PAF were computed.

RESULTS

Among the 744 patients, 37 patients had PAF. The AUCs of the STAF, LADS, and iPAB scores for predicting PAF were 0.87, 0.79, and 0.84, respectively, and with a cutoff at four points, the sensitivities were 73%, 70.3%, and 83.8%, and specificities were 92.1%, 82.2%, and 77%.

CONCLUSIONS

The STAF, LADS, and iPAB scores could satisfactorily predict PAF in patients with acute cerebral infarction. STAF was superior to the others in diagnostic performance.

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.

Cryptogenic Acute Ischemic Stroke: Assessment of the Performance of a New Continuous Long-Term Monitoring System in the Detection of Atrial Fibrillation

Background

Long-term monitoring has been advocated to enhance the detection of atrial fibrillation (AF) in patients with stroke.

Objective

To evaluate the performance of a new ambulatory monitoring system with mobile data transmission (PoIP) compared with 24-hour Holter. We also aimed to evaluate the incidence of arrhythmias in patients with and without stroke or transient ischemic attack.

Methods

Consecutive patients with and without stroke or TIA, without AF, were matched by propensity score. Participants underwent 24-hour Holter and 7-day PoIP monitoring.

Results

We selected 52 of 84 patients (26 with stroke or TIA and 26 controls). Connection and recording times were 156.5 ± 22.5 and 148.8 ± 20.8 hours, with a signal loss of 6,8% and 11,4%, respectively. Connection time was longer in ambulatory (164.3 ± 15.8 h) than in hospitalized patients (148.8 ± 25.6 h) (p = 0.02), while recording time did not differ between them (153.7 ± 16.9 and 143.0 ± 23.3 h). AF episodes were detected in 1 patient with stroke by Holter, and in 7 individuals (1 control and 6 strokes) by PoIP. There was no difference in the incidence of arrhythmias between the groups.

Conclusions

Holter and PoIP performed equally well in the first 24 hours. Data transmission loss (4.5%) occurred by a mismatch between signal transmission (2.5G) and signal reception (3G) protocols in cell phone towers (3G). The incidence of arrhythmias was not different between stroke/TIA and control groups.

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.

Atrial fibrillation is not uncommon among patients with ischemic stroke and transient ischemic stroke in China

Background

Atrial fibrillation (AF) is reported to be a less frequent cause of ischemic stroke in China than in Europe and North America, but it is not clear whether this is due to underestimation. Our aim was to define the true frequency of AF-associated stroke, to determine the yield of 6-day Holter ECG to detect AF in Chinese stroke patients, and to elucidate predictors of newly detected AF.

Methods

Patients with acute ischemic stroke or transient ischemic attack (TIA) were enrolled in a prospective, multicenter cohort study of 6-day Holter monitoring within 7 days after stroke onset at 20 sites in China between 2013 and 2015. Independent predictors of newly-detected AF were determined by multivariate analysis.

Results

Among 1511 patients with ischemic stroke and TIA (mean age 63 years, 33.1% women), 305 (20.2%) had either previously known (196, 13.0%) or AF newly-detected by electrocardiography (53, 3.5%) or by 6-day Holter monitoring (56/1262, 4.4%). A history of heart failure (OR = 4.70, 95%CI, 1.64–13.5), advanced age (OR = 1.06, 95%CI, 1.04–1.09), NIHSS at admission (OR = 1.06, 95%CI, 1.02–1.10), blood high density lipoprotein (HDL) (OR = 1.52, 95%CI, 1.09–2.13), together with blood triglycerides (OR = 0.64, 95%CI, 0.45–0.91) were independently associated with newly-detected AF.

Conclusions

Contrary to previous reports, AF-associated stroke is frequent (20%) in China if systemically sought. Prolonged noninvasive cardiac rhythm monitoring importantly increases AF detection in patients with recent ischemic stroke and TIA in China. Advanced age, history of heart failure, and higher admission NIHSS and higher level of HDL were independent indicators of newly-detected AF.

Trial registration

NCT02156765 (June 5, 2014).

Automatic detection of paroxysmal atrial fibrillation in patients with ischaemic stroke: better than routine diagnostic workup?

Background and purpose

Prolonged electrocardiogram (ECG) monitoring after ischaemic stroke increases the diagnostic yield of paroxysmal atrial fibrillation (pAF). In order to facilitate the additional workload involved in ECG analysis due to prolonged monitoring times, we investigated the effectiveness of pAF detection with an automated software algorithm (SA) in comparison to the routine staff‐based analysis (RA) during standard stroke‐unit care. Therefore, patients with acute ischaemic stroke or transitory ischaemic attack presenting with sinus rhythmus on the admission ECG and no history of atrial fibrillation were prospectively included.

Methods

A 24‐h Holter ECG assessment was performed using either RA based on a computer‐aided evaluation and subsequent review by a cardiologist or a commercially available automated SA. In the case of discordant results concerning the occurrence of pAF between the two methods, the data underwent an independent external rating.

Results

Of 809 prospectively enrolled patients, 580 patients fulfilled the inclusion criteria. pAF was ultimately diagnosed in 3.3% of the cohort (19 patients). SA and RA correctly diagnosed pAF in 17 patients resulting in a comparable diagnostic effectiveness of the analysis methods (sensitivity: SA 89.5% vs. RA 89.5%; specificity: SA 99.3% vs. RA 99.1%; κ, 0.686; P < 0.001; 95% confidence interval, 0.525–0.847). RA revealed clinically relevant ECG abnormalities in an additional seven patients.

Conclusions

Although it should not completely replace RA, SA‐based evaluation of Holter ECG reaches a high diagnostic effectiveness for the detection of pAF and can be used for a rapid and resource‐saving analysis of ECG data to deal with prolonged monitoring times.

A Simple, Non-Invasive Score to Predict Paroxysmal Atrial Fibrillation

Paroxysmal atrial fibrillation (pAF) is a major risk factor for stroke but remains often unobserved. To predict the presence of pAF, we developed model scores based on echocardiographic and other clinical parameters from routine cardiac assessment. The scores can be easily implemented to clinical practice and might improve the early detection of pAF. In total, 47 echocardiographic and other clinical parameters were collected from 1000 patients with sinus rhythm (SR; n = 728), pAF (n = 161) and cAF (n = 111). We developed logistic models for classifying between pAF and SR that were reduced to the most predictive parameters. To facilitate clinical implementation, linear scores were derived. To study the pathophysiological progression to cAF, we analogously developed models for cAF prediction. For classification between pAF and SR, amongst 12 selected model parameters, the most predictive variables were tissue Doppler imaging velocity during atrial contraction (TDI, A’), left atrial diameter, age and aortic root diameter. Models for classifying between pAF and SR or between cAF and SR showed areas under the ROC curves of 0.80 or 0.93, which resembles classifiers with high discriminative power. The novel risk scores were suitable to predict the presence of pAF based on variables readily available from routine cardiac assessment. Modelling helped to quantitatively characterize the pathophysiologic transition from SR via pAF to cAF. Applying the scores may improve the early detection of pAF and might be used as decision aid for initiating preventive interventions to reduce AF-associated complications.

Detection of Atrial Fibrillation Among Patients With Stroke Due to Large or Small Vessel Disease: A Meta-Analysis

BACKGROUND

Recent trials have demonstrated that extended cardiac monitoring increases the yield of paroxysmal atrial fibrillation (AF) detection in patients with cryptogenic stroke. The utility of extended cardiac monitoring is uncertain among patients with stroke caused by small and large vessel disease. We conducted a meta-analysis to estimate the yield of AF detection in this population.

METHODS AND RESULTS

We searched PubMed, Cochrane, and SCOPUS databases for studies on AF detection in stroke patients and excluded studies restricted to patients with cryptogenic stroke or transient ischemic attack. We abstracted AF detection rates for 3 populations grouped by stroke etiology: large vessel stroke, small vessel stroke, and stroke of undefined etiology (a mixture of cryptogenic, small vessel, large vessel, and other stroke etiologies). Our search yielded 30 studies (n=5687). AF detection rates were similar in patients with large vessel (2.2%, 95% CI 0.3-5.5; n=830) and small vessel stroke (2.4%, 95% CI 0.4-6.1; n=520). No studies had a monitoring duration longer than 7 days. The yield of AF detection in the undefined stroke population was higher (9.2%; 95% CI 7.1-11.5) compared to small vessel stroke (P=0.02) and large vessel stroke (P=0.02) populations.

CONCLUSIONS

AF detection rate is similar in patients with small and large vessel strokes (2.2-2.4%). Because no studies reported on extended monitoring (>7 days) in these stroke populations, we could not estimate the yield of AF detection with long-term cardiac monitoring. Randomized controlled trials are needed to examine the utility of AF detection with long-term cardiac monitoring (>7 days) in this patient population.

Left Atrial Function Is Impaired in Some Patients With Stroke of Undetermined Etiology: Potential Implications for Evaluation and Therapy

INTRODUCTION AND OBJECTIVES

Stroke etiology remains undetermined in up to 30% of cases. Paroxysmal atrial fibrillation is found in 20% to 28% of patients with stroke initially classified as being of undetermined etiology. The aim of our study was to analyze left atrial function in ischemic stroke patients to identify patterns associated with cardioembolic etiology and to determine whether the patterns identified can be found in individuals initially classified as having a stroke of undetermined etiology.

METHODS

We studied a cohort of in-hospital ischemic stroke patients referred for transthoracic echocardiography. Treating neurologists determined stroke etiology based on the TOAST classification. Left atrial contractile function was assessed using 2-dimensional echocardiography to determine their ejection fraction and speckle tracking to measure left atrial strain rate: a-wave. Left atrial function was compared between stroke etiology subgroups and healthy controls.

RESULTS

Ninety-seven patients (aged 67±15 years) with ischemic stroke (16.5% large-artery atherosclerosis, 15.5% small-vessel occlusion, 11.3% cardioembolic, 5.1% other determined etiology, 51.1% undetermined etiology) and 10 healthy volunteers (aged 63±7 years) were included. Left atrial ejection fraction was significantly decreased only in patients with stroke of cardioembolic and undetermined etiology compared with the control group (31.5±17.2%, 40.2±17.1%, and 59.1±8.4%, respectively; P=.004). The left atrial strain rate was significantly lower in patients with stroke caused by cardioembolic or undetermined etiology, or large-artery atherosclerosis compared with controls (-0.86±0.49, -1.31±0.56, -1.5±0.47, -2.37±1.18, respectively; P<.001).

CONCLUSIONS

Patients with stroke of undetermined etiology with left atrial function (ejection fraction and strain) similar to that of cardioembolic stroke patients may be misclassified and could potentially benefit from prolonged electrocardiography monitoring. Left atrial function analysis (ejection fraction and strain) might help to identify potential cardioembolic sources in patients with stroke of undetermined etiology.

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.