Continuous Stroke Unit Electrocardiographic Monitoring Versus 24-Hour Holter Electrocardiography for Detection of Paroxysmal Atrial Fibrillation After Stroke

Is Stroke risk analysis (SRA) a reliable method for predicting atrial fibrillation? A systematic review

INTRODUCTION

Atrial fibrillation is responsible for a considerable number of cases of cardioembolism, accounting for 17% to 30% of the etiologies of all strokes. The software known as Stroke Risk Analysis (SRA) detects patients at high risk of paroxysmal atrial fibrillation by analyzing a continuous electrocardiogram recorded over different periods of time.

OBJECTIVES

This article aims to carry out a systematic review investigating the effectiveness of the SRA method in predicting the risk of stroke patients having paroxysmal atrial fibrillation as the cause of the event.

METHODS

The methods correspond to the format of the International Prospective Register of Systematic Reviews Protocol, according to CRD Identification Code: CRD42021253974. A systematic search was carried out in BMJB, PubMed/MEDLINE, Science Direct and LILACS. Six cohort studies met the inclusion criteria, representing a total of 2,088 participants with stroke, and compared the detection of patients with paroxysmal atrial fibrillation on the continuous recording electrocardiogram with a time variation of 1 to 48h with the use of SRA.

RESULTS

Studies have shown that SRA has a high negative predictive value (between 96 and 99.1%) and can contribute to the selection of patients at high risk of paroxysmal atrial fibrillation to be referred for implantable cardiac monitoring to continue the investigation.

CONCLUSIONS

A sequential combination of SRA with implantable cardiac monitoring is a promising strategy for detecting undiagnosed paroxysmal atrial fibrillation. Thus, the SRA can act as a cost-effective pre-selection tool to identify patients at higher risk of having paroxysmal atrial fibrillation as a possible cause of stroke and who may benefit from implantable cardiac monitoring. However, the lack of randomized studies is a limitation that must be considered.

Rate of atrial fibrillation by Holter-Stroke Risk Analysis in undetermined TIA/rapidly improving stroke symptoms patients

Introduction

Holter-SRA (Stroke Risk Analysis) is an automated analysis of ECG monitoring for Atrial Fibrillation (AF) detection. The aim of this study was to evaluate the rate of AF in undetermined TIA/Rapidly improving stroke symptoms (RISS) patients.

Methods

Prospective study of undetermined TIA/RISS patients who presented to the emergency department. Early vascular studies (angio CT, transthoracic echocardiography and ECG) were performed in emergency department. The Holter-SRA device was placed for 2 h and the patients were classified into: confirmed AF, high risk of AF or low risk of AF. Prolonged ambulatory monitoring (7 days) was carried out every month for patients with a high-risk pattern. The results were evaluated until definitive detection of AF or low-risk pattern. The endpoints were rate of AF and vascular recurrence at 90 days.

Results

Over a period of 24 months, 83 undetermined TIA/RISS patients were enrolled. The mean age was 70 ± 10 years and 61% were men. The median ABCD2 score was 4 points (1-7). After 2 h of monitoring in the emergency department, AF was detected in one patient (1.2%), 51 patients with a low-risk pattern and 31 patients (37.3%) showed a high-risk pattern of AF. During the ambulatory monitoring, of the 31 patients high risk pattern patients, AF was diagnosed to 17 cases and of the 51 patients with a low-risk pattern, one case experienced a recurrent vascular due to undetected AF (1.9% false negative). Three patients (3.6%) suffered a vascular recurrence within the first 90 days, before AF diagnosis.

Conclusions

In our study, AF was detected in 22.9% of the 83 patients with indeterminate TIA/RISS. Holter-SRA has allowed us to increase the detection of AF, especially those patients with a high-risk pattern in the first 3 months.

Use of Anticoagulation for Thromboembolic Prophylaxis in Patients With Atrial High-Rate Episodes on Device Monitoring: A Narrative Review

Ischemic stroke and systemic thromboembolism are primary drivers of significant morbidity and mortality in patients with atrial fibrillation (AF). Although stroke is commonly the first index presentation of clinically silent AF, the growing use of continuous rhythm monitoring through cardiac implanted electronic devices has enabled earlier and increased detection of AF in patients who are otherwise asymptomatic before stroke development. Atrial high-rate episodes (AHREs) are atrial tachyarrhythmias frequently detected by cardiac implanted electronic devices; these events represent subclinical AF and other atrial tachyarrhythmias that can lead to stroke development and AF. Although the presence of AHREs increases the risk of developing both clinical AF and stroke compared with absence of AHREs, there has been a significant clinical variability in anticoagulation initiation in these subjects. In this narrative review, we explore the current evidence and published research surrounding the association between AHREs and stroke development in addition to the utility of anticoagulation in this population for thromboembolic prophylaxis.

Detecting atrial fibrillation in the polysomnography-derived electrocardiogram: a software validation study

PURPOSE

The present study validated a software-based electrocardiogram (ECG) analysis tool for detection of atrial fibrillation (AF) and risk for AF using polysomnography (PSG)-derived ECG recordings.

METHODS

The Stroke Risk Analysis® (SRA®) software was applied to 3-channel ECG tracings from diagnostic PSG performed in enrolled subjects including a subgroup of subjects with previously documented AF. No subjects used positive airway pressure therapy. All ECG recordings were visually analyzed by a blinded cardiologist.

RESULTS

Of subjects enrolled in the study, 93 had previously documented AF and 178 of 186 had an ECG that could be analyzed by either method. In subjects with known history of AF, automated analysis using SRA® classified 47 out of 87 ECG as either manifest AF or showing increased risk for paroxysmal AF (PAF) by SRA® (sensitivity 0.54, specificity 0.86). On visual analysis, 36/87 ECG showed manifest AF and 51/87 showed sinus rhythm. Among the latter subgroup, an increased risk for PAF was ascribed by SRA® in 11 cases (sensitivity 0.22, specificity 0.78) and by expert visual analysis in 5 cases (sensitivity 0.1, specificity 0.90). Among 36/178 ECG with manifest AF on visual analysis, 33 were correctly identified by the SRA® software (sensitivity and specificity 0.92).

CONCLUSION

Sleep studies provide a valuable source of ECG recordings that can be easily subjected to software-based analysis in order to identify manifest AF and automatically assess the risk of PAF. For optimal evaluability of data, multiple channel ECG tracings are desirable. For assessment of PAF risk, the SRA® analysis probably excels visual analysis, but sensitivity of both methods is low, reflecting that repeated ECG recording remains essential.

Datawarehouse-enabled quality control of atrial fibrillation detection in the stroke unit setting

Objective

(1) To assess the accuracy of a standard operating procedure (SOP) regarding the utilization of atrial fibrillation (AF) alarms in everyday clinical practice, and (2) to evaluate the performance of automated continuous surveillance for atrial fibrillation (AF) in hospitalized acute stroke patients.

Design

Retrospective cohort study.

Setting

Two stroke units from two tertiary care hospitals in Berlin, Germany.

Participants

We identified 635 patients with ischemic stroke diagnosis for the time period between 01. January and 30. September 2021 of which 176 patients had recorded AF alarms during monitoring. Of those, 115 patients were randomly selected for evaluation. After excluding 6 patients with hemorrhagic stroke in their records, 109 patients (mean age: 79.1 years, median NIHSS at admission: 6, 57% female) remained for analysis.

Intervention

Using a clinical data warehouse for comprehensive data storage we retrospectively downloaded and visualized ECG data segments of 65 s duration around the automated AF alarms. We restricted the maximum number of ECG segments to ten per patient. Each ECG segment plot was uploaded into a REDCap database and categorized as either AF, non-AF or artifact by manual review. Atrial flutter was subsumed as AF. These classifications were then matched with 1) medical history and known diseases before stroke, 2) discharge diagnosis, and 3) recommended treatment plan in the medical history using electronic health records.

Main outcome measures

The primary outcome was the proportion of previously unknown AF diagnoses correctly identified by the monitoring system but missed by the clinical team during hospitalization. Secondary outcomes included the proportion of patients in whom a diagnosis of AF would likely have led to anticoagulant therapy. We also evaluated the accuracy of the automated detection system in terms of its positive predictive value (PPV).

Results

We evaluated a total of 717 ECG alarm segments from 109 patients. In 4 patients (3.7, 95% confidence interval [CI] 1.18-9.68%) physicians had missed AF despite at least one true positive alarm. All four patients did not receive long-term secondary prevention in form of anticoagulant therapy. 427 out of 717 alarms were rated true positives, resulting in a positive predictive value of 0.6 (CI 0.56-0.63) in this cohort.

Conclusion

By connecting a data warehouse, electronic health records and a REDCap survey tool, we introduce a path to assess the monitoring quality of AF in acute stroke patients. We find that implemented standards of procedure to detect AF during stroke unit care are effective but leave room for improvement. Such data warehouse-based concepts may help to adjust internal processes or identify targets of further investigations.

Atrial Fibrillation Risk Assessment after Embolic Stroke of Undetermined Source

OBJECTIVE

Approximately 20% of strokes are embolic strokes of undetermined source (ESUS). Undetected atrial fibrillation (AF) remains an important cause. Yet, oral anticoagulation in unselected ESUS patients failed in secondary stroke prevention. Guidance on effective AF detection is lacking. Here, we introduce a novel, non-invasive AF risk assessment after ESUS.

METHODS

Catch-Up ESUS is an investigator-initiated, observational cohort study conducted between 2018 and 2019 at the Munich University Hospital. Besides clinical characteristics, patients received ≥72 h digital electrocardiogram recordings to generate the rhythm irregularity burden. Uni- and multivariable regression models predicted the primary endpoint of incident AF, ascertained by standardized follow-up including implantable cardiac monitors. Predictors included the novel rhythm irregularity burden constructed from digital electrocardiogram recordings. We independently validated our model in ESUS patients from the University Hospital Tübingen, Germany.

RESULTS

A total of 297 ESUS patients were followed for 15.6 ± 7.6 months. Incident AF (46 patients, 15.4%) occurred after a median of 105 days (25th to 75th percentile 31-33 days). Secondary outcomes were recurrent stroke in 7.7% and death in 6.1%. Multivariable-adjusted analyses identified the rhythm irregularity burden as the strongest AF-predictor (hazard ratio 3.12, 95% confidence interval 1.62-5.80, p < 0001) while accounting for the known risk factors age, CHA₂ DS₂ -VASc-Score, and NT-proBNP. Independent validation confirmed the rhythm irregularity burden as the most significant AF-predictor (hazard ratio 2.20, 95% confidence interval 1.45-3.33, p < 0001).

INTERPRETATION

The novel, non-invasive, electrocardiogram-based rhythm irregularity burden may help adjudicating AF risk after ESUS, and subsequently guide AF-detection after ESUS. Clinical trials need to clarify if high-AF risk patients benefit from tailored secondary stroke prevention. ANN NEUROL 2023;93:479-488.

Prediction of acute cerebrovascular stroke disability using mSOAR score (Stroke subtype, Oxfordshire Community Stroke Project, age, mRS and NIHSS)

Background

Stroke is among the most prevalent causes of disability. An easy reliable tool to predict stroke outcomes will help manage neurological and non-neurological events and rehabilitation. The modified SOAR (mSOAR) score, which includes stroke subtype, Oxfordshire Community Stroke Project (OCSP) classification, age, pre-stroke modified Rankin score (mRS), and National Institutes of Health Stroke Scale (NIHSS) is simple and easily calculated prognostic tool. The objective of this research was to test the ability of the mSOAR score to predict post-stroke disability as measured by mRS at discharge and 1 month after stroke onset.

Results

One hundred stroke patients (aged ≥ 18 years) were included. All subjects underwent complete neurologic examination, non-contrast head computed tomography. OCSP classification, Stroke subtype, NIHSS, and mRS score on discharge and 1 month after stroke onset were assessed for all patients. The mSOAR score was significantly correlated with mRS on discharge, after 1 month of stroke, and with the length of hospital stay. mSOAR score had high sensitivity and specificity for predicting moderate-to-severe disability on discharge and after 1 month of stroke onset.

Conclusion

The mSOAR is an excellent and accurate tool for predicting the severity of disability on discharge and 1-month post-stroke.

How is atrial fibrillation detected in everyday healthcare? Results of a Dutch cohort study

BACKGROUND

Atrial fibrillation (AF) is a common arrhythmia with serious potential consequences when left untreated. For timely treatment, early detection is imperative. We explored how new AF is detected in patients aged ≥ 65 years in Dutch healthcare.

METHODS

The study cohort consisted of 9526 patients from 49 Dutch general practices in the usual-care arm of the Detecting and Diagnosing Atrial Fibrillation study. We automatically extracted data from the electronic medical records and reviewed individual records of patients who developed AF. Patient selection started in 2015, and data collection ended in 2019.

RESULTS

We included 258 patients with newly diagnosed AF. In 55.0% of the patients, the irregular heartbeat was first observed in general practice and in 16.3% in the cardiology department. Cardiologists diagnosed most cases (47.3%), followed by general practitioners (GPs; 33.7%). AF detection was triggered by symptoms in 64.7% of the patients and by previous stroke in 3.5%. Overall, patients aged 65-74 years more often presented with symptoms than those aged ≥ 75 years (73.5% vs 60.6%; p = 0.042). In 31.5% of the patients, AF was diagnosed incidentally ('silent AF'). Silent-AF patients were on average 2 years older than symptomatic-AF patients. GPs less often diagnosed silent AF than symptomatic AF (21.0% vs 39.0%; p = 0.008), whereas physicians other than GPs or cardiologists more often diagnosed symptomatic AF than silent AF (34.6% vs 11.9%; p < 0.001). Most diagnoses were based on a 12-lead electrocardiogram (93.8%).

CONCLUSION

Diagnosing AF is a multidisciplinary process. The irregular heartbeat was most often detected by the GP, but cardiologists diagnosed most cases. One-third of all newly diagnosed AF was silent.

The accuracy of the Stroke Risk Analysis (SRA) system for predicting atrial fibrillation in patients in the postoperative period of myocardial revascularization

INTRODUCTION

Postoperative myocardial revascularization atrial fibrillation (POAF) is a clinical complication that affects about 30% of patients and its mechanisms of origin are still poorly understood. This fact makes it difficult to identify the patient at greatest risk for this arrhythmia. This mission seems evident due to the complications it entails, including longer hospital stays, risk of stroke, heart failure, and death. There are reports of preoperative clinical aspects inherent to the patient's condition, such as gender and age, and discontinuation of beta-blockers as risk factors. In addition, additional information obtained by electrocardiogram, echocardiogram, and blood count data, for example, present only modest predictive results. The analysis of heart rate and heart rate variability obtained by the Stroke Risk Analysis System (SRA) is a technique used to predict ambulatory atrial fibrillation (AF), using recordings of only one hour showing good accuracy. This system, however, has not yet been used to predict the emergence of POAF. The rationale for its use is based on the suspicion that the emergence of POAF is strongly related to sympatho-vagal imbalance and the increase in atrial ectopia, that is, changes in heart rhythm, the main variables analyzed by the SRA algorithm.

OBJECTIVE

To assess the accuracy of the SRA to identify patients at risk of having POAF after coronary artery bypass graft surgery (CABG).

METHOD

114 consecutive patients with coronary artery disease underwent coronary artery bypass grafting between the years 2015 and 2018. Between the first and fifth postoperative days, they underwent continuous electrocardiographic monitoring using the Holter system for cardiac rhythm analysis. Patients were divided into two groups: Group I was formed of those with POAF and Group II included patients without POAF. The tracings obtained by Holter were reanalyzed using the CardioManager®/Cardios program, converted and divided into one-hour sections using the SRA®/Cardios and Geratherm Converter program and submitted to the SRA-Apoplex medical/Geratherm® analysis algorithm. The SRA identifies three possibilities for classifying patient risk: a) Risk 0: patient in sinus rhythm; b) Risk 1: patient at increased risk for paroxysmal AF; c) Risk 2: patient with AF already present. For Group I, SRA were considered positive when Risks 1 and 2 were identified. For Group II, those identified as Risk 0 were considered negative SRA.

RESULTS

POAF occurred in 33/114 patients (28%). The sensitivity, specificity, positive predictive value, and negative predictive value of the SRA to identify patients with POAF were 69%, 84%, 69%, and 82%, respectively; the positive and negative likelihood ratios, in addition to the accuracy of the SRA were, respectively, 4.3%, 0.36%, and 79%. A subanalysis of the results of the day on which AF occurred was performed on the records obtained in the first three hours of recording and up to three hours before the appearance of POAF. In the first period, the SRA was able to predict POAF in 57% of cases, while in the second period, the system identified the arrhythmia in 83% of cases.

CONCLUSIONS

a) The SRA presents good accuracy to predict POAF; b) its accuracy is moderate in the first three hours of recording; c) the accuracy increases significantly near the beginning of POAF; d) these findings indicate that electrophysiological changes that precede POAF are acute, occurring a few hours before the event and are identified by the SRA algorithm.

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.

Cost-Effectiveness of Monitoring Patients Post-Stroke With Mobile ECG During the Hospital Stay

Background

The effectiveness of a nurse‐led in‐hospital monitoring protocol with mobile ECG (iECG) was investigated for detecting atrial fibrillation in patients post‐ischemic stroke or post‐transient ischemic attack. The study aimed to assess the cost‐effectiveness of using iECG during the initial hospital stay compared with standard 24‐hour Holter monitoring.

Methods and Results

A Markov microsimulation model was constructed to simulate the lifetime health outcomes and costs. The rate of atrial fibrillation detection in iECG and Holter monitoring during the in‐hospital phase and characteristics of modeled population (ie, age, sex, CHA2DS2‐VASc) were informed by patient‐level data. Costs related to recurrent stroke, stroke management, medications (new oral anticoagulants), and rehabilitation were included. The cost‐effectiveness analysis outcome was calculated as an incremental cost per quality‐adjusted life‐year gained. As results, monitoring patients with iECG post‐stroke during the index hospitalization was associated with marginally higher costs (A$31 196) and greater benefits (6.70 quality‐adjusted life‐years) compared with 24‐hour Holter surveillance (A$31 095 and 6.66 quality‐adjusted life‐years) over a 20‐year time horizon, with an incremental cost‐effectiveness ratio of $3013/ quality‐adjusted life‐years. Monitoring patients with iECG also contributed to lower recurrence of stroke and stroke‐related deaths (140 recurrent strokes and 20 deaths avoided per 10 000 patients). The probabilistic sensitivity analyses suggested iECG is highly likely to be a cost‐effective intervention (100% probability).

Conclusions

A nurse‐led iECG monitoring protocol during the acute hospital stay was found to improve the rate of atrial fibrillation detection and contributed to slightly increased costs and improved health outcomes. Using iECG to monitor patients post‐stroke during initial hospitalization is recommended to complement routine care.

Association between CHARGE-AF risk score and LA mechanics: LA reservoir strain can be a single parameter for predicting AF risk

AIMS

Atrial fibrillation (AF) is a prevalent arrhythmia and the leading preventable cause of cardioembolic stroke. Scoring systems for predicting AF risk do not use imaging modalities. We sought to determine whether LA longitudinal strain could be used as a single parameter for predicting the risk of AF.

METHODS AND RESULTS

Consecutive patients diagnosed with diastolic dysfunction between December 2019 and March 2020 were included. Two-dimensional, colour flow, continuous pulse-wave, and tissue Doppler transthoracic echocardiography (TTE) were performed using a Vivid E9 imaging system (GE Medical Systems, Chicago, USA). Measurements were obtained in the standard manner recommended by the American Society of Echocardiography. Moreover, LA longitudinal strain was measured using 2D speckle tracking echocardiography in the four-chamber view to evaluate left atrial function. The CHARGE-AF scoring system was used to predict AF risk.A total of 148 patients (mean age: 57.6 ± 11.9; male: 53%) with feasible views for LA strain measurement were divided into two groups based on a 10% CHARGE-AF cut-off score. The >10% group (48 patients; 32%) was defined as having a predicted 5-year AF risk >10%, and the ≤10% group (100 patients; 68%) was defined as having a predicted risk <10%. In the multivariate analysis, LA reservoir strain (LASr) was independently associated with CHARGE-AF score. Furthermore, using the Pearson correlation method, LASr was found to be highly correlated with CHARGE-AF score (r = -0.74, p < 0.0001).

CONCLUSIONS

LASr was highly correlated with CHARGE-AF risk score and may be used as a parameter to predict atrial myopathy and hence AF risk.

Clinical Implications of Atrial Fibrillation Detection Using Wearable Devices in Patients With Cryptogenic Stroke (CANDLE-AF) Trial: Design and Rationale

Background

Although many electrocardiography wearable devices have been released recently for the detection of atrial fibrillation (AF), there are few studies reporting prospective data for wearable devices compared to the strategy of the existing guidelines in the detection of atrial fibrillation (AF) after cryptogenic stroke. A tiny single-patch monitor is more convenient than a conventional Holter monitor recording device and, therefore, longer duration of monitoring may be acceptable.

Methods and Design

The CANDLE-AF study is a multicenter, prospective, randomized controlled trial. Patients with transient ischemic attack or ischemic stroke without any history of AF will be enrolled. The superiority of the 72-h single-patch monitor to standard strategy and non-inferiority of the 72-h single-patch monitor to an event-recorder-type device will be investigated. Single-patch monitor arm will repeat monitoring at 1, 3, 6, and 12 months, event-recorder-type arm will repeat monitoring twice daily for 12 months. The enrollment goal is a total of 600 patients, and the primary outcome is the detection of AF which continues at least 30 s during study period. The secondary outcome is the rate of changes from antiplatelet to anticoagulant and major adverse cardiac and cerebrovascular events within 1 year.

Conclusions

The results of CANDLE-AF will clarify the role of a single-lead patch ECG for the early detection of AF in patients with acute ischemic stroke. In addition, the secondary outcome will be analyzed to determine whether more sensitive AF detection can affect the prognosis and if further device development is meaningful. (cris.nih.go.kr KCT0005592).

Using machine learning to predict atrial fibrillation diagnosed after ischemic stroke

BACKGROUND

Selecting best candidates for prolonged poststroke cardiac monitoring in acute ischemic stroke (AIS) patients is still challenging. We aimed to develop a machine learning (ML) model to select AIS patients at high risk of poststroke atrial fibrillation (AF) for prolonged cardiac monitoring and then to compare ML model with traditional risk scores and classic statistical logistic regression (classic-LR) model.

METHODS

AIS patients from July 2012 to September 2020 across Nanjing First Hospital were collected. We performed the LASSO regression for selecting the critical features and built five ML models to assess the risk of poststroke AF. The SHAP and partial dependence plot (PDP) method were introduced to interpret the optimal model. We also compared ML model with CHADS₂ score, CHA₂DS₂-VASc score, AS5F score, HAVOC score, and classic-LR model.

RESULTS

A total of 3929 AIS patients were included. Among the five ML models, deep neural network (DNN) was the model with best performance. It also exhibited superior performance compared with CHADS₂ score, CHA₂DS₂-VASc score, AS5F score, HAVOC score and classic-LR model. The results of SHAP and PDP method revealed age, cardioembolic stroke, large-artery atherosclerosis stroke, and NIHSS score at admission were the top four important features and revealed the DNN model had good interpretability and reliability.

CONCLUSION

The DNN model achieved best performance and improved prediction performance compared with traditional risk scores and classic-LR model. The DNN model can be applied to identify AIS patients at high risk of poststroke AF as best candidates for prolonged poststroke cardiac monitoring.

Cryptogenic Stroke and Embolic Stroke of Undetermined Source: Risk Factors and Approaches for Detection of Atrial Fibrillation

BACKGROUND

Stroke is a problem worldwide because of its high mortality and disability rates. Almost 90% of strokes are ischemic, and more than half of the deaths are caused by an ischemic stroke. Most risk factors for stroke are manageable so that it can be avoided with proper prevention. Despite the success in determining the causes of stroke in recent years, selectively, the "culprit" causing stroke remains unsolved. In such cases, a diagnosis of undetermined etiology (cryptogenic stroke) or embolic stroke of undetermined source (ESUS) is generated, resulting the prevention of a recurrent cerebrovascular occurrence impossible. Atrial fibrillation (AF) can be a cause of stroke by causing blood clots in the chambers of the heart.

PURPOSE

The aim was to determine the optimal method of heart rate monitoring in patients with ischemic stroke, as methods and approaches for detecting AF are very diverse, but there is still no single opinion, which would be universal.

PROCEDURES

In our review, we consider epidemiology, risk factors for the stroke of undetermined etiology, as well as analytical methods for detecting heart rhythm disturbances in this category of patients.

FINDINGS

Atrial fibrillation (AF) is detected by thorough monitoring of heart rate of patients with cryptogenic stroke and ESUS can be diagnosed in up to 46% of patients. .

CONCLUSION

After AF detection, consideration should be given to prescribing anticoagulants, instead of antiplatelet agents, for the secondary prevention of stroke.

Does Chronic Kidney Disease Have an Impact on the Use of Oral Anticoagulants after Stroke? An Observational Follow-Up Study

INTRODUCTION

Chronic kidney disease is common in patients with acute ischemic stroke. We investigated whether chronic kidney disease has an impact on anticoagulation treatment recommendations after ischemic stroke or transient ischemic attack (TIA) related with atrial fibrillation (AF).

MATERIALS AND METHODS

We extracted treatment-related data concerning stroke/TIA patients with AF and available estimated glomerular filtration rates (eGFR) from a monocentric prospective German stroke registry. Chronic kidney disease was defined as eGFR <60 mL/min/1.73 m2. Using uni- and multivariate logistic regression analyses, we investigated whether chronic kidney disease was associated with a lower probability to be treated with anticoagulation early after stroke.

RESULTS

A total of 273 patients entered the analysis. In 242 AF patients (88.6%), oral anticoagulation was recommended after stroke. In multivariate logistic regression analysis, chronic kidney disease was not identified as an independent factor for the decision against anticoagulation (OR 1.63, 95% CI: 0.50-5.31, p = 0.421); only increasing age (OR 1.10, 95% CI: 1.00-1.21, p = 0.061) and a modified Rankin Scale >3 at discharge (OR 3.41, 95% CI: 0.88-13.24, p = 0.077) showed a nonsignificant trend for the decision to omit anticoagulation. A total of 155 of 167 patients (92.8%) were still anticoagulated at follow-up. A total of 44 patients with chronic kidney disease completed follow-up, and of those, 37 were still anticoagulated (84%). In patients without chronic kidney disease, 118/167 (70.7%) had continued anticoagulation (p = 0.310).

CONCLUSION

Our results show that chronic kidney disease was not the main factor in the decision to withhold oral anticoagulation in patients with recent stroke/TIA and AF.

Effect of Long-term Continuous Cardiac Monitoring vs Usual Care on Detection of Atrial Fibrillation in Patients With Stroke Attributed to Large- or Small-Vessel Disease: The STROKE-AF Randomized Clinical Trial

IMPORTANCE

Patients with ischemic stroke attributed to large- or small-vessel disease are not considered at high risk for atrial fibrillation (AF), and the AF incidence rate in this population is unknown.

OBJECTIVES

To determine whether long-term cardiac monitoring is more effective than usual care for AF detection in patients with stroke attributed to large- or small-vessel disease through 12 months of follow-up.

DESIGN, SETTING, AND PARTICIPANTS

The STROKE-AF trial was a randomized (1:1), multicenter (33 sites in the US) clinical trial that enrolled 496 patients between April 2016 and July 2019, with primary end point follow-up through August 2020. Eligible patients were aged 60 years or older or aged 50 to 59 years with at least 1 additional stroke risk factor and had an index stroke attributed to large- or small-vessel disease within 10 days prior to insertable cardiac monitor (ICM) insertion.

INTERVENTIONS

Patients randomized to the intervention group (n = 242) received ICM insertion within 10 days of the index stroke; patients in the control group (n = 250) received site-specific usual care consisting of external cardiac monitoring, such as 12-lead electrocardiograms, Holter monitoring, telemetry, or event recorders.

MAIN OUTCOMES AND MEASURES

Incident AF lasting more than 30 seconds through 12 months.

RESULTS

Among 492 patients who were randomized (mean [SD] age, 67.1 [9.4] years; 185 [37.6%] women), 417 (84.8%) completed 12 months of follow-up. The median (interquartile range) CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age 65 to 74 years, sex category) score was 5 (4-6). AF detection at 12 months was significantly higher in the ICM group vs the control group (27 patients [12.1%] vs 4 patients [1.8%]; hazard ratio, 7.4 [95% CI, 2.6-21.3]; P < .001). Among the 221 patients in the ICM group who received an ICM, 4 (1.8%) had ICM procedure-related adverse events (1 site infection, 2 incision site hemorrhages, and 1 implant site pain).

CONCLUSIONS AND RELEVANCE

Among patients with stroke attributed to large- or small-vessel disease, monitoring with an ICM compared with usual care detected significantly more AF over 12 months. However, further research is needed to understand whether identifying AF in these patients is of clinical importance.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02700945.

Update on Biomarkers Associated to Cardioembolic Stroke: A Narrative Review

Background: In the last years, several studies were conducted that evaluated biomarkers that could be helpful for cardioembolic stroke diagnosis, prognosis, and the determination of risk of stroke recurrence. Methods: We performed a narrative review of the main studies that evaluated biomarkers related to specific cardioembolic causes: atrial fibrillation, patent foramen ovale, atrial cardiomyopathy, and left ventricular wall motion abnormalities. Results: BNP and NT-proBNP are, among all biomarkers of cardioembolic stroke, the ones that have the highest amount of evidence for their use. NT-proBNP is currently used for the selection of patients that will be included in clinical trials that aim to evaluate the use of anticoagulation in patients suspected of having a cardioembolic stroke and for the selection of patients to undergo cardiac monitoring. NT-proBNP has also been incorporated in tools used to predict the risk of stroke recurrence (ABC-stroke score). Conclusions: NT-proBNP and BNP continue to be the biomarkers most widely studied in the context of cardioembolic stroke. The possibility of using other biomarkers in clinical practice is still distant, mainly because of the low methodological quality of the studies in which they were evaluated. Both internal and external validation studies are rarely performed for most biomarkers.

Different aspects of early and late development of atrial fibrillation during hospitalization in cryptogenic stroke

The detection of underlying atrial fibrillation (AF) has become increasingly possible by insertable cardiac monitoring (ICM). During hospitalization for cryptogenic stroke, factors related to the early and late development of AF have not been studied. CHALLENGE ESUS/CS is a multicenter registry of cryptogenic stroke patients undergoing transesophageal echocardiography. Twelve-lead electrocardiogram, continuous cardiac monitoring, and 24-h Holter electrocardiogram were all used for the detection of AF. Early and late detection of AF was determined with an allocation ratio of 1:1 among patients with AF. A total of 677 patients (68.7 ± 12.8 years; 455 men) were enrolled, and 64 patients developed AF during hospitalization. Four days after admission was identified as the approximate median day to classify early and late phases to detect AF: ≤ 4 days, 37 patients; > 4 days, 27 patients. Multiple logistic regression analysis showed that spontaneous echo contrast (SEC) (OR 5.91; 95% CI 2.19–15.97; p < 0.001) was associated with AF ≤ 4 days, whereas a large infarction > 3 cm in diameter (OR 3.28; 95% CI 1.35–7.97; p = 0.009) was associated with AF > 4 days. SEC and large infarctions were important predictors of in-hospital AF detection, particularly in the early and late stages, respectively; thus, they could serve as indications for recommending ICM.

Research Priorities in Atrial Fibrillation Screening: A Report From a National Heart, Lung, and Blood Institute Virtual Workshop

Clinically recognized atrial fibrillation (AF) is associated with higher risk of complications, including ischemic stroke, cognitive decline, heart failure, myocardial infarction, and death. It is increasingly recognized that AF frequently is undetected until complications such as stroke or heart failure occur. Hence, the public and clinicians have an intense interest in detecting AF earlier. However, the most appropriate strategies to detect undiagnosed AF (sometimes referred to as subclinical AF) and the prognostic and therapeutic implications of AF detected by screening are uncertain. Our report summarizes the National Heart, Lung, and Blood Institute's virtual workshop focused on identifying key research priorities related to AF screening. Global experts reviewed major knowledge gaps and identified critical research priorities in the following areas: (1) role of opportunistic screening; (2) AF as a risk factor, risk marker, or both; (3) relationship between AF burden detected with long-term monitoring and outcomes/treatments; (4) designs of potential randomized trials of systematic AF screening with clinically relevant outcomes; and (5) role of AF screening after ischemic stroke. Our report aims to inform and catalyze AF screening research that will advance innovative, resource-efficient, and clinically relevant studies in diverse populations to improve the diagnosis, management, and prognosis of patients with undiagnosed AF.

Detection of Atrial Fibrillation on Stroke Units: Comparison of Manual versus Automatic Analysis of Continuous Telemetry

BACKGROUND

Detection of atrial fibrillation (AF) is one of the primary diagnostic goals for patients on a stroke unit. Physician-based manual analysis of continuous ECG monitoring is regarded as the gold standard for AF detection but requires considerable resources. Recently, automated computer-based analysis of RR intervals was established to simplify AF detection. The present prospective study analyzes both methods head to head regarding AF detection specificity, sensitivity, and overall effectiveness.

METHODS

Consecutive stroke patients without history of AF or proof of AF in the admission ECG were enrolled over the period of 7 months. All patients received continuous ECG telemetry during the complete stay on the stroke unit. All ECGs underwent automated analysis by a commercially available program. Blinded to these results, all ECG tracings were also assessed manually. Sensitivity, specificity, time consumption, costs per day, and cost-effectiveness were compared.

RESULTS

216 consecutive patients were enrolled (70.7 ± 14.1 years, 56% male) and 555 analysis days compared. AF was detected by manual ECG analysis on 37 days (6.7%) and automatically on 57 days (10.3%). Specificity of the automated algorithm was 94.6% and sensitivity 78.4% (28 [5.0%] false positive and 8 [1.4%] false negative). Patients with AF were older and had more often arterial hypertension, higher NIHSS at admission, more often left atrial dilatation, and a higher CHA2DS2-VASc score. Automation significantly reduced human resources but was more expensive compared to manual analysis alone.

CONCLUSION

Automatic AF detection is highly specific, but sensitivity is relatively low. Results of this study suggest that automated computer-based AF detection should be rather complementary to manual ECG analysis than replacing it.

Diagnostic yield of chest and thumb ECG after cryptogenic stroke, Transient ECG Assessment in Stroke Evaluation (TEASE): an observational trial

OBJECTIVE

In stroke survivors, atrial fibrillation (AF) is typically evaluated solely by short-term ECG monitoring in the stroke unit. Prolonged continuous ECG monitoring or insertable cardiac monitors require substantial resources. Chest and thumb ECG could provide an alternative means of AF detection, which in turn could allow prompt anticoagulation to prevent recurrent stroke. The objective of this study was to assess the yield of newly diagnosed AF during 28 days of chest and thumb ECG monitoring two times per day in cryptogenic stroke.

METHODS

This study, Transient ECG Assessment in Stroke Evaluation, included patients who had a stroke from Region Gävleborg, Sweden, between 2017 and 2019. Patients with a recent ischaemic stroke without documented AF (or other reasons for anticoagulation) before or during ECG evaluation in the stroke unit were evaluated using the Coala Heart Monitor connected to a smartphone application for remote monitoring.

RESULTS

The prespecified number of 100 patients (mean age 67.6±10.8 years; 60% men) was analysed. In nine patients (9%, number needed to screen 11) AF but no other significant atrial arrhythmias (>30 s) was diagnosed. The mean CHA₂DS₂-VASc score was similar among patients with AF and no AF (4.9±1.1 vs 4.3±1.3; p=0.224) and patients with AF were older (74.3±9.0 vs 66.9±10.8; p=0.049). Patients performed on average 90.1%±15.0% of scheduled transmissions.

CONCLUSION

In evaluation of cryptogenic stroke, 9% of patients had AF detected using chest and thumb ECG two times per day during 1 month. In many stroke survivors, this is a feasible approach and they will be potentially protected from recurrent stroke by anticoagulation treatment.

TRIAL REGISTRATION NUMBER

NCT03301662.

Software-based analysis of 1-hour Holter ECG to select for prolonged ECG monitoring after stroke

Objective

Identification of ischemic stroke patients at high risk for paroxysmal atrial fibrillation (pAF) during 72 hours Holter ECG might be useful to individualize the allocation of prolonged ECG monitoring times, currently not routinely applied in clinical practice.

Methods

In a prospective multicenter study, the first analysable hour of raw ECG data from prolonged 72 hours Holter ECG monitoring in 1031 patients with acute ischemic stroke/TIA presenting in sinus rhythm was classified by an automated software (AA) into “no risk of AF” or “risk of AF” and compared to clinical variables to predict AF during 72 hours Holter‐ECG.

Results

pAF was diagnosed in 54 patients (5.2%; mean age: 78 years; female 56%) and was more frequently detected after 72 hours in patients classified by AA as “risk of AF” (n = 21, 17.8%) compared to “no risk of AF” (n = 33, 3.6%). AA‐based risk stratification as “risk of AF” remained in the prediction model for pAF detection during 72 hours Holter ECG (OR3.814, 95% CI 2.024‐7.816, P < 0.001), in addition to age (OR1.052, 95% CI 1.021‐1.084, P = 0.001), NIHSS (OR 1.087, 95% CI 1.023‐1.154, P = 0.007) and prior treatment with thrombolysis (OR2.639, 95% CI 1.313‐5.306, P = 0.006). Similarly, risk stratification by AA significantly increased the area under the receiver operating characteristic curve (AUC) for prediction of pAF detection compared to a purely clinical risk score (AS5F alone: AUC 0.751; 95% CI 0.724‐0.778; AUC for the combination: 0.789, 95% CI 0.763‐0.814; difference between the AUC P = 0.022).

Interpretation

Automated software‐based ECG risk stratification selects patients with high risk of AF during 72 hours Holter ECG and adds predictive value to common clinical risk factors for AF prediction.

Comparison of Arrhythmia Detection by 24-Hour Holter and 14-Day Continuous Electrocardiography Patch Monitoring

BACKGROUND

Although 24-hour Holter monitoring is routinely used for patients with suspected paroxysmal arrhythmia, its sensitivity in detecting such arrhythmias is insufficient.

METHODS

We compared a 14-day electrocardiography (ECG) monitor patch - a single-use, noninvasive, waterproof, continuous monitoring patch - with a 24-hour Holter monitor in 32 consecutive patients with suspected arrhythmia.

RESULTS

The 14-day ECG patch was well tolerated, and its rates of detection of relevant arrhythmias on days 1, 3, 7, and 14 were 13%, 28%, 47%, and 66%, respectively. The detection rate of paroxysmal arrhythmias was significantly higher for the 14-day ECG patch than for the 24-hour Holter monitor (66% vs. 9%, p < 0.001). Among the 32 patients, 202 atrial fibrillation or atrial flutter episodes were detected in 6 patients (22%) with the 14-day ECG patch; however, only 1 atrial fibrillation episode was detected in a patient (3%, p < 0.05) with the 24-hour Holter monitor. Other clinically relevant arrhythmias recorded on the 14-day ECG patch included 21 (65.5%) episodes of supraventricular tachycardia, 2 (6.3%) long pause, and 2 (6.3%) ventricular arrhythmias. The mean dermal response score immediately after removal of the 14-day ECG patch from the patients was 0.64, which indicated minimal erythema.

CONCLUSIONS

The 14-day ECG patch was well tolerated and allowed for longer continuous monitoring than the 24-hour Holter monitor, thus resulting in improved clinical accuracy in the detection of paroxysmal arrhythmias. Future studies should examine the long-term effectiveness of 14-day ECG patches for managing selected patients.

Cryptogenic stroke and atrial fibrillation in a real-world population: the role of insertable cardiac monitors

The incidence of atrial fibrillation (AF) in cryptogenic stroke (CS) patients has been studied in carefully controlled clinical trials, but real-world data are limited. We investigated the incidence of AF in clinical practice among CS patients with an insertable cardiac monitor (ICM) placed for AF detection. Patients with CS admitted to our Stroke Unit were included in the study; they received an ICM and were monitored for up to 3 years for AF detection. All detected AF episodes of at least 120 sec were considered. From March 2016 to March 2019, 58 patients (mean age 68.1 ± 9.3 years, 67% male) received an ICM to detect AF after a CS. No patients were lost to follow-up. AF was detected in 24 patients (41%, AF group mean age 70.8 ± 9.4 years, 62% male) after a mean time of 6 months from ICM (ranging from 2 days to 2 years) and 8 months after CS (ranging from 1 month to 2 years). In these AF patients, anticoagulant treatment was prescribed and nobody had a further stroke. In conclusion, AF episodes were detected via continuous monitoring with ICMs in 41% of implanted CS patients. AF in CS patients is asymptomatic and difficult to diagnose by strategies based on intermittent short-term recordings. Therefore, we suggest that ICMs should be part of daily practice in the evaluation of CS patients.

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.

Non-vitamin K oral anticoagulants (NOACs) in patients with stroke and atrial fibrillation

Patients with atrial fibrillation who had a previous transient ischemic attack or ischemic stroke had a significantly high risk of stroke recurrence and the introduction of oral anticoagulants should be mandatory. However, the long-term use of oral anticoagulants increases the risk of developing all types of intracranial hemorrhages. The advantages of non-vitamin K oral anticoagulants (NOACs) compared to warfarin are that they have a significantly lower risk for hemorrhagic stroke. They are preferred in elderly patients, those with small vessel disease, or those with previous intracerebral hemorrhage. The time of NOACs introduction after an ischemic stroke depends on its severity and the rule "1-3-6-12" days should be applied. The reintroduction of NOACs in patients with atrial fibrillation and previous intracerebral hemorrhage depends on its etiology and should be after about 4-8 weeks if the cardioembolic risk is high and the risk for intracranial hemorrhage small.

Stroke Risk Analysis, a System With a High Detection Rate of Atrial Fibrillation in Stroke and Transient Ischemic Attack

Background and Purpose- Stroke Risk Analysis (SRA) comprises an algorithm for automated analysis of ECG monitoring, enabling the detection of paroxysmal atrial fibrillation (pxAF) and identifying patterns indicating a high risk of atrial fibrillation (R_AF). We compared Holter-enabled continuous ECG monitoring in combination with SRA (hSRA) with standard continuous ECG monitoring for pxAF detection in patients with acute ischemic stroke. Also, we sought to identify whether the detection of R_AF patterns during the first cycle (first 2 hours) of hSRA recording was associated with the detection of pxAF during the Stroke Unit stay. Methods- We enrolled 524 consecutive patients admitted in the Stroke Unit with acute ischemic stroke or transient ischemic attack with neither history of AF nor AF at admission into a prospective multicentric observational analytic clinical study with intrapatient comparison, who received both continuous ECG monitoring as well as hSRA up to 7 days. Investigators were blinded to hSRA results unless pxAF was detected on SRA. Results- Of the 524 consecutive acute stroke patients (median age, 70.0 years; 60% male; acute ischemic stroke 93%, transient ischemic attack 7%), 462 were eligible and included in the study. Among 462 patients with hSRA available for 66 hours, AF was documented by hSRA in 79 patients (17.1%). From this group, 45 AF cases (9.7%) were confirmed after review by an independent and blinded cardiologist. continuous ECG monitoring detected 21 AF cases (4.3%; P<0.0001). hSRA detected R_AF patterns in 92 patients. 35 out of the 92 R_AF patients showed an episode of AF during the Stroke Unit stay. Predictive values of R_AF patterns within the first cycle of hSRA were: sensitivity 71%, specificity 86%, positive predictive value 38%, and negative predictive value 96%. Conclusions- Automated analysis using SRA technology strongly improves pxAF detection in acute ischemic stroke patients compared with continuous ECG monitoring. The predictive value of a R_AF pattern, as detected by hSRA during the first few hours after admission, deserves further investigation.

Searching for Atrial Fibrillation Poststroke: A White Paper of the AF-SCREEN International Collaboration

Cardiac thromboembolism attributed to atrial fibrillation (AF) is responsible for up to one-third of ischemic strokes. Stroke may be the first manifestation of previously undetected AF. Given the efficacy of oral anticoagulants in preventing AF-related ischemic strokes, strategies of searching for AF after a stroke using ECG monitoring followed by oral anticoagulation (OAC) treatment have been proposed to prevent recurrent cardioembolic strokes. This white paper by experts from the AF-SCREEN International Collaboration summarizes existing evidence and knowledge gaps on searching for AF after a stroke by using ECG monitoring. New AF can be detected by routine plus intensive ECG monitoring in approximately one-quarter of patients with ischemic stroke. It may be causal, a bystander, or neurogenically induced by the stroke. AF after a stroke is a risk factor for thromboembolism and a strong marker for atrial myopathy. After acute ischemic stroke, patients should undergo 72 hours of electrocardiographic monitoring to detect AF. The diagnosis requires an ECG of sufficient quality for confirmation by a health professional with ECG rhythm expertise. AF detection rate is a function of monitoring duration and quality of analysis, AF episode definition, interval from stroke to monitoring commencement, and patient characteristics including old age, certain ECG alterations, and stroke type. Markers of atrial myopathy (eg, imaging, atrial ectopy, natriuretic peptides) may increase AF yield from monitoring and could be used to guide patient selection for more intensive/prolonged poststroke ECG monitoring. Atrial myopathy without detected AF is not currently sufficient to initiate OAC. The concept of embolic stroke of unknown source is not proven to identify patients who have had a stroke benefitting from empiric OAC treatment. However, some embolic stroke of unknown source subgroups (eg, advanced age, atrial enlargement) might benefit more from non-vitamin K-dependent OAC therapy than aspirin. Fulfilling embolic stroke of unknown source criteria is an indication neither for empiric non-vitamin K-dependent OAC treatment nor for withholding prolonged ECG monitoring for AF. Clinically diagnosed AF after a stroke or a transient ischemic attack is associated with significantly increased risk of recurrent stroke or systemic embolism, in particular, with additional stroke risk factors, and requires OAC rather than antiplatelet therapy. The minimum subclinical AF duration required on ECG monitoring poststroke/transient ischemic attack to recommend OAC therapy is debated.

Are atrial high rate episodes (AHREs) a precursor to atrial fibrillation?

Abstract

Atrial high rate episodes (AHREs), also termed, subclinical atrial tachyarrhythmias or subclinical atrial fibrillation (AF) are an important cardiovascular condition. Advancement in implantable cardiac devices such as pacemakers or internal cardiac defibrillators has enabled the continuous assessment of atrial tachyarrhythmias in patients with an atrial lead. Patients with device-detected AHREs are at an elevated risk of stroke and may have unmet anticoagulation needs. While the benefits of oral anticoagulation for stroke prevention in patients with clinical AF are well recognised, it is not known whether the same risk–benefit ratio exists for anticoagulation therapy in patients with AHREs. The occurrence and significance of AHRE are increasingly acknowledged but these events are still not often acted upon in patients presenting with stroke and TIA. Additionally, patients with AHRE show a significant risk for major adverse cardiovascular events (MACE) including acute heart failure, myocardial infarction, cardiovascular hospitalisation, ventricular tachycardia/fibrillation, which is dependent on AHRE burden. In this review, we present an overview of this relatively new entity, its associated thromboembolic risk and its management implications.

Graphic abstract

MR-imaging pattern is not a predictor of occult atrial fibrillation in patients with cryptogenic stroke

Background

To date, insertable cardiac monitors (ICMs) are the most effective method for the detection of occult atrial fibrillation (AF) in cryptogenic stroke. The overall detection rate after 12 months, however, is low and ranges between 12.4 and 33.3%, even if clinical predictors are considered. Ischemic stroke patients due to cardiogenic embolism present with particular lesion patterns. In patients with cryptogenic stroke, MR-imaging pattern may be a valuable predictor for AF.

Methods

This is an MRI-based, retrospective, observational, comparative, single-center study of 104 patients who underwent ICM implantation after cryptogenic stroke. The findings were compared to a reference group with related stroke etiology, i.e., 166 patients with embolic stroke due to AF detected for the first time by long-term ECG. Lesion patterns were evaluated with regard to affected territories, distribution (cortical, lacunar, scattered), lesion volume, and lesion size (diameter of the lesion size > 20 mm).

Results

The MR-imaging analysis of acute ischemic lesions yielded no association between AF and lesion size or volume, arterial vessel distribution, or the number of affected territories. There was no significant difference between the cohorts regarding ischemic patterns (cortical lesions, scattered lesions, and lacunar infarcts). An important clinical inference of our findings is that 10% (2 of 20) of cases in the ICM group in whom AF was detected had a lacunar infarct pattern. Similar results were shown in cases of ischemic stroke patients with AF detected for the first time by long-term ECG, with 10.9% (16 of 147) of them showing lacunar infarcts. The analysis of chronic MRI lesions revealed no differences between the groups in the rate of chronic lesions, arterial vessel distribution, or the number of affected territories. Left atrial size (LA size) and the presence of atrial runs in long-term ECG were independently associated with AF.

Conclusions

In this MRI-based analysis of patients with cryptogenic stroke who had received ICM implantation, the detection rate of AF in patients with ICM was not related to the imaging pattern. In addition, the lacunar infarct pattern should not be an exclusion criterion for ICM insertion in patients with cryptogenic stroke. ICM insertion in patients with cryptogenic stroke should not be evaluated solely on the basis of reference to infarct patterns.

[Contribution of Holter ECG in the etiologic diagnosis of the ischemic stroke in Brazzaville, Congo]

Déterminer la prévalence des troubles rythmiques au cours des infarctus cérébraux et identifier les facteurs prédictifs de la fibrillation atriale (FA) paroxystique. Il s'est agi d'une étude transversale, descriptive et analytique, menée à Brazzaville entre janvier 2012 et décembre 2016. Elle a porté sur une série consécutive de 267 patients victimes d'un accident vasculaire cérébral ischémique transitoire (n = 17) ou constitué (n = 250), documenté par un scanner cérébral. Tous ces patients ont bénéficié d'un enregistrement Holter ECG dès 24h, réalisé dans le cadre de la recherche étiologique. Les principales anomalies rythmiques enregistrées ont été répertoriées et la régression logistique a permis l'identification des facteurs prédictifs de survenue de la FA paroxystique. Il s'agissait de 164 hommes (61,4%) et 103 femmes (38,6%), âgés en moyenne de 60,2 ± 12,1 ans (extrêmes: 22 et 94 ans). Les principaux facteurs de risque cardiovasculaire identifiés étaient une hypertension artérielle (HTA) dans 214 cas (80,1%), un diabète sucré dans 36 cas (13,5%), et un tabagisme dans 18 cas (6,7%), avec un taux de cumul de 1,5 facteur par individu. L'examen Holter ECG, normal dans 216 cas (81%), était pathologique dans 51 cas (19%). Les principales anomalies enregistrées consistaient en des extrasystoles ventriculaires bénignes (n = 32), une FA paroxystique (n = 7), des extrasystoles supraventriculaires (n = 5), une tachycardie ventriculaire (TV) non soutenue (n = 4), une TV soutenue (n = 2) et un bloc auriculo-ventriculaire type Mobitz II (n = 1). La fréquence de la FA paroxystique était de 2,6%. En analyse bivariée, il n'a pas été noté de corrélation entre la FA paroxystique et le sexe (p = 0,890), l'HTA (p = 0,818), le diabète (p = 0,839), le tabac (p = 0,969). En analyse multivariée, seul l'âge était prédictif de la survenue d'une FA paroxystique au cours des infarctus cérébraux (OR = 1,11;p = 0,0134). Il ressort de cette étude préliminaire que les troubles du rythme emboligènes sont relativement rares au cours des infarctus cérébraux à Brazzaville. La FA paroxystique, quoique peu fréquente, reste essentiellement corrélée à l'âge. Sa recherche systématique chez les sujets âgés contribue à améliorer la prise en charge.

Early prolonged ambulatory cardiac monitoring in stroke (EPACS): an open-label randomised controlled trial

Background

Cardioembolism in paroxysmal atrial fibrillation (PAF) is a preventable cause of transient ischaemic attack (TIA) or ischaemic stroke; however, due to its transient nature, a short-duration Holter monitor may miss a significant proportion of events.

Methods

We conducted an open-label randomised controlled trial of cardiac monitoring after a TIA or ischaemic stroke comparing a 14-day ECG monitoring patch (Zio^® Patch, iRhythm Technologies) with short-duration Holter monitoring for the detection of PAF. The primary outcome was the detection of one or more episodes of ECG-documented PAF lasting at least 30 s within 90 days in each of the study arms. A budget impact analysis from the healthcare perspective was performed.

Results

From February 2016 through February 2017, 43 (76.8%) of the 56 patients assigned to the patch-based monitoring group and 47 (78.3%) of the 60 patients assigned to short-duration Holter monitoring group had successful monitor placement with 90 days of follow-up. Of the 26 protocol failures between the two groups, 23 (88.5%) were due to patient refusal for outpatient short-duration ECG monitor placement, whilst only 1 (3.8%) was due unsuccessful ZioPatch placement. The rate of detection of PAF at 90 days was 16.3% in the patch-based monitoring group (seven patients) compared to 2.1% in the short-duration Holter monitoring group (1 patient), with an odds ratio of 8.9 (95% CI 1.1–76.0; P = 0.026). An economic model demonstrated that implementation of the Zio Patch service would result in 10.8 more strokes avoided per year compared to current practice with Holter monitoring with an associated yearly saving in direct medical costs of £113,630, increasing to £162,491 over 5 years.

Conclusions

Early, prolonged, patch-based monitoring after an index stroke or TIA is superior to short-duration Holter monitoring in the detection of PAF and likely cost-effective for preventing recurrent strokes.

Trial registrationhttp://www.isrctn.com. Unique identifier: ISRCTN 50253271. Registered 21 January 2016

Electronic supplementary material

The online version of this article (10.1186/s40001-019-0383-8) contains supplementary material, which is available to authorized users.

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.

Electrocardiomatrix Facilitates Accurate Detection of Atrial Fibrillation in Stroke Patients

Background and Purpose- Cardiac telemetry is a routine part of inpatient ischemic stroke/transient ischemic attack evaluation to assess for atrial fibrillation (AF). Yet, tools to assist stroke clinicians in the evaluation of the large quantities of telemetry data are limited. The investigators developed a new method to evaluate electrocardiographic signals, electrocardiomatrix, that was applied to stroke unit telemetry data to determine its feasibility, validity, and usefulness. Electrocardiomatrix displays telemetry data in a 3-dimensional matrix that allows for more accurate and less time consuming P-wave analysis. Methods- In this single-center, prospective, observational study conducted in a stroke unit, all telemetry data from ischemic stroke and transient ischemic attack patients were collected (April 2017-January 2018) for examination facilitated by electrocardiomatrix. AF>30 seconds was identified through review of electrocardiomatrix-generated matrices by a nonphysician researcher. Electrocardiomatrix results were compared with the clinical team's medical record documentation of AF identified through telemetry. A study cardiologist reviewed the standard telemetry associated with all AF episodes identified by electrocardiomatrix and each case of disagreement. Results- Telemetry data (median 46 hours [interquartile range: 22-90]) were analyzed among 265 unique subjects (88% ischemic stroke). Electrocardiomatrix was successfully applied in 260 (98%) of cases. The positive predictive value of electrocardiomatrix compared with the clinical documentation was 86% overall and 100% among the subset with no prior history of AF. For the 5 false-positive and 5 false-negative cases, expert overview disagreed with the clinical documentation and confirmed the electrocardiomatrix-based diagnosis. Conclusions- The application of electrocardiomatrix to stroke unit-acquired telemetry data is feasible and appears to have superior accuracy compared with traditional monitor analysis by noncardiologists.

Newer technologies for detection of atrial fibrillation

Atrial fibrillation is a common arrhythmia that is associated with increased risk of stroke, which can be reduced with appropriate anticoagulation treatment. However, it remains underdiagnosed in contemporary clinical practice using conventional detection methods, resulting in missed opportunities to implement appropriate treatment. Newer technologies developed in recent years can potentially enhance the detection of atrial fibrillation and overcome certain limitations of the conventional methods. However, uncertainties remain about their use and the significance of atrial fibrillation detected by some of these newer technologies. This review examines the evidence supporting the use of some of these technologies and evaluates their applications in certain clinical scenarios.

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.

Detection of Atrial Fibrillation in Cryptogenic Stroke

PURPOSE OF REVIEW

To summarize the literature on the detection of atrial fibrillation (AF) in patients with "cryptogenic" stroke, a cohort including about 25% of all ischemic stroke patients and patients with embolic stroke of undetermined source (ESUS).

RECENT FINDINGS

A first episode of AF is detected in up to one third of cryptogenic stroke and in up to one fourth of ESUS patients during long-term monitoring. AF prevalence correlates to patient selection, duration, and quality of ECG monitoring. Higher rates of AF were reported in stroke patients with left atrial pathology, specific ECG alterations, or increased natriuretic peptides. While AF detection impacts on medical stroke prevention in the vast majority of patients, patient selection for prolonged monitoring is largely left at the physician's discretion. AF detection after cryptogenic stroke or ESUS is a frequent, potentially causal condition. Whether subsequent oral anticoagulation may improve outcome remains open.

Risk of thromboembolism in patients developing critical illness-associated atrial fibrillation

Although common, the long-term significance of -developing atrial fibrillation (AF) during a period of critical illness is unclear. We undertook a retrospective cohort analysis to -assess the rate of thromboembolism (TE) in patients -developing atrial fibrillation de novo during admission to our intensive care unit. In total, 1,955 patients were followed up (-maximum follow-up 1,276 days) for the occurrence of TE, of which 220 (11.3%) had developed AF or atrial flutter during their critical care admission. There were 11 TE events among the patients with new AF (0.053 events per patient-year), compared with 18 in the non-AF group (0.0059 events per patient-year). The unadjusted hazard ratio for TE in patients developing new AF compared with those not developing AF was 8.09 (95% CI 3.08-17.19, p<0.001). In patients admitted to critical care, the development of AF appears to be associated with a significantly increased risk of subsequent thromboembolism.

Electrocardiographic RR Interval Dynamic Analysis to Identify Acute Stroke Patients at High Risk for Atrial Fibrillation Episodes During Stroke Unit Admission

Patients at short-term risk of paroxysmal atrial fibrillation (PAF) often exhibit increased RR interval variability during sinus rhythm. We studied if RR dynamic analysis, applied in the first hours after stroke unit (SU) admission, identified acute ischemic stroke patients at higher risk for subsequent PAF episodes detected within the SU hospitalization. Acute ischemic stroke patients underwent continuous cardiac monitoring (CCM) using standard bedside monitors immediately after SU admission. The CCM tracks from the first 48 h were analyzed using a telemedicine service (SRA clinic, Apoplex Medical, Germany). Based on the RR dynamics, the stroke risk analysis (SRA) algorithm stratified the risk for PAF as follows: low risk for PAF, high risk for PAF, presence of manifest AF. The subsequent presence/absence of PAF during the whole SU hospitalization was ruled out using all available CCMs, standard ECGs, or 24-h Holter ECGs. Two hundred patients (40% females, mean age 71 ± 16 years) were included. According to the initial SRA analysis, 111 patients (56%) were considered as low risk for PAF, 52 (26%) as high risk while 37 patients (18%) had manifest AF. A low-risk level SRA was associated with a reduced probability for subsequent PAF detection (1/111, 0.9%, 95% CI 0–4.3%) while a high-risk level SRA predicted an increased probability (20/52, 38.5% (95% CI 25–52%). RR dynamic analysis performed in the first hours after ischemic stroke may stratify patients into categories at low or high risk for forthcoming paroxysmal AF episodes detected within the SU hospitalization.

Expert opinion paper on atrial fibrillation detection after ischemic stroke

This expert opinion paper on atrial fibrillation detection after ischemic stroke includes a statement of the "Heart and Brain" consortium of the German Cardiac Society and the German Stroke Society. This paper was endorsed by the Stroke Unit-Commission of the German Stroke Society and the German Atrial Fibrillation NETwork. In patients with ischemic stroke, detection of atrial fibrillation should usually lead to a change in secondary stroke prevention, since oral anticoagulation is superior to antiplatelet drugs. The detection of previously undiagnosed atrial fibrillation can be improved in patients with ischemic stroke to optimize stroke prevention. This paper summarizes the present knowledge on atrial fibrillation detection after ischemic stroke. We propose an interdisciplinary standard for a "structured analysis of ECG monitoring" on the stroke unit as well as a staged diagnostic scheme for the detection of atrial fibrillation. Since the optimal duration and mode of ECG monitoring has not yet been finally established, this paper is intended to give advice to physicians who are involved in stroke care. In line with the nature of an expert opinion paper, labeling of classes of recommendations is not provided, since many statements are based on the expert opinion, reported case series and clinical experience. Therefore, this paper is not intended as a guideline.