Atrial time and voltage dispersion are both needed to predict new-onset atrial fibrillation in ischemic stroke patients

Factors associated with increased atrial fibrillation detection in patients with embolic stroke of undetermined source

BACKGROUND

Studies suggest that longer duration of cardiac monitoring after embolic stroke of undetermined source (ESUS) yields higher detection rates for atrial fibrillation (AF). A common strategy for cardiac monitoring after ESUS starts with a 14-day surface monitor, which is easier to administer, and lower cost compared to implantable monitoring. We tested whether cardiac markers associated with higher likelihood of AF detection can be used to identify patients with ESUS who are more likely to benefit from initial short-term monitoring.

METHODS

We adjudicated stroke etiology from patients with acute ischemic stroke discharged from a tertiary care medical center with 14-day surface cardiac monitor (ZioPatch®) between January 2019 and September 2023. The primary outcome was ≥30 seconds of AF on surface monitoring. Predictors included ECG and echocardiographic markers associated with AF in a general population identified during hospitalization. Associations were analyzed using Chi-squared or Fisher's exact tests and age-adjusted logistic regression.

RESULTS

We identified 415 patients with ESUS (mean age 67.2 years, 49.9% female). 4.3% (n=18/415) developed AF after a median of 13.8 days (IQR 13-15.8) of monitoring. 9.6% (n=8/83) of patients with enlarged left atrial dimension >4cm and 8.0% (n=9/113) of patients with mitral valve regurgitation developed AF. Significantly more patients with AF had a combination of enlarged left atrial dimension and/or mitral valve regurgitation (36.8% with AF vs 61.1% without AF, p=0.037). Adjusting for age, enlarged left atrial dimension remained significantly associated with increased odds of detection of AF (OR 3.17, 95% CI 1.20-8.36).

CONCLUSIONS

In patients with ESUS, the rate of AF detection using a surface 14-day cardiac monitor was low. However, the likelihood of detecting AF was higher among patients with enlarged left atrial dimension and mitral valve regurgitation, suggesting this group may benefit most from an initial short-term monitoring strategy.

Prognostic significance of ratio of P-wave duration to P-wave vector magnitude for mortality in acute anterior myocardial infarction

BACKGROUND

The impact of P-wave abnormality in acute anterior MI, where the culprit vessel is the left anterior descending artery, remains undetermined. This study aimed to elucidate the impact of P-wave morphology on clinical outcomes in acute anterior MI.

METHODS

Patients undergoing emergent percutaneous coronary intervention for acute anterior MI were enrolled between September 2014 and April 2019 (derivation cohort) and May 2019 through July 2023 (validation cohort). P-wave duration (Pd) and P-wave vector magnitude (Pvm) were measured. The Pvm was calculated as the square root of the sum of the squared P-wave magnitudes in leads II and V6 and one-half of the P-wave amplitude in V2. The patients were categorized into high and low Pd/Pvm groups using a statistically derived cut-off value. The endpoint comprised the composite of heart failure (HF) hospitalization and all-cause death.

RESULTS

Consecutive 426 patients were enrolled in this study (derivation cohort, 213 patients; validation cohort, 216 patients). The calculated cut-off value of Pd/Pvm for predicting the clinical endpoint, determined through receiver operating curve analysis, was 793.5 ms/mV (area under the curve [AUC] = 0.85, sensitivity of 73.8 %, and specificity of 94.0 %) in the derivation cohort. Kaplan-Meier analyses revealed a significantly higher risk of the endpoint in patients with high Pd/Pvm than those with low Pd/Pvm in derivation and validation cohorts (Log-rank p < 0.001 and p < 0.001, respectively). Multivariate Cox proportional hazards analysis identified advanced age, elevated Pd/Pvm, and reduced left ventricular ejection fraction as independent and significant factors associated with the endpoint in the validation cohort (p = 0.008, p < 0.001, and p < 0.001, respectively).

CONCLUSION

High Pd/Pvm was significantly associated with the composite of HF hospitalization and all-cause death after acute anterior MI.

ECG predictors of AF: A systematic review (predicting AF in ischaemic stroke-PrAFIS)

In 25% of patients presenting with embolic stroke, a cause is not determined. Atrial fibrillation (AF) is a commonly identified mechanism of stroke in this population, particularly in older patients. Conventional investigations are used to detect AF, but can we predict AF in this population and generally? We performed a systematic review to identify potential predictors of AF on 12-lead electrocardiogram (ECG).

METHOD

We conducted a search of EMBASE and Medline databases for prospective and retrospective cohorts, meta-analyses or case-control studies of ECG abnormalities in sinus rhythm predicting subsequent atrial fibrillation. We assessed quality of studies based on the Newcastle-Ottawa scale and data were extracted according to PRISMA guidelines.

RESULTS

We identified 44 studies based on our criteria. ECG patterns that predicted the risk of developing AF included interatrial block, P-wave terminal force lead V1, P-wave dispersion, abnormal P-wave-axis, abnormal P-wave amplitude, prolonged PR interval, left ventricular hypertrophy, QT prolongation, ST-T segment abnormalities and atrial premature beats. Furthermore, we identified that factors such as increased age, high CHADS-VASC, chronic renal disease further increase the positive-predictive value of some of these parameters. Several of these have been successfully incorporated into clinical scoring systems to predict AF.

CONCLUSION

There are several ECG abnormalities that can predict AF both independently, and with improved predictive value when combined with clinical risk factors, and if incorporated into clinical risk scores. Improved and validated predictive models could streamline selection of patients for cardiac monitoring and initiation of oral anticoagulants.

P-wave characteristics as electrocardiographic markers of atrial abnormality in prediction of incident atrial fibrillation - The Malmö Preventive Project

BACKGROUND

P-wave indices reflect atrial abnormalities contributing to atrial fibrillation (AF). We aimed to assess a comprehensive set of P-wave characteristics for prediction of incident AF in a population-based setting.

METHODS

Malmö Preventative Project (MPP) participants were reexamined in 2002-2006 with electrocardiographic (ECG) and echocardiographic examinations and followed for 5 years. AF-free subjects (n = 983, age 70 ± 5 years, 38% females) with sinus rhythm ECGs were included in the study. ECGs were digitally processed using the Glasgow algorithm. P-wave duration, axis, dispersion, P-terminal force in lead V1 and interatrial block (IAB) were evaluated. ECG risk score combining the morphology, voltage and length of P-wave (MVP score) was calculated. New-onset diagnoses of AF were obtained from nation-wide registers.

RESULTS

During follow up, 66 patients (7%) developed AF. After adjustment for age and gender, the independent predictors of AF were abnormal P-wave axis > 75° (HR 1.63 CI95% 1.95-11.03) and MVP score 4 (HR 6.17 CI 95% 1.76-21.64), both correlated with LA area: Person r - 0.146, p < 0.001 and 0.192, p < 0.001 respectively. Advanced IAB (aIAB) with biphasic P-wave morphology in leads III and aVF was the most prevalent variant of aIAB and predicted AF in a univariate model (HR 2.59 CI 95% 1.02-6.58).

CONCLUSION

P-wave frontal axis and MVP score are ECG-based AF predictors in the population-based cohort. Our study provides estimates for prevalence and prognostic importance of different variants of aIAB, providing a support to use biphasic P-wave morphology in lead aVF as the basis for aIAB definition.

CHA2DS2-VASc score, P-wave indexes, and echocardiographic parameters in sinus rhythm patients without valvular heart disease

OBJECTIVE

The aim of this study was to evaluate the correlation between P-wave indexes, echocardiographic parameters, and CHA2DS2-VASc score in patients without atrial fibrillation and valvular disease.

METHODS

This retrospective cross-sectional study included patients of a tertiary hospital with no history of atrial fibrillation, atrial flutter, or valve disease and collected data from June 2021 to May 2022. The exclusion criteria were as follows: unavailable medical records, pacemaker carriers, absence of echocardiogram report, or uninterpretable ECG. Clinical, electrocardiographic [i.e., P-wave duration, amplitude, dispersion, variability, maximum, minimum, and P-wave voltage in lead I, Morris index, PR interval, P/PR ratio, and P-wave peak time], and echocardiographic data [i.e., left atrium and left ventricle size, left ventricle ejection fraction, left ventricle mass, and left ventricle indexed mass] from 272 patients were analyzed.

RESULTS

PR interval (RHO=0.13, p=0.032), left atrium (RHO=0.301, p<0.001) and left ventricle diameter (RHO=0.197, p=0.001), left ventricle mass (RHO=0.261, p<0.001), and left ventricle indexed mass (RHO=0.340, p<0.001) were positively associated with CHA2DS2-VASc score, whereas P-wave amplitude (RHO=-0.141, p=0.02), P-wave voltage in lead I (RHO=-0.191, p=0.002), and left ventricle ejection fraction (RHO=-0.344, p<0.001) were negatively associated with the same score. The presence of the Morris index was associated with high CHA2DS2-VASc (p=0.022).

CONCLUSION

Prolonged PR interval, Morris index, increased left atrium diameter, left ventricle diameter, left ventricle mass, and left ventricle indexed mass values as well as lower P-wave amplitude, P-wave voltage in lead I, and left ventricle ejection fraction values were correlated with higher CHA2DS2-VASc scores.

Predicting risk of AF in ischaemic stroke using sinus rhythm ECG abnormalities: A meta-analysis

OBJECTIVE

To identify ECG changes in sinus rhythm that may be used to predict subsequent development of new AF.

METHOD

We identified prospective and retrospective cohort or case control studies evaluating ECG patterns from a 12-lead ECG in sinus rhythm taken in hospital or community predicting subsequent development of new AF. For each identified ECG predictor, we then identify absolute event rates and pooled risk ratios (RR) using an aggregate level random effects meta-analysis.

RESULTS

We identified 609,496 patients from 22 studies. ECG patterns included P wave terminal force V1 (PTFV1), interatrial block (IAB) and advanced interatrial block (aIAB), abnormal P wave axis (aPWA), PR prolongation and atrial premature complexes (APCs). Pooled risk ratios reached significance for each of these; PTFV1 RR 1.48 (95% CI 1.04-2.10), IAB 2.54 (95% CI 1.64-3.93), aIAB 4.05 (95% CI 2.64-6.22), aPWA 1.89 (95% CI 1.25-2.85), PR prolongation 2.22 (95% CI 1.27-3.87) and APCs 3.71 (95% CI 2.23-6.16). Diabetes reduced the predictive value of PR prolongation.

CONCLUSION

APC and aIAB were most predictive of AF, while IAB, PR prolongation, PTFV1 and aPWA were also significantly associated with development of AF. These support their use in a screening tool to identify at risk cohorts who may benefit from further investigation, or following stroke, with empirical anticoagulation.

Electrocardiographic Predictors of Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common pathological arrhythmia, and its complications lead to significant morbidity and mortality. However, patients with AF can often go undetected, especially if they are asymptomatic or have a low burden of paroxysms. Identification of those at high risk of AF development may help refine screening and management strategies.

METHODS

PubMed and Embase databases were systematically searched for studies looking at electrocardiographic predictors of AF from inception to August 2021.

RESULTS

A total of 115 studies were reported which examined a combination of atrial and ventricular parameters that could be electrocardiographic predictors of AF. Atrial predictors include conduction parameters, such as the PR interval, p-wave index and dispersion, and partial interatrial or advanced interatrial block, or morphological parameters, such as p-wave axis, amplitude and terminal force. Ventricular predictors include abnormalities in QRS amplitude, morphology or duration, QT interval duration, r-wave progression and ST segment, i.e., t-wave abnormalities.

CONCLUSIONS

There has been significant interest in electrocardiographic prediction of AF, especially in populations at high risk of atrial AF, such as those with an embolic stroke of undetermined source. This review highlights the breadth of possible predictive parameters, and possible pathological bases for the predictive role of each parameter are proposed.

The significance of the morphology-voltage-P-wave duration (MVP) ECG score for prediction of in-hospital and long-term atrial fibrillation in ischemic stroke

BACKGROUND

Atrial fibrillation (AF) is the most common preventable cause of stroke. Diagnosis of new AF is frequent after acute ischemic stroke (AIS). We aimed to evaluate the predictive value of the recently developed morphology-voltage-P-wave duration (MVP) ECG risk score for in-hospital and long-term AF diagnosis following AIS.

MATERIAL AND METHODS

In this observational investigation, we evaluated the ability of the MVP ECG risk score to predict AF in 266 consecutive patients with AIS. The study population was divided into three groups according to their calculated MVP ECG risk score on admission electrocardiography. The groups were compared in terms of their predictive value for in-hospital and long-term AF diagnosis.

RESULTS

After adjustment for confounding baseline variables, MVP ECG risk score 5-6 group had 13.2 times higher rates of in-hospital AF compared to MVP ECG risk score 0-2 group, which was used as the reference group. For long-term follow-up, MVP ECG risk score 5-6 group had 5.2 times higher rates of long-term AF compared to MVP ECG risk score 0-2 group. A ROC analysis showed that the optimal cut-off value of the MVP ECG risk score to predict in-hospital AF was 4 with 78% sensitivity and 76% specificity (AUC: 0.80; 95% CI: 0.64-0.96; p < 0.001), the optimal cut-off value of the MVP ECG risk score to predict long-term AF was 3 with 85% sensitivity and 59% specificity (AUC: 0.81; 95% CI: 0.76-0.86; p < 0.001).

CONCLUSION

The MVP ECG risk score, which can be easily calculated from a surface ECG, can be used to guide who needs stricter monitoring for the diagnosis of long-term AF in patients with AIS.

Heat map visualization for electrocardiogram data analysis

BACKGROUND

Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization.

METHODS

We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map.

RESULTS

In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. STE leads were mainly in the V₁, V₂ and V₃ leads. The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V₁, V₂, V₃) and others (V₄, V₅, V₆, I, II, III, aVF, aVL, aVR). Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. These cases also could be fully displayed and visualized in the heat map. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V₁, V₂, V₃ and V₄ leads could be clustered together, and the V₅, V₆, I and aVL leads could be clustered together.

CONCLUSION

Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information.

P-wave vector magnitude predicts the left atrial low-voltage area in patients with paroxysmal atrial fibrillation

BACKGROUND

P-wave amplitude (PWA) parameters can be the surrogate measures of the left atrial low-voltage areas (LVAs).

METHODS

We measured PWAs using an automated system in 50 patients with paroxysmal atrial fibrillation (AF). We examined the relationships between left atrial LVAs and PWA parameters, including P-wave vector magnitude, calculated as the square root of the sum of lead II PWA squared, lead V6 PWA squared, and a one-half lead V2 PWA squared.

RESULTS

Lead I PWA was most strongly correlated with LVAs in the anterior wall and appendage (anterior wall, R = -0.391, P = 0.006; appendage, R = -0.342, P = 0.016), whereas lead II PWA was most strongly correlated with LVAs in the septum, posterior wall, and bottom wall (septum, R = -0.413, P = 0.003; posterior wall, R = -0.297, P = 0.039; bottom wall; R = -0.288, P = 0.045). Although maximum, minimum, mean, and lead I PWAs were not correlated with total LVA, P-wave vector magnitude and lead II PWA were significantly correlated with total LVA (P-wave vector magnitude, R = -0.430, P = 0.002; lead II PWA, R = -0.323, P = 0.023). P-wave vector magnitude achieved the highest accuracy for predicting significant LVA (total LVA > 10%) with an area under the curve of 0.772; sensitivity, specificity, and positive and negative predictive values were 64%, 88%, 85%, and 69%, respectively, for the cutoff value of 0.130 mV.

CONCLUSION

P-wave vector magnitude is a useful electrocardiographic predictor of left atrial LVAs.

P-wave vector magnitude predicts recurrence of atrial fibrillation after catheter ablation in patients with persistent atrial fibrillation

BACKGROUND

The predictive efficacies of parameters related to P-wave amplitude (PWA) for atrial fibrillation (AF) recurrence after catheter ablation are unclear.

METHODS

We measured multiple PWA parameters using an automated system in 126 consecutive patients with persistent and long-standing persistent AF who underwent catheter ablation. The relationships between AF recurrence and various PWA parameters were examined, including the association with P-wave vector magnitude (calculated as the square root of the sum of lead II PWA squared, lead V6 PWA squared, and a one-half lead V2 PWA squared).

RESULTS

Atrial fibrillation did not recur in 87 patients (69%) during 32 ± 15 months of follow-up. The maximum PWA, mean PWA, and P-wave vector magnitude were lower in patients with AF recurrence than those without (maximum PWA, 0.14 ± 0.05 mV vs. 0.16 ± 0.05 mV, p = 0.017; mean PWA, 0.05 ± 0.02 mV vs. 0.06 ± 0.02 mV, p = 0.003; P-wave vector magnitude, 0.09 ± 0.03 mV vs. 0.13 ± 0.04 mV, p < 0.001). A multivariate Cox regression analysis revealed that the predictive ability of P-wave vector magnitude for AF recurrence was independent of other clinical properties (hazard ratio: 0.153, 95% confidence interval: 0.046-0.507, p = 0.002). Atrial fibrillation freedom rates of patients with P-wave vector magnitude higher and lower than 0.13 mV were 93% and 57%, respectively. P-wave vector magnitude weakly correlated with left atrial dimension (R = -0.280, p = 0.004).

CONCLUSIONS

P-wave vector magnitude can predict AF recurrence after catheter ablation in patients with persistent AF.