Prolonged Cardiac Monitoring for Detection of Paroxysmal Atrial Fibrillation After Cerebral Ischemia

Ischemic Stroke at a Tertiary Academic Hospital in Tanzania: A Prospective Cohort Study With a Focus on Presumed Large Vessel Occlusion

Background

Large vessel ischemic strokes account for more than one-third of all strokes associated with substantial morbidity and mortality without early intervention. The incidence of large vessel occlusion (LVO) is not known in sub-Saharan Africa (SSA). Definitive vessel imaging is not routinely available in resource-limited settings.

Aims

We aimed to investigate the burden and outcomes of presumed LVO among patients with ischemic stroke admitted to a large tertiary academic hospital in Tanzania.

Methods

This cohort study recruited all consenting first-ever ischemic stroke participants admitted at a tertiary hospital in Tanzania. Demographic data were recorded, and participants were followed up to 1 year using the modified Rankin Scale (mRS). A diagnosis of presumed LVO was made by a diagnostic neuroradiologist and interventional neurologist based on contiguous ischemic changes in a pattern consistent with proximal LVO on a non-contrast computed tomography head. We examined factors associated with presumed LVO using logistic regression analysis. Inter-observer Kappa was calculated.

Results

We enrolled 158 first-ever ischemic strokes over 8 months with a mean age of 59.7 years. Presumed LVO accounted for 39.2% [95% confidence interval (CI) 31.6–47.3%] and an overall meantime from the onset of stroke symptoms to hospital arrival was 1.74 days. Participants with presumed LVO were more likely to involve the middle cerebral artery (MCA) territory (70.9%), p < 0.0001. Independent factors on multivariate analysis associated with presumed LVO were hypertension [adjusted odds ratio (aOR) 5.74 (95% CI: 1.74–18.9)] and increased waist-hip ratio [aOR 7.20 (95% CI: 1.83–28.2)]. One-year mortality in presumed LVO was 80% when compared with 73.1% in participants without presumed LVO. The Cohen's Kappa inter-observer reliability between the diagnostic neuroradiologist and interventional neurologist was 0.847.

Conclusion

There is a high burden of presumed LVO associated with high rates of 1-year morbidity and mortality at a tertiary academic hospital in Tanzania. Efforts are needed to confirm these findings with definitive vessel imaging, promoting cost-effective preventive strategies to reduce the burden of non-communicable diseases (NCDs), and a call for adopting endovascular therapies to reduce morbidity and mortality.

ESC Working Group on e-Cardiology Position Paper: accuracy and reliability of electrocardiogram monitoring in the detection of atrial fibrillation in cryptogenic stroke patients : In collaboration with the Council on Stroke, the European Heart Rhythm Association, and the Digital Health Committee

The role of subclinical atrial fibrillation as a cause of cryptogenic stroke is unambiguously established. Long-term electrocardiogram (ECG) monitoring remains the sole method for determining its presence following a negative initial workup. This position paper of the European Society of Cardiology Working Group on e-Cardiology first presents the definition, epidemiology, and clinical impact of cryptogenic ischaemic stroke, as well as its aetiopathogenic association with occult atrial fibrillation. Then, classification methods for ischaemic stroke will be discussed, along with their value in providing meaningful guidance for further diagnostic efforts, given disappointing findings of studies based on the embolic stroke of unknown significance construct. Patient selection criteria for long-term ECG monitoring, crucial for determining pre-test probability of subclinical atrial fibrillation, will also be discussed. Subsequently, the two major classes of long-term ECG monitoring tools (non-invasive and invasive) will be presented, with a discussion of each method's pitfalls and related algorithms to improve diagnostic yield and accuracy. Although novel mobile health (mHealth) devices, including smartphones and smartwatches, have dramatically increased atrial fibrillation detection post ischaemic stroke, the latest evidence appears to favour implantable cardiac monitors as the modality of choice; however, the answer to whether they should constitute the initial diagnostic choice for all cryptogenic stroke patients remains elusive. Finally, institutional and organizational issues, such as reimbursement, responsibility for patient management, data ownership, and handling will be briefly touched upon, despite the fact that guidance remains scarce and widespread clinical application and experience are the most likely sources for definite answers.

Detection of paroxysmal atrial fibrillation in 994 patients with a cerebrovascular event by intermittent 21-day ECG-monitoring and 7-day continuous Holter-recording

BACKGROUND

The detection of paroxysmal atrial fibrillation (AF) is of importance in stroke care. The method used is continuous electrocardiogram (ECG)-monitoring or multiple short ECG-recordings during an extended period. Their relative efficiency is a matter of discussion. In a retrospective cohort study on 994 patients with an ischemic stroke or transient ischemic attack (TIA), we have compared continuous 7-day monitoring to intermittent recording 60 sec three times daily with a handheld device during 3 weeks. We related the result to subsequent occurrence of AF as detected in 12-lead ECG recordings.

METHODS

The patients were identified in the local database of cardiovascular investigations. Their clinical profile and vital status during the follow-up were obtained from the Swedish Stroke Register and the Swedish general population registry. For comparison, we used an age- and sex-matched population with no known cerebrovascular event and a population with a cerebrovascular event that was not screened.

RESULTS

AF was detected in 7.1% by continuous screening and in 5.1% by intermittent screening (P = 0.3). During follow-up of 32 months, AF in 12-lead ECG was found in 7.0%. In the subgroup with positive screening, 46.3% had AF compared with 6.7% in the subgroup with negative screening (P < 0.0001).

CONCLUSIONS

The two screening approaches had a similar yield of arrhythmia, in spite of the group with intermittent monitoring having a more favorable clinical profile. A positive screening was highly predictive of AF in ECG during the follow-up.

Atrial Fibrillation Related and Unrelated Stroke Recurrence Among Ischemic Stroke Patients With Atrial Fibrillation

Background: Ischemic stroke with atrial fibrillation (AF) may recur despite appropriate treatment. It may be AF-related or AF-unrelated. We compared the factors associated with AF-related and AF-unrelated recurrences among ischemic stroke patients with AF. Methods: Patients with ischemic stroke and AF were enrolled from 11 centers in Korea. Ischemic stroke recurrence was classified as AF-related if the lesion pattern was compatible with cardioembolism without significant stenosis or as AF-unrelated if the lesion was more likely due to small vessel disease or arterial stenosis. Factors associated with stroke recurrence (AF-related and AF-unrelated) were investigated. Results: Among the 2,239 patients, 115 (5.1%) experienced recurrence (75 AF-related and 40 AF-unrelated). Factors independently associated with any stroke recurrence included AF diagnosed before stroke, small subcortical infarctions, and small scattered lesions in a single vascular territory. Type of AF was associated with the type of stroke recurrence, with persistent AF being associated with AF-related stroke [hazard ratio (HR) = 2.94, 95% confidence interval (CI) 1.69-5.26; p < 0.001]. By contrast, paroxysmal AF (HR = 3.76, 95% CI 1.56-9.04; p = 0.003), AF diagnosed before stroke (HR = 2.38, 95% CI 1.19-4.55; p = 0.014), small scattered lesions in a single vascular territory (reference: corticosubcortical lesion, HR = 3.19, 95% CI 1.18-8.63; p = 0.022), and the use of antiplatelet agents (HR = 2.11, 95% CI 1.11-4.03; p = 0.024) were independently associated with AF-unrelated stroke. Conclusion: Persistent AF was more associated with AF-related stroke recurrence, whereas paroxysmal AF was more associated with AF-unrelated stroke recurrence. A scattered lesion in a single vascular territory may predict AF-unrelated stroke recurrence.

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

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

Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source

OBJECTIVES

Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized AF. We pursued this study to determine if the AI-ECG model differentiates between patients with ESUS and those with known causes of stroke, and to evaluate whether the AF prediction by AI-ECG among patients with ESUS was associated with the results of prolonged ambulatory cardiac rhythm monitoring.

MATERIALS AND METHODS

We reviewed consecutive patients admitted with acute ischemic stroke to a comprehensive stroke center between January 2018 and August 2019 and employed the TOAST classification to categorize the mechanisms of ischemia. Use and results of ambulatory cardiac rhythm monitoring after discharge were gathered. We ran the AI-ECG model to obtain AF probabilities from all ECGs acquired during the hospitalization and compared those probabilities in patients with ESUS versus those with known stroke causes (apart from AF), and between patients with and without AF detected by ambulatory cardiac rhythm monitoring.

RESULTS

The study cohort had 930 patients, including 263 patients (28.3%) with known AF or AF diagnosed during the index hospitalization and 265 cases (28.5%) categorized as ESUS. Ambulatory cardiac rhythm monitoring was performed in 226 (85.3%) patients with ESUS. AF probability by AI-ECG was not associated with ESUS. However, among patients with ESUS, the probability of AF by AI-ECG was associated with a higher likelihood of AF detection by ambulatory monitoring (P = 0.004). A probability of AF by AI-ECG greater than 0.20 was associated with AF detection by ambulatory cardiac rhythm monitoring with an OR of 5.47 (95% CI 1.51-22.51).

CONCLUSIONS

AI-ECG may help guide the use of prolonged ambulatory cardiac rhythm monitoring in patients with ESUS to identify those who might benefit from anticoagulation.

Second look Holter ECG in neurorehabilitation

Background

Many stroke survivors suffer recurrent stroke because paroxysmal atrial fibrillation (AF) was missed and no preventive anticoagulation initiated. This prospective cohort study determined the added diagnostic yield of second-look 24-h electrocardiographic recording (ECG) in a population at high risk for AF: patients who suffered a stroke of such severity that they require inpatient neurorehabilitation.

Methods

We enrolled 508 patients with ischemic stroke admitted to post-acute inpatient neurorehabilitation and determined whether AF was detected during acute care at the referring hospital. Second-look baseline and 24-h Holter ECG were then conducted during neurorehabilitation. Primary outcome was number of newly detected AF with duration of > 30 s; secondary outcomes were number of newly detected absolute arrhythmia of 10–30 s and < 10 s duration. For comparison, we further enrolled 100 patients with hemorrhagic stroke without history of AF (age = 72 + 11 years, 51% female).

Results

In 206 of the 508 ischemic stroke patients, AF had been detected during acute phase work-up (age = 78 + 10 years, 55% female). For the remaining 302 ischemic stroke patients, no AF was detected during acute phase work-up (age = 74 + 9 years; 47% female). Second-look 24-h ECG showed previously missed AF of > 30 s in 20 of these patients, i.e. 6.6% of the sample, and shorter absolute arrhythmia in 50 patients (i.e. 16.5%).

Conclusions

Second-look 24-Hour ECG performed during post-acute inpatient neurorehabilitation has a high diagnostic yield and should become a standard component of recurrent stroke prevention.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Brain Natriuretic Peptide and Discovery of Atrial Fibrillation After Stroke

Background and Purpose—

Diagnosing paroxysmal atrial fibrillation (pAF) can be challenging after acute ischemic stroke. Enhanced and prolonged Holter-ECG monitoring (EPM) improves the detection rate but is not feasible for all patients. We hypothesized that brain natriuretic peptide (BNP) may help to identify patients with stroke at high risk for pAF to select patients for EPM more effectively.

Methods—

Patients with acute cerebral ischemia ≥60 years presenting in sinus rhythm and without history of AF were included into a prospective, randomized multicenter study to receive either EPM (3× 10-day Holter-ECG) or usual stroke care diagnostic work-up. BNP plasma levels were measured on randomization and 3 months thereafter. Levels were compared between patients with and without pAF detected by means of EPM or usual care. Furthermore, the number needed to screen for EPM depending on BNP cut offs was calculated.

Results—

A total of 398 patients were analyzed. In 373 patients (93.7%), BNP was measured at baseline and in 275 patients (69.1%) after 3 months. pAF was found in 27 patients by means of EPM and in 9 patients by means of usual care ( P =0.002). Median BNP was higher in patients with pAF as compared to patients without AF in both study arms at baseline (57.8 versus 28.3 pg/mL in the EPM arm, P =0.0003; 46.2 versus 27.7 pg/mL, P =0.28 in the control arm) and after 3 months (74.9 versus 31.3 pg/mL, P =0.012 in the EPM arm, 99.3 versus 26.3 pg/mL, P =0.02 in the control arm). Applying a cut off of 100 pg/mL, the number needed to screen was reduced from 18 by usual care to 3 by EPM.

Conclusions—

BNP measured early after ischemic stroke identifies a subgroup of patients with stroke at increased risk for AF, in whom EPM is particularly efficacious.

Registration—

URL: https://www.clinicaltrials.gov . Unique identifier: NCT01855035.

An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction

BACKGROUND

Atrial fibrillation is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing screening methods require prolonged monitoring and are limited by cost and low yield. We aimed to develop a rapid, inexpensive, point-of-care means of identifying patients with atrial fibrillation using machine learning.

METHODS

We developed an artificial intelligence (AI)-enabled electrocardiograph (ECG) using a convolutional neural network to detect the electrocardiographic signature of atrial fibrillation present during normal sinus rhythm using standard 10-second, 12-lead ECGs. We included all patients aged 18 years or older with at least one digital, normal sinus rhythm, standard 10-second, 12-lead ECG acquired in the supine position at the Mayo Clinic ECG laboratory between Dec 31, 1993, and July 21, 2017, with rhythm labels validated by trained personnel under cardiologist supervision. We classified patients with at least one ECG with a rhythm of atrial fibrillation or atrial flutter as positive for atrial fibrillation. We allocated ECGs to the training, internal validation, and testing datasets in a 7:1:2 ratio. We calculated the area under the curve (AUC) of the receiver operatoring characteristic curve for the internal validation dataset to select a probability threshold, which we applied to the testing dataset. We evaluated model performance on the testing dataset by calculating the AUC and the accuracy, sensitivity, specificity, and F1 score with two-sided 95% CIs.

FINDINGS

We included 180 922 patients with 649 931 normal sinus rhythm ECGs for analysis: 454 789 ECGs recorded from 126 526 patients in the training dataset, 64 340 ECGs from 18 116 patients in the internal validation dataset, and 130 802 ECGs from 36 280 patients in the testing dataset. 3051 (8·4%) patients in the testing dataset had verified atrial fibrillation before the normal sinus rhythm ECG tested by the model. A single AI-enabled ECG identified atrial fibrillation with an AUC of 0·87 (95% CI 0·86-0·88), sensitivity of 79·0% (77·5-80·4), specificity of 79·5% (79·0-79·9), F1 score of 39·2% (38·1-40·3), and overall accuracy of 79·4% (79·0-79·9). Including all ECGs acquired during the first month of each patient's window of interest (ie, the study start date or 31 days before the first recorded atrial fibrillation ECG) increased the AUC to 0·90 (0·90-0·91), sensitivity to 82·3% (80·9-83·6), specificity to 83·4% (83·0-83·8), F1 score to 45·4% (44·2-46·5), and overall accuracy to 83·3% (83·0-83·7).

INTERPRETATION

An AI-enabled ECG acquired during normal sinus rhythm permits identification at point of care of individuals with atrial fibrillation.

FUNDING

None.

Paroxysmal atrial fibrillation detection in patients with acute ischemic stroke through prolonged Holter: prospective study

INTRODUCTION

The detection of paroxysmal atrial fibrillation (PAF) is crucial in the etiological study of an acute ischemic stroke (AIS), although this type of arrhythmia is often under-diagnosed. This prospective study aims to (1) evaluate the new-onset PAF detection rate among elderly patients with AIS in an acute setting, and (2) to assess the applicability of the STAF score (Score for the Targeting of Atrial Fibrillation) for such patients.

METHODOLOGY

An observational and prospective study was performed over a period of 11 months. Patients with acute ischemic stroke who had been admitted to the stroke unit were included. Exclusion criteria included prior AF, AF readings on ECG during admission, or stroke mimic. The patients were monitored with a bedside ECG monitor throughout the first 48 h, then simultaneously with an extended Holter recorder for a maximum of 6 days. The occurrence and duration of PAF events was evaluated. The STAF risk score for PAF was calculated and compared to the detection rate of PAF for each patient.

RESULTS

The sample population consisted of 67 patients, whose median age was 76 years (IQR 71-84) and who were 57% males. The median duration of Holter recording was 3.5 days per patient (IQR 2-5). We detected new PAF cases in 16% of patients, and a total of 31% had supraventricular arrhythmia episodes lasting 10 s or longer. Among the patients in which this arrhythmia was detected, 10% had it detected by the bedside ECG monitor in the first 48 h. The median risk score was 5 (IQR 4-6). There was no association between the risk score used and PAF.

CONCLUSION

In elderly patients with AIS, the use of an extended Holter recorder led to the detection of more cases of PAF, offering them the chance to initiate hypocoagulant therapy. Among this population, the STAF score was non-discriminative and did not prove useful in predicting PAF.

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

Background

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

Objectives

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

Design

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

Setting

Primary care.

Participants

Adults.

Intervention

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

Main outcome measures

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

Review methods

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

Results

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

Conclusions

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

Limitations

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

Future work

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

Study registration

This study is registered as PROSPERO CRD42014013739.

Funding

The National Institute for Health Research Health Technology Assessment programme.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

TRIAL REGISTRATION

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

Atrial fibrillation, cognitive impairment, and neuroimaging

INTRODUCTION

The objective of our study was to investigate cross-sectional associations of atrial fibrillation with neuroimaging measures of cerebrovascular disease and Alzheimer's disease and their interactions with mild cognitive impairment (MCI).

METHODS

Magnetic resonance imaging scans of individuals from a population-based study were analyzed for infarctions, total gray matter, and hippocampal and white matter hyperintensity volumes. A subsample underwent positron emission tomography imaging.

RESULTS

Atrial fibrillation was associated with infarctions and lower total gray matter volume. Compared with subjects with no atrial fibrillation and no infarction, the odds ratio (95% confidence intervals) for MCI was 2.99 (1.57-5.70; P = .001) among participants with atrial fibrillation and infarction, 0.90 (0.45-1.80; P = .77) for atrial fibrillation and no infarction, and 1.50 (0.96-2.34; P = .08) for no atrial fibrillation and any infarction.

DISCUSSION

Participants with both atrial fibrillation and infarction are more likely to have MCI than participants with either infarction or atrial fibrillation alone.

Graphics-processor-unit-based parallelization of optimized baseline wander filtering algorithms for long-term electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here, we present a graphics processor unit (GPU)-based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to autoregressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and four times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a seven-day high-resolution ECG is computed within less than 3 s. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Cryptogenic stroke

In about a quarter of ischaemic strokes the cause is undetermined, because the investigation is incomplete or delayed, because there are multiple causes or because the stroke is truly cryptogenic. Cryptogenic stroke can be further classified as non-embolic or embolic. Embolic stroke of undetermined source can be due to paroxysmal atrial fibrillation, minor emboligenic cardiac conditions, atheroembolism, cancer associated and paradoxical embolism through a patent foramen ovale (PFO) or less often a pulmonary fistula. Currently, risk factor control, statins and antiplatelets are the main therapeutic measures to prevent recurrent stroke. There is no evidence to implement routine closure of PFO in patients with cryptogenic stroke. Direct anticoagulants are being evaluated in randomized controlled trials including embolic stroke of undetermined source patients. Advances in high resolution ultrasound or magnetic resonance imaging of extracranial and intracranial vessels and of the heart and prolonged heart rhythm monitoring will be instrumental techniques to identify arterial and cardiac hidden causes of stroke.

Cryptogenic Stroke And Role Of Loop Recorder

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

Atrial fibrillation and stroke - Coexistence and attitude to preventive therapy on the basis of Szczecin and Szczecin region patients

Atrial fibrillation (AF) is an independent factor increasing the risk of an ischemic stroke (IS) fivefold. The objective of the study was to evaluate the frequency of coexistence of non-valvular AF and IS during the acute stroke and to analyze the attitude of AF patients to treatment. The study included 3712 successive patients presenting either an IS or a transient ischemic attack. The analysis revealed a significant increase in the rate of patients with AF and IS in the years 2010-2013 (31.9%) compared with 2002-2005 (20.2%). A rise in the proportion of AF and IS patients was recorded over the course of consecutive years in group II. The proportion of newly detected AF cases during hospital stay differed significantly between the groups (16.9% vs. 31.9%). Group I and II patients differed essentially with regards to hypertension incidence and female rates. Antiplatelet medications or OACs were taken by a significantly greater number of AF patients in group II. Low number of therapeutic levels of INR was recorded in both groups. IS and AF coexist more frequently than indicated by previous assessments and demographic data from other countries. Increase in the number of IS and AF patients may result from higher detectability of AF and older age of patients affected with stroke, women in particular. Despite a well grounded knowledge about the benefits of OACs use in the prophylaxis of thrombotic-embolic events in AF patients, they are rarely used. A surprisingly low proportion of patients taking OACs reaches a therapeutic INR level.