Bayés syndrome and acute cardioembolic ischemic stroke

Trajectory Groups of 72-Hour Heart Rate After Mechanical Thrombectomy and Outcomes

Background and Purpose

Elevated heart rate (HR) after mechanical thrombectomy (MT) was associated with an increased risk of adverse outcomes. However, optimal HR management after MT remains unclear. This study aimed to identify patient subgroups with distinct HR trajectories after MT and explore their association with outcomes.

Methods

Acute ischemic stroke patients undergoing MT therapy were prospectively recruited from July 2020 to December 2022. Their heart rate indicators were collected every hour for 72 hours after MT procedure. Latent variable mixture modeling was used to separate subjects into five groups with distinct HR trajectories. The primary outcome was poor functional outcome (mRS score >2) at 3 months. Additional outcome was all-cause mortality (mRS score = 6) at 3 months.

Results

A total of 224 patients with large vessel occlusion were enrolled, with a mean age of 65.2+14.0 years. Eighty-seven patients had a good functional outcome, and 137 patients had a poor functional outcome. Five distinct HR trajectories were observed: low (19.2%), moderate (33.0%), rapidly stabilized HR group (20.5%), persistently high HR group (21.0%), and very high HR group (6.3%). After adjusting for potential confounders, the HR trajectory group was independently associated with poor functional outcome at 3 months (P for interaction = 0.022). The risk of having poor functional outcome was increased in the rapidly stabilized HR group (odds ratio, 3.18 [95% confidence interval, 1.10-9.19]), the persistently high HR group (odds ratio, 5.55 [95% confidence interval, 1.72-17.87]) and very high HR group (odds ratio, 18.32 [95% confidence interval, 2.20-95.52]) but not in the moderate group (odds ratio, 1.50 [95% confidence interval, 0.61-3.69]), when compared with the low HR group. No significant association was found between trajectory group and 3-month all-cause mortality.

Conclusion

HR during the first 72 hours after MT may be categorized into distinct trajectory groups, which differ in relation to poor functional outcome event risks. The findings may help to recognize potential candidates for future HR control trials.

Future Perspectives to Improve CHA2DS2VASc Score: The Role of Left Atrium Remodelling, Inflammation and Genetics in Anticoagulation of Atrial Fibrillation

In 10% of ischemic strokes, non-valvular atrial fibrillation (NVAF) is detected retroactively. Milder, or even asymptomatic forms of NVAF have shown high mortality, thrombotic risk, and deterioration of cognitive function. The current guidelines for the diagnosis and treatment of AF contain "grey areas", such as the one related to anticoagulant treatment in men with CHA2DS2-VASc score 1 and women with score 2. Moreover, parameters such as renal function, patient weight or left atrium remodelling are missing from the recommended guidelines scores. Vulnerable categories of patients including the elderly population, high hemorrhagic risk patients or patients with newly diagnosed paroxysmal episodes of atrial high rate at device interrogation are at risk of underestimation of the thrombotic risk. This review presents a systematic exposure of the most important gaps in evaluation of thrombotic and hemorrhagic risk in patients with NVAF. The authors propose new algorithms and risk factors that should be taken into consideration for an accurate thrombotic and hemorrhagic risk estimation, especially in vulnerable categories of patients.

Tricuspid regurgitation: a hidden risk factor for atrial fibrillation related stroke?

Background and purpose

Tricuspid regurgitation (TR) is a common but overlooked valvular disease, and its association with the etiologic subtypes of ischemic stroke is unclear. We explored the relationship between TR and atrial fibrillation (AF) in patients with acute ischemic stroke.

Methods

This retrospective analysis of ongoing stroke registry assessed 6,886 consecutive acute ischemic stroke patients who underwent transthoracic echocardiography during their in-hospital care. Multivariable logistic regression models adjusted for age, sex, stroke characteristics, and echocardiographic indices were used to investigate the association between TR and total AF, and newly diagnosed AF during hospitalization and a 1-year follow-up period, respectively.

Results

TR was present in 877 (12.7%) patients (mild, 9.9%; moderate, 2.4%; severe, 0.5%). AF was identified in 24.1% (medical history, 11.1%; first detected in the emergency room, 6.6%; newly diagnosed after admission, 6.4%). TR was associated with AF [adjusted odds ratio (aOR) 4.87 (95% confidence interval (CI), 2.63-9.03)], compared with no/trivial TR. The association between TR and AF was consistent regardless of severity (aOR [95% CI], 4.57 [2.63-7.94] for mild and 7.05 [2.57-19.31] for moderate-to-severe TR) or subtype of TR (5.44 [2.91-10.14] for isolated and 3.81 [2.00-7.28] for non-isolated TR). Among the AF-naïve patients at admission, TR was associated with newly diagnosed AF during hospitalization and a 1-year follow-up period (aOR [95% CI], 2.68 [1.81-3.97]).

Conclusions

TR is associated with AF in acute ischemic stroke patients regardless of severity and subtypes of TR. TR is also associated with newly diagnosed AF after stroke.

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

INTRODUCTION

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

OBJECTIVE

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A Simplified Risk Score to Predict In-Hospital Newly-Diagnosed Atrial Fibrillation in Acute Ischemic Stroke Patients

Purpose

Atrial fibrillation (AF) is a significant cause of stroke, and newly diagnosed AF (NDAF) is typically detected in the early period of stroke onset. We aimed to identify the factors associated with in-hospital NDAF in acute ischemic stroke patients and developed a simplified clinical prediction model.

Methods

Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients.

Results

The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity.

Conclusion

The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.

Excessive Supraventricular Ectopic Activity and the Risk of Atrial Fibrillation and Stroke: A Systematic Review and Meta-Analysis

BACKGROUND

Excessive supraventricular ectopic activity (ESVEA) is correlated with the development of atrial fibrillation (AF) and is frequently observed in ischemic stroke patients. This meta-analysis aims to summarize the evidence on the association between ESVEA and the risk of AF and stroke.

METHODS

PubMed and Embase databases were systematically searched to identify all publications providing relevant data from inception to 23 August 2022. Hazard ratio (HR) and 95% confidence interval (CI) were pooled using fixed-effect or random-effect models.

RESULTS

We included 23,272 participants from 20 studies. Pooled results showed that ESVEA was associated with an increased risk of AF in the general population (HR: 2.57; 95% CI 2.16-3.05), increased risk of AF in ischemic stroke patients (HR: 2.91; 95% CI 1.80-4.69), new-onset ischemic stroke (HR: 1.91; 95% CI 1.30-2.79), and all-cause mortality (HR: 1.41; 95% CI 1.24-1.59). Pooled analysis indicated that ESVEA was not associated with recurrent ischemic stroke/transient ischemic attack (TIA) (HR: 1.24; 95% CI 0.91-1.67).

CONCLUSIONS

ESVEA is associated with AF, new-onset ischemic stroke, and all-cause mortality.

Advanced interatrial block predicts recurrence of embolic stroke of undetermined source

BACKGROUND

Advanced interatrial block (IAB) is an independent risk factor for ischaemic stroke. This study aimed to analyse whether advanced IAB predicts recurrence of embolic stroke of undetermined source (ESUS).

METHODS

104 patients with a confirmed diagnosis of ESUS were followed up for a median period of 15 months (interquartile range, 10-48). We recorded data on clinical variables, P-wave characteristics, and presence of IAB on the electrocardiogram. Electrocardiogram findings were interpreted by a blinded, centralised rater at (XXXX2). ESUS recurrence was the primary outcome variable.

RESULTS

Median age was 47 years (range, 19-85); 50% of patients were women. IAB was detected in 36 patients (34.6%); IAB was partial in 29 cases (27.9%) and advanced in 7 (6.7%). Sixteen patients (15.4%) presented stroke recurrence; of these, 5 had partial and 4 had advanced IAB (P = .01; odds ratio [OR] = 9.44; 95% confidence interval [CI], 1.88-47.46; relative risk [RR] = 4.62; 95% CI, 2.01-10.61). Median P-wave duration was longer in patients with stroke recurrence (P = .009). The multivariate logistic regression analysis identified the following independent risk factors for stroke recurrence: advanced IAB (P < .001; OR = 10.86; 95% CI, 3.07-38.46), male sex (P = .028; OR = 4.6; 95% CI, 1.18-17.96), and age older than 50 years (P = .039; OR = 3.84; 95% CI, 1.06-13.88). In the Cox proportional hazards model, the risk variables identified were age older than 50 years (P = .002; hazard ratio, 7.04; 95% CI, 2.06-23.8) and P-wave duration (per ms) (P = .007; hazard ratio, 1.02; 95% CI, 1.01-1.04).

CONCLUSIONS

Advanced IAB and age older than 50 years predict ESUS recurrence.

Artificial Intelligence-Enabled ECG: Physiologic and Pathophysiologic Insights and Implications

Advancements in machine learning and computing methods have given new life and great excitement to one of the most essential diagnostic tools to date-the electrocardiogram (ECG). The application of artificial intelligence-enabled ECG (AI-ECG) has resulted in the ability to identify electrocardiographic signatures of conventional and unique variables and pathologies, giving way to tremendous clinical potential. However, what these AI-ECG models are detecting that the human eye is missing remains unclear. In this article, we highlight some of the recent developments in the field and their potential clinical implications, while also attempting to shed light on the physiologic and pathophysiologic features that enable these models to have such high diagnostic yield. © 2022 American Physiological Society. Compr Physiol 12:3417-3424, 2022.

Embolic stroke of undetermined source: beyond atrial fibrillation

INTRODUCTION

Embolic stroke of undetermined source (ESUS) accounts for 25% of all cerebral infarcts; only 30% are associated with paroxysmal atrial fibrillation (AF). Various biochemical, electrocardiographic, and echocardiographic findings may suggest left atrial damage and increased risk of embolism in the absence of clinically documented AF or atrial flutter. In this review, we analyse the available evidence on atrial cardiopathy or atrial disease, its involvement in ESUS, and its identification through electrocardiographic, echocardiographic, and serum markers and its possible therapeutic implications.

DEVELOPMENT

A systematic search was conducted on MEDLINE (PubMed) using the following MeSH terms: MeSH [ESUS]+[atrial cardiopathy]+[atrial fibrillation]+[interatrial block]+[treatment]. We selected what we considered to be the most useful original prospective or retrospective studies and systematic reviews. We then read the full texts of the articles and checked the references cited in each article. We analyse epidemiological and demographic variables of patients with ESUS, as well as recent evidence related to presentation and prognosis and factors associated with recurrence and mortality. We review the contribution of atrial cardiopathy diagnosis prior to the detection of AF and the clinical, electrocardiographic, and echocardiographic variables and the biochemical markers associated with its development and its potential contribution to cerebral embolism.

CONCLUSIONS

The systematic search of biochemical and electrocardiographic, and echocardiographic alterations can be useful to identify ESUS patients at higher risk of recurrence.

Embolic stroke of undetermined source: Beyond atrial fibrillation

INTRODUCTION

Embolic stroke of undetermined source (ESUS) accounts for 25% of all cerebral infarcts; only 30% are associated with paroxysmal atrial fibrillation (AF). Various biochemical, electrocardiographic, and echocardiographic findings may suggest left atrial damage and increased risk of embolism in the absence of clinically documented AF or atrial flutter. In this review, we analyse the available evidence on atrial cardiopathy or atrial disease, its involvement in ESUS, and its identification through electrocardiographic, echocardiographic, and serum markers and its possible therapeutic implications.

DEVELOPMENT

A systematic search was conducted on MEDLINE (PubMed) using the following MeSH terms: MeSH [ESUS]+[atrial cardiopathy]+[atrial fibrillation]+[interatrial block]+[treatment]. We selected what we considered to be the most useful original prospective or retrospective studies and systematic reviews. We then read the full texts of the articles and checked the references cited in each article. We analyse epidemiological and demographic variables of patients with ESUS, as well as recent evidence related to presentation and prognosis and factors associated with recurrence and mortality. We review the contribution of atrial cardiopathy diagnosis prior to the detection of AF and the clinical, electrocardiographic, and echocardiographic variables and the biochemical markers associated with its development and its potential contribution to cerebral embolism.

CONCLUSIONS

The systematic search of biochemical and electrocardiographic, and echocardiographic alterations can be useful to identify ESUS patients at higher risk of recurrence.

Artificial Intelligence and Atrial Fibrillation

In the context of atrial fibrillation (AF), traditional clinical practices have thus far fallen short in several domains such as identifying patients at risk of incident AF or patients with concomitant undetected paroxysmal AF. Novel approaches leveraging artificial intelligence have the potential to provide new tools to deal with some of these old problems. In this review we focus on the roles of artificial intelligence-enabled ECG pertaining to AF, potential roles of deep learning (DL) models in the context of current knowledge gaps, as well as limitations of these models. One key area where DL models can translate to better patient outcomes is through automated ECG interpretation. Further, we overview some of the challenges facing AF screening and the harms and benefits of screening. In this context, a unique model was developed to detect underlying hidden AF from sinus rhythm and is discussed in detail with its potential uses. Knowledge gaps also remain regarding the best ways to monitor patients with embolic stroke of undetermined source (ESUS) and who would benefit most from oral anticoagulation. The AI-enabled AF model is one potential way to tackle this complex problem as it could be used to identify a subset of high-risk ESUS patients likely to benefit from empirical oral anticoagulation. Role of DL models assessing AF burden from long duration ECG data is also discussed as a way of guiding management. There is a trend towards the use of consumer-grade wristbands and watches to detect AF from photoplethysmography data. However, ECG currently remains the gold standard to detect arrythmias including AF. Lastly, role of adequate external validation of the models and clinical trials to study true performance is discussed. This article is protected by copyright. All rights reserved.

Left Atrial Strain Helps Identifying the Cardioembolic Risk in Transient Ischemic Attacks Patients with Silent Paroxysmal Atrial Fibrillation

Purpose

Patients with transient ischemic attacks often present asymptomatic and paroxysmal atrial fibrillation. Since atrial fibrillation initiates in the atria, we aimed to identify whether the abnormalities in left atrial structure and function could identify the cardioembolic etiology of the transient ischemic attacks in patients at sinus rhythm.

Patients and Methods

A total of 190 patients over 50 years old with sinus rhythm discharged after a transient ischemic attack were included in the study and divided into two groups according to the presence (group I) or absence (group II) of documented paroxysmal atrial fibrillation. The documentation of paroxysmal atrial fibrillation was based on the examination of medical registers. Cardiac ultrasound assessment was performed at a minimum of 14 days after the onset of the transient ischemic attack, to avoid assessment of atrial stunning.

Results

The group I patients were older, more frequent women, with a history of stroke or transient ischemic attack and a higher CHA2DS2-VASc score. They also presented larger left atrial volumes, lower left atrial emptying fraction, and significantly impaired left atrial deformation patterns. Multivariate logistic regression identified three variables that were independently associated with paroxysmal atrial fibrillation: age, left atrial reservoir strain, and left atrial emptying fraction (P < 0.0001). The cut-off levels for the variables were age > 55 years, reservoir strain < −17%, and emptying fraction < 51%.

Conclusion

The present study demonstrates that the LA strain is independently associated with paroxysmal atrial fibrillation in transient ischemic attack patients and might be of great help in identifying their cardioembolic etiology and preventing subsequent strokes by the initiation of anticoagulant therapy.

Advanced interatrial block predicts recurrence of embolic stroke of undetermined source

BACKGROUND

Advanced interatrial block (IAB) is an independent risk factor for ischaemic stroke. This study aimed to analyse whether advanced IAB predicts recurrence of embolic stroke of undetermined source (ESUS).

METHODS

104 patients with a confirmed diagnosis of ESUS were followed up for a median period of 15 months (interquartile range, 10-48). We recorded data on clinical variables, P-wave characteristics, and presence of IAB on the electrocardiogram (ECG). ECG findings were interpreted by a blinded, centralised rater at (XXXX2). ESUS recurrence was the primary outcome variable.

RESULTS

Median age was 47 years (range, 19-85); 50% of patients were women. IAB was detected in 36 patients (34.6%); IAB was partial in 29 cases (27.9%) and advanced in 7 (6.7%). Sixteen patients (15.4%) presented stroke recurrence; of these, 5 had partial and 4 had advanced IAB (P = .01; odds ratio [OR] = 9.44; 95% confidence interval [CI], 1.88-47.46; relative risk [RR] = 4.62; 95% CI, 2.01-10.61). Median P-wave duration was longer in patients with stroke recurrence (P = .009). The multivariate logistic regression analysis identified the following independent risk factors for stroke recurrence: advanced IAB (P < .001; OR = 10.86; 95% CI, 3.07-38.46), male sex (P = .028; OR = 4.6; 95% CI, 1.18-17.96), and age older than 50 years (P = .039; OR = 3.84; 95% CI, 1.06-13.88). In the Cox proportional hazards model, the risk variables identified were age older than 50 years (P = .002; hazard ratio, 7.04; 95% CI, 2.06-23.8) and P-wave duration (per ms) (P = .007; hazard ratio, 1.02; 95% CI, 1.01-1.04).

CONCLUSIONS

Advanced IAB and age older than 50 years predict ESUS recurrence.

What every clinician should know about Bayés syndrome

Bayés syndrome is a new clinical entity, characterized by the association of advanced interatrial block (IAB) on surface electrocardiogram with atrial fibrillation (AF) and other atrial arrhythmias. This syndrome is associated with an increased risk of stroke, dementia, and mortality. Advanced IAB is diagnosed by the presence of a P-wave ≥ 120ms with biphasic morphology (±) in inferior leads. The cause of IAB is complete Bachmann bundle blockade, leading to retrograde depolarization of the left atrium from areas near the atrioventricular junction. The anatomic substrate of advanced IAB is fibrotic atrial cardiomyopathy. Dyssynchrony induced by advanced IAB is a trigger and maintenance mechanism of AF. This alteration of the atrial architecture produces atrial remodeling, blood stasis and hypercoagulability, triggering the thrombogenic cascade. The presence of advanced IAB, even in patients without documented atrial arrhythmias, has also been associated with AF, stroke, dementia, and mortality. However, in these patients, there is no evidence to support the use of anticoagulation. Therefore, in patients with advanced IAB, a proactive search for AF is recommended.

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.

Prevalence and Significance of Interatrial Block in Takotsubo Syndrome (from the RETAKO Registry)

Interatrial block (IAB) represents a conduction delay between right and left atria and is associated with an increased risk of atrial fibrillation and stroke. IAB has not been previously assessed in patients with Takotsubo syndrome (TS). Our aim was to describe the prevalence and prognostic significance of IAB in patients with TS. Data come from the Spanish National prospective registry of patients with definitive TS diagnosis. IAB was defined as a P-wave ≥120 ms and was considered partial when the P-wave was positive in inferior leads and advanced when it was biphasic (+/-). A total of 246 patients were included, normal P-wave was found in 151 (61%), partial IAB in 58 (24%), atrial fibrillation in 18 (7%), advanced IAB in 13 (5%), and 6 (2%) were pacemaker dependent. During a mean follow up of 12 months the composite of all-cause mortality and hospital readmission was significantly higher in patients with advanced IAB (31%) or atrial fibrillation (33%) than in the rest of the cohort (pacemaker stimulation 17%, normal P-wave 13%, partial IAB 12%), p < 0.01. The data regarding P wave characteristics were an independent predictor of the composite end point all-cause death and hospital readmission. IAB has a high prevalence in patients with TS. Advanced IAB and atrial fibrillation are associated with a poor prognosis.

Second-degree interatrial block: A case series

Advanced interatrial block (IAB) (P-wave ≥120 ms and biphasic P-wave in leads II, III and aVF) is a prevalent ECG pattern frequently associated with supraventricular arrhythmias and stroke, especially in patients with structural heart disease. Intermittent IAB is a much more poorly defined electrocardiographic entity with uncertain clinical significance. In this case series, we review and analyze eight cases of second degree intermittent IAB. In six cases, there is normalization of advanced IAB after a premature supraventricular or ventricular contraction, suggesting a functional block that temporarily recovers post extra-systolic pause. Recognition of intermittent IAB (second degree) may help further characterize the prognostic and clinical implications of this ECG pattern.

Update on Bayés' syndrome: the association between an interatrial block and supraventricular arrhythmias

INTRODUCTION

The past few years have given rise to extensive research on an interatrial block and its clinical relevance, mainly its association with supraventricular arrhythmias. In 2015, the authors of this article reviewed the Bayes syndrome for the first time and after three years there has been so much evidence accumulated that it seems reasonable to rewrite an update, based fundamentally on the new findings. Focused on its relationship with cardioembolic strokes, today efforts are being targeted at understanding its pathophysiology, its diagnosis, and its prognostic implications, in order to learn if it should be treated. Areas covered: A non-systematic review of the literature was developed using the Pubmed and Cochrane databases, focusing on randomized clinical trials and large observational studies that evaluated new physiopathological and epidemiological aspects, new clinical scenarios in which it has been assessed and its association with dementia. Finally, those studies that proposed new possible treatments were reviewed. Expert commentary: Interatrial block is not only a predictor of supraventricular arrhythmias, is a subclinical disease that might be considered as a marker of risk for adverse outcomes. Although there is some evidence to suggest that early treatment may be beneficial, potential therapies have yet to be investigated.

Second-degree interatrial block: Brief review and concept

The advanced interatrial block (A-IAB) (P ≥ 120 ms plus ± pattern in II, III and aVF) corresponds at atrial level, to right or left advanced bundle branch block at ventricular level, and it is well known that these patterns may be seen transiently in relation to taquicardia or bradycardia (tachycardia or bradycardia dependent right or left bundle branch block). We present for the first time, the same phenomenon at atrial level. In one case, the A-IAB appears in relation to tachycardization and in the other disappears during a pause induced by ventricular premature complex.

Atrial cardiopathy: a mechanism of cryptogenic stroke

INTRODUCTION

Cryptogenic stroke accounts for approximately 30% of all ischemic strokes. Recently, atrial cardiopathy diagnosed by the presence of one of its serum, imaging, or electrocardiogram biomarkers has been shown to be associated with ischemic stroke, particularly of embolic subtypes. Areas covered: This paper aims to summarize data on occult atrial fibrillation and stroke, provide an overview on mechanisms, such as inflammation and fibrosis, of stroke in atrial cardiopathy, critically review data on biomarkers of atrial cardiopathy and their association with stroke, and suggest therapeutic implications, including directions for future research. Expert commentary: Atrial cardiopathy may constitute one of the mechanisms in cryptogenic stroke, and patients with evidence of atrial cardiopathy constitute a group of patients in whom clinical trials are warranted to test anticoagulation versus antiplatelet therapy to reduce stroke recurrence risk. In addition, more studies are needed to determine the degree of overlap between these atrial cardiopathy biomarkers and which one is more useful in predicting the risk of stroke and response to anticoagulation therapy.

Bayes Syndrome and Imaging Techniques

BACKGROUND

Interatrial block (IAB) is due to disruption in the Bachmann region (BR). According to whether interatrial electrical conduction is delayed or completely blocked through the BR, it can be classified as IAB of first, second or third degree. On the surface electrocardiogram, a P wave ≥ 120 ms (partial IAB) is observed or associated to the prolongation of the P wave with a biphasic (positive / negative) morphology in the inferior leads (advanced IAB). Bayes syndrome is defined as an advanced IAB associated with atrial arrhythmia, more specifically atrial fibrillation. Objective and Conclusion: The purpose of this review is to describe the latest evidence about an entity considered an anatomical and electrical substrate with its own name, which may be a predictor of supraventricular arrhythmia and cardioembolic cerebrovascular accidents, as well as the role of new imaging techniques, such as echocardiographic strain and cardiac magnetic resonance imaging, in characterizing atrial alterations associated with this syndrome and generally in the study of anatomy and atrial function.