Left Atrium Assessment by Speckle Tracking Echocardiography in Cryptogenic Stroke: Seeking Silent Atrial Fibrillation

Assessment of left atrial function using two-dimensional speckle tracking echocardiography in cryptogenic stroke patients

BACKGROUND

Cryptogenic cerebrovascular stroke can be defined as an ischemic stroke that lacks a clear cause, even after a thorough evaluation. It should be distinguished from the embolic stroke of undetermined source (ESUS), a subgroup that includes cardio-embolic sources. This study aims to assess left atrial function through two-dimensional speckle tracking echocardiography (2D-STE) to determine its potential association with cryptogenic stroke and its predictive value for subclinical atrial fibrillation (AF). Our prospective cohort study involved 62 patients with unexplained cerebrovascular stroke or TIA, regardless of gender. Following TEE assessments, 22 patients were excluded due to identified sources of cardio-embolism. The remaining 40 participants were clustered into Group I. Group II, consisted of 40 healthy individuals without significant medical history, served as a control group. Both groups underwent two-dimensional trans-thoracic echocardiography and speckle tracking echocardiography.

RESULTS

LA dysfunction parameters exhibited significant differences between Group I and Group II. LV diastolic dysfunction, LAVI, LAEF, and LASr were notably affected in Group I. At the same time, LA diameter in the parasternal long-axis view (PLAX) displayed a significant difference with a p value of 0.001. Within Group I, 14 patients experienced AF episodes (Group Ia, 35%); while, the remaining 26 were categorized as Group Ib (65%). LV diastolic dysfunction displayed a p value < 0.011; while, LAVI, LAEF, and LASr exhibited considerable differences with p values < 0.0001. However, the LA diameter showed no significant variation between the two groups. LASr emerged as the most sensitive and specific parameter for predicting AF, with a cutoff point of ≤ 24.5% and a p value < 0.0001. LAEF showed a cutoff point of ≤ 40.5% and a p value of 0.011. Meanwhile, LAVI demonstrated the lowest sensitivity and specificity, with a mean cutoff point of ≥ 38.5 ml/m2 and a p value of 0.003.

CONCLUSIONS

2D-STE is crucial for assessing LA dysfunction as a potential cryptogenic stroke cause after TEE and ruling out cardio-embolism sources. LASr serves as a key LA cardiopathy indicator, even preceding AF. LASr independently poses an AF risk. While LAEF and LAVI are significant LA dysfunction parameters and AF predictors, they exhibit lower sensitivity and specificity than LASr.

pRR30, pRR3.25% and Asymmetrical Entropy Descriptors in Atrial Fibrillation Detection

BACKGROUND

Early detection of atrial fibrillation (AF) is essential to prevent stroke and other cardiac and embolic complications. We compared the diagnostic properties for AF detection of the percentage of successive RR interval differences greater than or equal to 30 ms or 3.25% of the previous RR interval (pRR30 and pRR3.25%, respectively), and asymmetric entropy descriptors of RR intervals. Previously, both pRR30 and pRR3.25% outperformed many other heart rate variability (HRV) parameters in distinguishing AF from sinus rhythm (SR) in 60 s electrocardiograms (ECGs).

METHODS

The 60 s segments with RR intervals were extracted from the publicly available Physionet Long-Term Atrial Fibrillation Database (84 recording, 24 h Holter ECG). There were 31,753 60 s segments of AF and 32,073 60 s segments of SR. The diagnostic properties of all parameters were analysed with receiver operator curve analysis, a confusion matrix and logistic regression. The best model with pRR30, pRR3.25% and total entropic features (H) had the largest area under the curve (AUC)-0.98 compared to 0.959 for pRR30-and 0.972 for pRR3.25%. However, the differences in AUC between pRR30 and pRR3.25% alone and the combined model were negligible from a practical point of view. Moreover, combining pRR30 and pRR3.25% with H significantly increased the number of false-negative cases by more than threefold.

CONCLUSIONS

Asymmetric entropy has some potential in differentiating AF from SR in the 60 s RR interval time series, but the addition of these parameters does not seem to make a relevant difference compared to pRR30 and especially pRR3.25%.

Atrial strain and occult atrial fibrillation in cryptogenic stroke patients: a systematic review and meta-analysis

BACKGROUND

Cryptogenic stroke (CS) remains a significant cause of morbidity. Failure to identify the underlying pathology increases the rate of recurrence. Atrial fibrillation (AF) seems to be responsible for a substantial proportion of CS. Thus, there is an unmet need to identify and properly treat those with silent AF.

PURPOSE

To investigate the association between left atrial strain and newly diagnosed AF in CS patients.

OBJECTIVES

We searched major electronic databases for articles assessing the relationship between either peak left atrial longitudinal (PALS) or peak contractile (PACS) strain-quantified using speckle tracking echocardiography-and the incidence of occult AF during the diagnostic work-up of CS patients.

RESULTS

Eleven studies (two thousand and eighty-one patients) were analyzed. Incidence of occult AF was 19%. Both PALS and PACS were significantly lower in patients with newly diagnosed AF (MD - 8.6%, 95%CI - 10.7 to - 6.4, I2 86.4% and MD - 5.5, 95%CI - 6.8 to - 4.2, I2 80.8%). According to the diagnostic accuracy meta-analysis, PALS < 20% present 71% (95%CI 47-87%) sensitivity and 71% (95%CI 60-81%) specificity for the diagnosis of occult AF, assuming a prevalence of 20%. The corresponding values for PACS < 11% are 83% (95%CI 57-94%) and 78% (95%CI 56-91%).

CONCLUSION

Both PALS and PACS are significantly lower in patients with CS and silent AF. It seems that the cut-off values mentioned above could help physicians in identifying patients who may benefit more from prolonged rhythm monitoring. More studies are needed to confirm these findings.

Increased Left Atrial Stiffness is Significantly Associated with Paroxysmal Atrial Fibrillation in Diabetic Patients

Purpose

Atrial fibrillation (AF) and diabetes mellitus (DM) are common pathogenic diseases. Diabetes is an independent risk factor for AF, and coexisting AF is a risk factor for the diabetic pa-tient's progression. The purpose of this study was to see if two-dimensional-speckle tracking echocardiography (2D-STE) might provide valuable criteria for determining the risk of AF in diabetic patients.

Patients and Methods

This retrospective study compared 30 adult diabetic patients with documented paroxysmal atrial fibrillation (PAF) with 30 age- and sex-matched diabetic patients without PAF. Inclusion criteria were: age ≥18 years, sinus rhythm, diabetes mellitus type 2, and the ability to sign the informed consent. Exclusion criteria included: moderate or severe valvular disease, previous myocardial infarction, left ventricular ejection fraction (LVEF) <50%, congenital heart disease, a history of cardiac surgery, paced atrial or ventricular rhythm, inadequate echocardiography imaging. The medical history, clinical, biochemical data and the results of the transthoracic cardiac ultrasound examination were registered during their evaluation at the outpatients cardiology clinics.

Results

The mean age of the patients was 62.5±1.7 years, 60% were men. Diabetic patients who experienced PAF episodes demonstrated significantly impaired left atrial (LA) deformation patterns, with decreased LA strains and increased LA stiffness (p < 0.05).

Conclusion

The present study demonstrates that LA strains and LA stiffness are significantly associated with the occurrence of PAF in diabetic patients. As 2D-STE of the LA is more sensitive than routine echocardiographic examination, it should be performed in patients suspected of being suffering from PAF.

Left atrial deformation and risk of transient ischemic attack and stroke in patients with paroxysmal atrial fibrillation

Left atrial (LA) remodeling is closely related to the occurrence of cerebral stroke; however, the relationship between early-stage impaired deformability of the left atrium and stroke/transient ischemic attack (TIA) remains unclear. The aim of this study was to evaluate the changes in LA deformability and to assess its relationship with stroke/TIA events using speckle tracking echocardiography. A total of 365 patients with paroxysmal atrial fibrillation (non-stroke/TIA [n = 318]; stroke/TIA [n = 47]) underwent comprehensive echocardiography with speckle tracking imaging to calculate mean LA longitudinal strain and strain rate values from apical 4-chamber, 2-chamber, and 3-chamber views. The stroke/TIA group was older, had a greater proportion of males, and had lower LA strain rate during left ventricular early diastole (SRE), and the difference was statistically significant (P < .05). On univariate linear regression analysis, the following clinical and conventional echocardiographic parameters showed a significant linear correlation (P < .001) with SRE: E/A ratio; LA volume index (VI); body mass index; mean E/e'; left ventricular ejection fraction; age; and hypertension. Multiple linear regression analysis revealed a linear dependence between SRE and E/A ratio, LA VI, and body mass index. The regression equation was y = -1.430-0.394X1 + 0.012X2 + 0.019X3 (P < .001) (y, SRE; X1, E/A ratio; X2, LA VI; X3, body mass index). In multivariate logistic regression analyses, SRE and sex ratio were independent risk factors for stroke/TIA (SRE, odds ratio 2.945 [95% confidence interval 1.092-7.943]; P = .033; sex, odds ratio 0.462 [95% confidence interval 0.230-0.930]; P = .031). Among patients with paroxysmal atrial fibrillation, SRE reflected impaired deformability of the left atrium in the early stages and was associated with the risk of stroke/TIA.

Statistical and Diagnostic Properties of pRRx Parameters in Atrial Fibrillation Detection

BACKGROUND

We studied the diagnostic properties of the percentage of successive RR intervals differing by at least x ms (pRRx) as functions of the threshold value x in a range of 7 to 195 ms for the differentiation of atrial fibrillation (AF) from sinus rhythm (SR).

METHODS

RR intervals were measured in 60-s electrocardiogram (ECG) segments with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). For validation, we have used ECGs from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Atrial Fibrillation Database. The pRRx distributions in AF and SR in relation to x were studied by histograms, along with the mutual association by the nonparametric Spearman correlations for all pairs of pRRx, and separately for AF or SR. The optimal cutoff values for all pRRx were determined using the receiver operator curve characteristic. A nonparametric bootstrap with 5000 samples was used to calculate a 95% confidence interval for several classification metrics.

RESULTS

The distributions of pRRx for x in the 7-195 ms range are significantly different in AF than in SR. The sensitivity, specificity, accuracy, and diagnostic odds ratios differ for pRRx, with the highest values for x = 31 ms (pRR31) rather than x = 50 (pRR50), which is most commonly applied in studies on heart rate variability. For the optimal cutoff of pRR31 (68.79%), the sensitivity is 90.42%, specificity 95.37%, and the diagnostic odds ratio is 194.11. Validation with the ECGs from the MIT-BIH Atrial Fibrillation Database confirmed our findings.

CONCLUSIONS

We demonstrate that the diagnostic properties of pRRx depend on x, and pRR31 outperforms pRR50, at least for ECGs of 60-s duration.

Utility of speckle-tracking echocardiography for predicting atrial fibrillation following ischemic stroke: a systematic review and meta-analysis

Undiagnosed atrial fibrillation (AF) is one of the main sources of cryptogenic stroke. And strain indices measured by speckle-tracking echocardiography are associated with atrial remodeling supposed to be the substrate of AF. Therefore, there is a strong need for evaluating the utility of speckle-tracking echocardiography to predict the likelihood of AF in patients with cryptogenic stroke. PubMed, Embase and Cochrane Database were searched for studies. The random-effects model was used to calculate the pooled results, and summary receiver operating characteristic curve (SROC) analysis was performed to show the overall predictive value. There were 1483 patients with cryptogenic stroke from 8 studies. Meta-analysis showed that strain indices including global longitudinal strain (GLS) (mean difference [SMD]: - 0.22, 95% confidence interval [95% CI] - 0.40 to - 0.04), left atrial reservoir strain (εR), (SMD: - 0.87, 95% CI - 1.26 to - 0.48, conduit strain (εCD) (SMD: - 0.56, 95% CI - 0.81 to - 0.30), contractile strain (εCT) (SMD: - 1.00, 95% CI - 1.39 to - 0.61), and left atrial reservoir strain rate (SRe) (SMD: - 0.54, 95% CI - 0.80 to - 0.28) measured at the period of cryptogenic stroke was significantly decreased in patients with AF occurrence compared to without. SROC analysis suggested an acceptable predictive efficiency of εR for AF occurrence (AUC = 0.799). For patients after cryptogenic stroke, GLS, εR, εCD, εCT and SRe were significantly decreased in AF occurrence compared with non-occurrence. But there was no value in left atrial reservoir strain rate (SRs) and contractile strain rate (SRa) for predicting AF.

Using Minimum Redundancy Maximum Relevance Algorithm to Select Minimal Sets of Heart Rate Variability Parameters for Atrial Fibrillation Detection

Heart rate is quite regular during sinus (normal) rhythm (SR) originating from the sinus node. In contrast, heart rate is usually irregular during atrial fibrillation (AF). Complete atrioventricular block with an escape rhythm, ventricular pacing, or ventricular tachycardia are the most common exceptions when heart rate may be regular in AF. Heart rate variability (HRV) is the variation in the duration of consecutive cardiac cycles (RR intervals). We investigated the utility of HRV parameters for automated detection of AF with machine learning (ML) classifiers. The minimum redundancy maximum relevance (MRMR) algorithm, one of the most effective algorithms for feature selection, helped select the HRV parameters (including five original), best suited for distinguishing AF from SR in a database of over 53,000 60 s separate electrocardiogram (ECG) segments cut from longer (up to 24 h) ECG recordings. HRV parameters entered the ML-based classifiers as features. Seven different, commonly used classifiers were trained with one to six HRV-based features with the highest scores resulting from the MRMR algorithm and tested using the 5-fold cross-validation and blindfold validation. The best ML classifier in the blindfold validation achieved an accuracy of 97.2% and diagnostic odds ratio of 1566. From all studied HRV features, the top three HRV parameters distinguishing AF from SR were: the percentage of successive RR intervals differing by at least 50 ms (pRR50), the ratio of standard deviations of points along and across the identity line of the Poincare plots, respectively (SD2/SD1), and coefficient of variation-standard deviation of RR intervals divided by their mean duration (CV). The proposed methodology and the presented results of the selection of HRV parameters have the potential to develop practical solutions and devices for automatic AF detection with minimal sets of simple HRV parameters. Using straightforward ML classifiers and the extremely small sets of simple HRV features, always with pRR50 included, the differentiation of AF from sinus rhythms in the 60 s ECGs is very effective.

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.