P Wave Parameters and Indices: A Critical Appraisal of Clinical Utility, Challenges, and Future Research-A Consensus Document Endorsed by the International Society of Electrocardiology and the International Society for Holter and Noninvasive Electrocardiology

The Role of P-Wave Variables in Enhancing Prediction of New-Onset Atrial Fibrillation in Patients With Acute Myocardial Infarction

BACKGROUND

After acute myocardial infarction (AMI), it is common to observe new-onset atrial fibrillation (NOAF), which is often related to a negative prognosis. Some P-wave variables (P-wave duration [PWD], P-wave amplitude, and interatrial block [IAB]), reflecting the process of electrical and structural remodeling, could predict the risk of atrial fibrillation (AF). This study aimed to assess the predictive value of P-wave variables for post-AMI NOAF.

METHODS

We retrospectively analyzed 1581 AMI patients with no prior AF, using follow-up data from January 2023 to January 2024. P-wave variables were measured, and patients were grouped based on in-hospital NOAF occurrence.

RESULTS

Overall, 164 (10.3%) of the 1581 patients had NOAF. The age (61.08 ± 12.02 vs. 67.91 ± 11.60, p < 0.001), left atrial size (36.31 ± 3.94 vs. 39.12 ± 5.51, p < 0.001), Brain Natriuretic Peptide (1588.45 ± 3346.18 vs. 3864.39 ± 6251.92, p < 0.001), P-wave variables (PWD: 102.78 ± 12.56 vs. 117.88 ± 18.81, p < 0.001; P-wave amplitude: 0.12 ± 0.04 vs. 0.13 ± 0.04, p = 0.041; interatrial block: 89.6% vs. 10.3%, p < 0.001), congestive heart failure (4.7% vs. 23.2%, p < 0.001), and Killip > 1 (25.3% vs. 55.5%, p < 0.001) showed significant differences between the non-AF and NOAF groups. P-wave variables were significantly associated with an increased risk of NOAF in multivariable regression analysis.

CONCLUSIONS

The addition of P-wave variables to AF risk factors from literature and guidelines significantly improved NOAF risk discrimination. P-wave variables were strongly associated with NOAF after AMI. Adding these variables enhanced the predictive performance for post-AMI NOAF.

Association of abnormal P-wave parameters with all-cause mortality in diffuse large B-cell lymphoma

Patients diagnosed with diffuse large B-cell lymphoma (DLBCL) are at increased risk of developing atrial fibrillation (AF). Abnormal P-wave parameters (PWPs) have been identified as independent predictors of AF, however, their prognostic significance in DLBCL patients remains unknown. Newly diagnosed DLBCL patients from January 2015 to August 2022 were retrospectively included in this study. Patients were devided as with abnormal PWPs or without it. Primary outcome was the all-cause mortality. The median duration of follow-up was 16.3 months. The Kaplan‒Meier method and multivariable COX proportional hazards regression models were used to analyze the relationship between PWPs and all-cause mortality. Logistic regression analyses were performed to identify risk factors associated with PWPs. A total of 374 newly diagnosed DLBCL patients were included, of whom 137 patients exhibited abnormalities in PWPs. Compared to the group with normal PWPs, patients with PWPs abnormalities had a higher proportion of males (p = 0.001), elevated levels of blood urea nitrogen (p = 0.038) and blood creatinine (p = 0.005), and a higher rate of all-cause mortality (p = 0.001). PWPs, particularly P-wave duration (p = 0.017) and P-wave terminal force in lead V1 (PTFV1) (p = 0.001), were independently correlated with all-cause mortality in DLBCL patients. Furthermore, male patients exhibited a higher susceptibility to abnormal PWPs (p = 0.001). PWPs, particularly P-wave duration and PTFV1, serve as simple yet effective prognostic indicators for all-cause mortality in DLBCL patients. Consequently, vigilant monitoring of PWPs, particularly in male patients, is warranted to accurately evaluate the prognosis of DLBCL.

Association Between P-Wave Duration, Dispersion, and Interatrial Block and Atrial High-Rate Episodes in CIED Patients

INTRODUCTION

Atrial high-rate episodes (AHRE) have been linked to increased thromboembolic risk and all-cause mortality in patients with cardiac implantable electronic devices (CIEDs). Various predictors of AHRE development have been identified, emphasizing the need for close monitoring and the potential transition to clinical atrial fibrillation (AF). However, the predictive value of P wave characteristics on AHRE development remains conflicting. This meta-analysis aims to summarize existing data to investigate this association.

METHOD

We examined studies from MEDLINE and EMBASE databases up to May 2024 to investigate the association of baseline P-wave duration (PWD), P-wave dispersion (PWDIS), and interatrial block (IAB) with the risk of developing AHRE. We extracted the mean and standard deviations of PWD and PWDIS to calculate the pooled mean difference (MD). Risk ratios (RR) and 95% confidence intervals (CIs) were used to assess the association between IAB and AHRE risk, using the generic inverse variance method for combination.

RESULTS

The meta-analysis included nine studies. Patients with AHRE had longer PWD and PWDIS compared to those without AHRE, with a pooled MD for PWD of 9.17 ms (95% CI: 4.74-13.60; I2 = 47%, p < 0.001) and a pooled MD for PWDIS of 20.56 ms (95% CI: 11.57-29.56; I2 = 57%, p < 0.001). Additionally, patients with IAB had a higher risk of developing AHRE, with a pooled RR of 3.33 (95% CI: 2.53-4.38; I2 = 0%, p < 0.001), compared to those without IAB.

CONCLUSIONS

Our meta-analysis found that patients with AHRE had higher PWD and PWDIS than those without AHRE. Additionally, IAB was associated with a higher risk of developing AHRE. These findings emphasize the importance of close monitoring and risk stratification, particularly for patients with P wave abnormalities.

[Intrinsic steady-state pattern of mouse cardiac electrophysiology: analysis using a characterized quantitative electrocardiogram strategy]

OBJECTIVE

To explore the intrinsic steady-state electrophysiological properties of mouse heart under physiological conditions by high-resolution quantitative analysis.

METHODS

Twenty-two young adult C57BL/6 mice with a 1:1 male-to-female ratio were used. The limbs of the mice were fixed without anesthesia, and electrocardiographic waveforms, including characteristic P-waves, R-waves, and ST-waves, were recorded using a sensitive 12-lead electrophysiological recorder (ECGsqa) under spontaneous breathing. LabScribe software was used to extract and quantify high-resolution time course and amplitude parameters within a single cardiac cycle from the V3 precordial lead. Pearson correlation test combined with simple linear regression was used to generate a scatter plot of ECG parameter fitting. The common and unique correlation parameters were separately identified by joint associations for profiling the quantitative association network.

RESULTS

ECGsqa analysis identified and quantified 14 characteristic ECG parameters, 28.6% of which showed statistical differences between the groups. Compared to male mice, female mice exhibited higher amplitudes and velocities of R and ST waves. Among the 51 association pairs identified in primary association analysis, 47.1% were positively correlated, including shared (29.2%), male-specific (29.2%), and female-specific (41.7%) association groups. Second-order clustering of the association pairs revealed that the amplituderate association pairs of each waveform voltage in both male and female mouse hearts were strongly correlated. The male mice showed an atrioventricular interconnection pattern, while the female mice showed a unique atrial conduction system quality dependence. The distribution network characteristics of the association groups showed that sex-specific and common correlation sets formed a certain series pattern.

CONCLUSION

We discovered a novel intrinsic correlation network of cardiac electrophysiological traits in male and female mice, which reveals the key internal quantitative characteristics and gender difference of both atrial and ventricular conduction systems.

Predictors of atrial fibrillation after embolic stroke of undetermined source in patients with implantable loop recorders

BACKGROUND

In patients with embolic stroke of undetermined source (ESUS), underlying subclinical atrial fibrillation (AF) is often suspected. Previous studies identifying predictors of AF have been limited in their ability to diagnose episodes of AF. Implantable loop recorders enable prolonged, continuous, and therefore more reliable detection of AF. The aim of this study was to identify clinical and ECG parameters as predictors of AF in ESUS patients with implantable loop recorders.

METHODS

101 ESUS patients who received an implantable loop recorder between 2012 and 2020 were included in this study. Patients were followed up regularly on a three-monthly outpatient interval.

RESULTS

During a mean follow-up of 647 ± 385 days, AF was detected in 26 patients (26%). Independent risk factors of AF were age ≥ 60 years (HR 2.753, CI 1.129-6.713, p = 0.026), P-wave amplitude in lead II ≤ 0.075 mV (HR 3.751, CI 1.606-8.761, p = 0.002), and P-wave duration ≥ 125 ms (HR 4.299, CI 1.844-10.021, p < 0.001). In patients without risk factors, the risk of developing AF was 16%. In the presence of one risk factor, the probability increased only slightly to 18%. With two or three risk factors, the risk of AF increased to 70%.

CONCLUSION

AF was detected in about one in four patients after ESUS in this study. A comprehensive evaluation involving multiple parameters and the existence of multiple risk factors yields the highest predictive accuracy for detecting AF in patients with ESUS.

Role of Cardiac Biomarkers in Stroke and Cognitive Impairment

This topical review assesses the growing role of cardiac biomarkers beyond cardiovascular health and focuses on their importance in stroke and dementia. The first part describes blood-based cardiac biomarkers in patients with stroke and highlights applications in the setting of early diagnosis, poststroke complications, outcome prediction as well as secondary prevention. Among other applications, natriuretic peptides can be helpful in differentiating stroke subtypes. They are also currently being investigated to guide prolonged ECG monitoring and secondary prevention in patients with stroke. Elevated cardiac troponin after ischemic stroke can provide information about various poststroke complications recently termed the stroke-heart syndrome. The second part focuses on the role of cardiac biomarkers in vascular cognitive impairment and dementia, emphasizing their association with structural brain lesions. These lesions such as silent brain infarcts and white matter hyperintensities often co-occur with cardiac disease and may be important mediators between cardiovascular disease and subsequent cognitive decline. ECG and echocardiogram measurements, in addition to blood-based biomarkers, show consistent associations with vascular brain changes and incident dementia, suggesting a role in indicating risk for cognitive decline. Together, the current evidence suggests that cardiac blood-based, electrophysiological, and imaging biomarkers can be used to better understand the heart and brain connection in the setting of not only stroke but also dementia.

Atrial cardiomyopathy revisited-evolution of a concept: a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS)

AIMS

The concept of "atrial cardiomyopathy" (AtCM) had been percolating through the literature since its first mention in 1972. Since then, publications using the term were sporadic until the decision was made to convene an expert working group with representation from four multinational arrhythmia organizations to prepare a consensus document on atrial cardiomyopathy in 2016 (EHRA/HRS/APHRS/SOLAECE expert consensus on atrial cardiomyopathies: definition, characterization, and clinical implication). Subsequently, publications on AtCM have increased progressively.

METHODS AND RESULTS

The present consensus document elaborates the 2016 AtCM document further to implement a simple AtCM staging system (AtCM stages 1-3) by integrating biomarkers, atrial geometry, and electrophysiological changes. However, the proposed AtCM staging needs clinical validation. Importantly, it is clearly stated that the presence of AtCM might serve as a substrate for the development of atrial fibrillation (AF) and AF may accelerates AtCM substantially, but AtCM per se needs to be viewed as a separate entity.

CONCLUSION

Thus, the present document serves as a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS) to contribute to the evolution of the AtCM concept.

Exploring the impact of electrocardiographic parameters on the risk of common arrhythmias: a two-sample Mendelian randomization study

Background

Observational studies have shown that heart rate (HR), heart rate variability (HRV), P-wave terminal force, P-wave duration, T-wave amplitude and PR interval are associated with risk factors for atrial fibrillation (AF) or bradycardia. Arrhythmias are associated with many causes of hospitalization. However, observational studies are susceptible to confounding factors that have not yet been identified. The objective of this study was to clarify the causal relationships by Mendelian randomization analysis.

Methods

We conducted a two-sample and multivariate Mendelian randomization (MVMR) analysis using genome-wide association study (GWAS) data from a European population to assess the total and direct causal effects of HR, three HRV traits, P-wave terminal force, P-wave duration, T-wave top amplitude in five-lead modes, and the PR interval on the risk of AF (N=191,205), bradycardia (N=463,010), and supraventricular tachycardia (SVT) (N=463,010).

Results

The results of the univariate MR analysis revealed the following significant causal effects: the higher the genetically predicted PR interval, the lower the risk of AF; the higher the HR and T-wave top amplitude (aVR leads and V3 + V4 + aVL leads), the lower the risk of bradycardia; and the higher HR and the lower PR interval, the higher the risk of SVT. The multivariate MR results indicated that the HRV_standard deviation of the normal-to-normal (SDNN) interval had an independent causal effect on the risk of AF [odds ratio (OR): 0.515; 95% confidence interval (CI): 0.278-0.954; P=0.03], and the T-wave top amplitude in the aVR leads (OR: 0.998; 95% CI: 0.996-0.999; P<0.001) and the HRV_SDNN (OR: 0.988; 95% CI: 0.976-1.000; P=0.045) had independent causal effects on the risk of bradycardia.

Conclusions

The HRV_SDNN had an independent causal effect on AF, while the HRV_SDNN and T-wave top amplitude in the aVR leads had independent causal effects on bradycardia, which suggests that some of the electrocardiographic parameters have preventive effects on the incidence of AF and bradycardia.

Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events

Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syndrome or conduction disorders, predicting PMI is challenging, as patients often experience related symptoms. This study was designed to create a deep learning model (DLM) for predicting future PMI from ECG data and assess its ability to predict future cardiovascular events. In this study, a DLM was trained on a dataset of 158,471 ECGs from 42,903 academic medical center patients, with additional validation involving 25,640 medical center patients and 26,538 community hospital patients. Primary analysis focused on predicting PMI within 90 days, while all-cause mortality, cardiovascular disease (CVD) mortality, and the development of various cardiovascular conditions were addressed with secondary analysis. The study's raw ECG DLM achieved area under the curve (AUC) values of 0.870, 0.878, and 0.883 for PMI prediction within 30, 60, and 90 days, respectively, along with sensitivities exceeding 82.0% and specificities over 81.9% in the internal validation. Significant ECG features included the PR interval, corrected QT interval, heart rate, QRS duration, P-wave axis, T-wave axis, and QRS complex axis. The AI-predicted PMI group had higher risks of PMI after 90 days (hazard ratio [HR]: 7.49, 95% CI: 5.40-10.39), all-cause mortality (HR: 1.91, 95% CI: 1.74-2.10), CVD mortality (HR: 3.53, 95% CI: 2.73-4.57), and new-onset adverse cardiovascular events. External validation confirmed the model's accuracy. Through ECG analyses, our AI DLM can alert clinicians and patients to the possibility of future PMI and related mortality and cardiovascular risks, aiding in timely patient intervention.

Screening Tool for Paroxysmal Atrial Fibrillation Based on a Deep-Learning Algorithm Using Printed 12-Lead Electrocardiographic Records during Sinus Rhythm

Background

Recent advancements in artificial intelligence (AI) have significantly improved atrial fibrillation (AF) detection using electrocardiography (ECG) data obtained during sinus rhythm (SR). However, the utility of printed ECG (pECG) records for AF detection, particularly in developing countries, remains unexplored. This study aims to assess the efficacy of an AI-based screening tool for paroxysmal AF (PAF) using pECGs during SR.

Methods

We analyzed 5688 printed 12-lead SR-ECG records from 2192 patients admitted to Beijing Chaoyang Hospital between May 2011 to August 2022. All patients underwent catheter ablation for PAF (AF group) or other electrophysiological procedures (non-AF group). We developed a deep learning model to detect PAF from these printed SR-ECGs. The 2192 patients were randomly assigned to training (1972, 57.3% with PAF), validation (108, 57.4% with PAF), and test datasets (112, 57.1% with PAF). We developed an applet to digitize the printed ECG data and display the results within a few seconds. Our evaluation focused on sensitivity, specificity, accuracy, F1 score, the area under the receiver-operating characteristic curve (AUROC), and precision-recall curves (PRAUC).

Results

The PAF detection algorithm demonstrated strong performance: sensitivity 87.5%, specificity 66.7%, accuracy 78.6%, F1 score 0.824, AUROC 0.871 and PRAUC 0.914. A gradient-weighted class activation map (Grad-CAM) revealed the model's tailored focus on different ECG areas for personalized PAF detection.

Conclusions

The deep-learning analysis of printed SR-ECG records shows high accuracy in PAF detection, suggesting its potential as a reliable screening tool in real-world clinical practice.

An interesting electrocardiogram caused by lead reversal

BACKGROUND

During normal sinus rhythm, atrial depolarization is conducted from right atrium to left atrium through Bachmann's bundle, and a normal P wave axis which is measured on the frontal plane is between 0º and + 75º. The change of P wave polarity is helpful for the analysis of origin point.

CASE PRESENTATION

We report a patient with negative P wave in lead I. The characteristics of QRS complex in leads V1 to V6 are helpful to preliminarily differential diagnosis. The 12-lead electrocardiogram (ECG) with correct limb leads (right arm-left arm) placement shows sinus rhythm with complete right bundle branch block (RBBB).

CONCLUSIONS

The change of P wave polarity as well as characteristics of QRS complex can help identify limb-lead reversals.

The effect of high-power short-duration pulmonary vein isolation on PWPT-a predictor of paroxysmal atrial fibrillation

BACKGROUND

The P wave peak time (PWPT) is a predictor of paroxysmal atrial fibrillation (PAF). High-power short-duration ablation has been associated with improved durability of circumferential pulmonary vein electrical isolation (PVI). We investigated the effect of high-power short-duration PVI on PWPT in patients with PAF.

METHODS

Out of 111 patients with PAF, 91 received radiofrequency ablation (ablation group) and 20 received medication treatment (control group). A VIZIGO sheath and an STSF catheter (Biosense Webster, CA, USA) were used together for high-power short-duration circumferential PVI at ablation index values of 500 and 400 for the anterior and posterior walls, respectively. The patients were followed up for 12 months.

RESULTS

The preoperative PWPT in the ablation group was similar to that in the control group: PWPT II = 54.38 ± 6.18 ms vs. 54.35 ± 6.12 ms (p > 0.05), PWPT V1 = 54.19 ± 6.21 ms vs. 54.31 ± 6.08 ms (p > 0.05), respectively. Circumferential PVI was achieved for all patients in the ablation group during the operation. At the 12-month follow-up, there were seven cases of AF recurrence. The PWPT in the ablation group 12 months postoperatively was shorter than the preoperative value: PWPT II = 49.39 ± 7.11 ms vs. 54.38 ± 6.18 ms (p < 0.001), PWPT V1 = 47.69 ± 7.01 ms vs. 54.19 ± 6.21 ms (p < 0.001). The PWPT in the patients with AF recurrence was significantly longer than that in the non-recurrence patients: PWPT II = 50.48 ± 7.12 ms vs. 47.33 ± 6.21 ms (p < 0.001), PWPT V1 = 50.84 ± 7.05 ms vs. 47.19 ± 6.27 ms, (p < 0.001). The PWPT of the control group at the 12-month follow-up was similar to the baseline level: PWPT II = 54.32 ± 6.20 ms vs. 54.35 ± 6.12 ms (p > 0.05), PWPT V1 = 53.89 ± 6.01 ms vs. 54.31 ± 6.08 ms (p > 0.05).

CONCLUSION

The results showed that high-power short-duration PVI had a positive effect on PWPT, which is a predictor of PAF.

Atrial electrical remodeling and function after transcatheter aortic valve replacement in patients with aortic stenosis

To examine reverse atrial electrical remodeling in patients with aortic stenosis (AS) after trans-catheter aortic valve replacement (TAVR). In 65 consecutive patients with severe AS (83 ± 4 years, 47 (72.3%) females), we analyzed ECG records for the P wave duration (PWD) in lead II and P-terminal force (PTFV1) in V1, and measured cardiac dimensions and function by echocardiography (ECHO) following TAVR. Biomarkers were measured to assess myocardial injury by TAVR. TAVR was successfully performed without major complications: the aortic valve area increased from 0.62 ± 0.14 cm2 to 1.52 ± 0.24cm2, and the trans-aortic pressure gradient decreased from 58.4 ± 15.9 mmHg to 15.0 ± 19.6 mmHg. PWD and PTFV increased immediately after TAVR and returned to the pre-TAVR levels on the next day. Then, the PWD declined toward 6 months after TAVR non-significantly in all patients, but significantly in 25 patients with baseline PWD ≥ 130 ms (P = 0.039). PTFV1 showed no long-term change. Improvement was observed in the ejection fraction, all thickness of the left ventricle and in the left atrial dimensions on ECHO. After recovery from transient aggravation by TAVR procedure, PWD reversed slowly, and the change was significant in those with baseline PWD ≥ 130 ms while change in PTFV1 was not significant at 6 months of follow-up. ECHO showed a reversal of remodeling in the left ventricle and in the left atrial dimension after TAVR.

A randomized clinical trial of omega-3 fatty acid and vitamin D supplementation on electrocardiographic risk profiles

Beneficial and adverse associations with arrhythmias have been reported for omega-3 fatty acids (omega-3 FA) and Vitamin D. The 12 lead electrocardiogram (ECG) contains quantitative measures reflecting diverse aspects of electrophysiology that might provide insights into mechanisms underlying these associations. In a pre-specified ancillary study of the VITaminD and omegA-3 (VITAL) trial, we examined the effect of 1 g of marine omega-3 FA per day, comprised of 460 mg eicosapentanoic acid and 380 mg of docosahexaenoic acid, and 2000 IU VitaminD3 per day on ECG characteristics associated with atrial and ventricular arrhythmias among individuals age 50 years or greater. A total of 911 study participants underwent ECGs at baseline and again at 2 years after the randomization. Individuals randomized to active omega-3 FA demonstrated significant net increase in PR-interval duration (p = 0.005) and P-wave duration (p = 0.03) as well significant net decrease in P-wave amplitude (p = 0.037) as compared to placebo. RMSSD increased to a greater extent in the omega-3 FA arm compared to placebo (p = 0.040). For Vitamin D3, the Cornell voltage increased to a lesser extent in the participants assigned to active treatment as compared to placebo (p = 0.044). There were no other significant differences in QRS, QTc, Cornell voltage or heart rate. Thus, randomized treatment with omega-3 FA supplements resulted in changes on the ECG that are potentially reflective of heightened vagal tone and/or slowing of intraatrial and AV conduction. Vitamin D3 supplementation resulted in modest reductions in progressive LV voltage suggestive of a potential antihypertrophic effect.Trial registration ClinicalTrials.gov Identifiers: NCT01169259, NCT02178410 (06/26/2010 and 06/30/2014).

Electrocardiographic markers of subclinical atrial fibrillation detected by implantable loop recorder: insights from the LOOP Study

AIMS

Insights into subclinical atrial fibrillation (AF) development are warranted to inform the strategies of screening and subsequent clinical management upon AF detection. Hence, this study sought to characterize the onset and progression of subclinical AF with respect to 12-lead electrocardiogram (ECG) parameters.

METHODS AND RESULTS

We included AF-naïve individuals aged 70-90 years with additional stroke risk factors who underwent implantable loop recorder (ILR) monitoring in the LOOP Study. Using data from daily ILR recordings and the computerized analysis of baseline ECG, we studied empirically selected ECG parameters for AF detection (≥6 min), cumulative AF burden, long-lasting AF (≥24 h), and AF progression. Of 1370 individuals included, 419 (30.6%) developed AF during follow-up, with a mean cumulative AF burden of 1.5% [95% CI: 1.2-1.8]. Several P-wave-related and ventricular ECG parameters were associated with new-onset AF and with cumulative AF burden in AF patients. P-wave duration (PWD), P-wave terminal force in Lead V1, and interatrial block (IAB) further demonstrated significant associations with long-lasting AF. Among AF patients, we observed an overall reduction in cumulative AF burden over time (IRR 0.70 [95% CI: 0.51-0.96]), whereas IAB was related to an increased risk of progression to AF ≥24 h (HR 1.86 [95% CI: 1.02-3.39]). Further spline analysis also revealed longer PWD to be associated with this progression in AF duration.

CONCLUSION

We identified several ECG parameters associated with new-onset subclinical AF detected by ILR. Especially PWD and IAB were robustly related to the onset and the burden of AF as well as progression over time.

Reduction in atrial and ventricular electrical heterogeneity following pulmonary vein isolation in patients with atrial fibrillation

BACKGROUND

Pulmonary vein isolation (PVI) modulates the intrinsic cardiac autonomic nervous system and reduces atrial fibrillation (AF) recurrence.

METHODS

In this retrospective analysis, we investigated the impact of PVI on ECG interlead P-wave, R-wave, and T-wave heterogeneity (PWH, RWH, TWH) in 45 patients in sinus rhythm undergoing clinically indicated PVI for AF. We measured PWH as a marker of atrial electrical dispersion and AF susceptibility and RWH and TWH as markers of ventricular arrhythmia risk along with standard ECG measures.

RESULTS

PVI acutely (16 ± 8.9 h) reduced PWH by 20.7% (from 31 ± 1.9 to 25 ± 1.6 µV, p < 0.001) and TWH by 27% (from 111 ± 7.8 to 81 ± 6.5 µV, p < 0.001). RWH was unchanged after PVI (p = 0.068). In a subgroup of 20 patients with longer follow-up (mean = 47 ± 3.7 days after PVI), PWH remained low (25 ± 1.7 µV, p = 0.01), but TWH partially returned to the pre-ablation level (to 93 ± 10.2, p = 0.16). In three individuals with early recurrence of atrial arrhythmia in the first 3 months after ablation, PWH increased acutely by 8.5%, while in patients without early recurrence, PWH decreased acutely by 22.3% (p = 0.048). PWH was superior to other contemporary P-wave metrics including P-wave axis, dispersion, and duration in predicting early AF recurrence.

CONCLUSION

The rapid time course of decreased PWH and TWH after PVI suggests a beneficial influence likely mediated via ablation of the intrinsic cardiac nervous system. Acute responses of PWH and TWH to PVI suggest a favorable dual effect on atrial and ventricular electrical stability and could be used to track individual patients' electrical heterogeneity profile.

Cryptogenic stroke as a working diagnosis: the need for an early and comprehensive diagnostic work-up

In the Nordic Atrial Fibrillation and Stroke (NOR-FIB) study, the causes of ischemic stroke were identified in 43% of cryptogenic stroke patients monitored with implantable cardiac monitor (ICM), but one-third of these patients had non-cardioembolic causes. These results suggest the need for an early and comprehensive diagnostic work-up before inserting an ICM.

A predictive model of response to metoprolol in children and adolescents with postural tachycardia syndrome

BACKGROUND

The present work was designed to explore whether electrocardiogram (ECG) index-based models could predict the effectiveness of metoprolol therapy in pediatric patients with postural tachycardia syndrome (POTS).

METHODS

This study consisted of a training set and an external validation set. Children and adolescents with POTS who were given metoprolol treatment were enrolled, and after follow-up, they were grouped into non-responders and responders depending on the efficacy of metoprolol. The difference in pre-treatment baseline ECG indicators was analyzed between the two groups in the training set. Binary logistic regression analysis was further conducted on the association between significantly different baseline variables and therapeutic efficacy. Nomogram models were established to predict therapeutic response to metoprolol. The receiver-operating characteristic curve (ROC), calibration, and internal validation were used to evaluate the prediction model. The predictive ability of the model was validated in the external validation set.

RESULTS

Of the 95 enrolled patients, 65 responded to metoprolol treatment, and 30 failed to respond. In the responders, the maximum value of the P wave after correction (Pcmax), P wave dispersion (Pd), Pd after correction (Pcd), QT interval dispersion (QTd), QTd after correction (QTcd), maximum T-peak-to-T-end interval (Tpemax), and T-peak-to-T-end interval dispersion (Tped) were prolonged (all P < 0.01), and the P wave amplitude was increased (P < 0.05) compared with those of the non-responders. In contrast, the minimum value of the P wave duration after correction (Pcmin), the minimum value of the QT interval after correction (QTcmin), and the minimum T-peak-to-T-end interval (Tpemin) in the responders were shorter (P < 0.01, < 0.01 and < 0.01, respectively) than those in the non-responders. The above indicators were screened based on the clinical significance and multicollinearity analysis to construct a binary logistic regression. As a result, pre-treatment Pcmax, QTcmin, and Tped were identified as significantly associated factors that could be combined to provide an accurate prediction of the therapeutic response to metoprolol among the study subjects, yielding good discrimination [area under curve (AUC) = 0.970, 95% confidence interval (CI) 0.942-0.998] with a predictive sensitivity of 93.8%, specificity of 90.0%, good calibration, and corrected C-index of 0.961. In addition, the calibration curve and standard curve had a good fit. The accuracy of internal validation with bootstrap repeated sampling was 0.902. In contrast, the kappa value was 0.769, indicating satisfactory agreement between the predictive model and the results from the actual observations. In the external validation set, the AUC for the prediction model was 0.895, and the sensitivity and specificity were 90.9% and 95.0%, respectively.

CONCLUSIONS

A high-precision predictive model was successfully developed and externally validated. It had an excellent predictive value of the therapeutic effect of metoprolol on POTS among children and adolescents.

Stacked machine learning models to classify atrial disorders based on clinical ECG features: a method to predict early atrial fibrillation

OBJECTIVES

Atrial Tachycardia (AT) and Left Atrial Enlargement (LAE) are atrial diseases that are significant precursors to Atrial Fibrillation (AF). There are ML models for ECG classification; clinical features-based classification is required. The suggested work aims to create stacked ML models that categorize Sinus Rhythm (SR), Sinus Tachycardia (ST), AT, and LAE signals based on clinical parameters for AF prognosis.

METHODS

The classification was based on thirteen clinical parameters, such as amplitude, time domain ECG aspects, and P-Wave Indices (PWI), such as the ratio of P-wave length and amplitude ((P (ms)/P (µV)), P-wave area (µV*ms), and P-wave terminal force (PTFV1(µV*ms). Apart from classifying the ECG signals, the stacked ML models prioritized the clinical features using a pie formula-based technique.

RESULTS

The Stack 1 model achieves 99% accuracy, sensitivity, precision, and F1 score, while the Stack 2 model achieves 91%, 91%, 94%, and 92% for identifying SR, ST, LAE, and AT, respectively. Both stack models obtained a computational time of 0.06 seconds. PTFV1 (µV*ms), P (ms)/P (µV)), and P-wave area (µV*ms) were ranked as crucial clinical features.

CONCLUSION

Clinical feature-based stacking ML models may help doctors obtain insight into important clinical ECG aspects for early AF prediction.

Analysis of the amplified p-wave enables identification of patients with atrial fibrillation during sinus rhythm

Aim

This study sought to develop and validate diagnostic models to identify individuals with atrial fibrillation (AF) using amplified sinus-p-wave analysis.

Methods

A total of 1,492 patients (491 healthy controls, 499 with paroxysmal AF and 502 with persistent AF) underwent digital 12-lead-ECG recording during sinus rhythm. The patient cohort was divided into training and validation set in a 3:2 ratio. P-wave indices (PWI) including duration of standard p-wave (standard PWD; scale at 10 mm/mV, sweep speed at 25 mm/s) and amplified sinus-p-wave (APWD, scale at 60-120 mm/mV, sweep speed at 100 mm/s) and advanced inter-atrial block (aIAB) along with other clinical parameters were used to develop diagnostic models using logistic regression. Each model was developed from the training set and further tested in both training and validation sets for its diagnostic performance in identifying individuals with AF.

Results

Compared to standard PWD (Reference model), which achieved an AUC of 0.637 and 0.632, for training and validation set, respectively, APWD (Basic model) importantly improved the accuracy to identify individuals with AF (AUC = 0.86 and 0.866). The PWI-based model combining APWD, aIAB and body surface area (BSA) further improved the diagnostic performance for AF (AUC = 0.892 and 0.885). The integrated model, which further combined left atrial diameter (LAD) with parameters of the PWI-based model, achieved optimal diagnostic performance (AUC = 0.916 and 0.902).

Conclusion

Analysis of amplified p-wave during sinus rhythm allows identification of individuals with atrial fibrillation.

Circulating Levels of Ferritin, RDW, PTLs as Predictive Biomarkers of Postoperative Atrial Fibrillation Risk after Cardiac Surgery in Extracorporeal Circulation

Postoperative atrial fibrillation (POAF) is the most common arrhythmia after cardiac surgery in conventional extracorporeal circulation (CECC), with an incidence of 15-50%. The POAF pathophysiology is not known, and no blood biomarkers exist. However, an association between increased ferritin levels and increased AF risk, has been demonstrated. Based on such evidence, here, we evaluated the effectiveness of ferritin and other haematological parameters as POAF risk biomarkers in patients subjected to cardiac surgery. We enrolled 105 patients (mean age = 70.1 ± 7.1 years; 70 men and 35 females) with diverse heart pathologies and who were subjected to cardiothoracic surgery. Their blood samples were collected and used to determine hematological parameters. Electrocardiographic and echocardiographic parameters were also evaluated. The data obtained demonstrated significantly higher levels of serum ferritin, red cell distribution width (RDW), and platelets (PLTs) in POAF patients. However, the serum ferritin resulted to be the independent factor associated with the onset POAF risk. Thus, we detected the ferritin cut-off value, which, when ≥148.5 ng/mL, identifies the subjects at the highest POAF risk, and with abnormal ECG atrial parameters, such as PW indices, and altered structural heart disease variables. Serum ferritin, RDW, and PTLs represent predictive biomarkers of POAF after cardiothoracic surgery in CECC; particularly, serum ferritin combined with anormal PW indices and structural heart disease variables can represent an optimal tool for predicting not only POAF, but also the eventual stroke onset.

Left Atrial Cardiomyopathy - A Challenging Diagnosis

Left atrial cardiomyopathy (LACM) has been an ongoing focus of research for several years. There is evidence that LACM is responsible for atrial fibrillation and embolic strokes of undetermined sources. Therefore, the correct diagnosis of LACM is of clinical importance. Various techniques, including electrocardiography, echocardiography, cardiac magnetic resonance imaging, computed tomography, electroanatomic mapping, genetic testing, and biomarkers, can both identify and quantify structural, mechanical as well as electrical dysfunction in the atria. However, the question arises whether these techniques can reliably diagnose LACM. Because of its heterogeneity, clinical diagnosis is challenging. To date, there are no recommendations for standardized diagnosis of suspected LACM. However, standardization could help to classify LACM more precisely and derive therapeutic directions to improve individual patient management. In addition, uniform diagnostic criteria for LACM could be important for future studies. Combining several parameters and relating them seems beneficial to approach the diagnosis of LACM. This review provides an overview of the current evidence regarding the diagnosis of LACM, in which several potential parameters are discussed and, consequently, a proposal for a diagnostic algorithm is presented.

Markers of Atrial Cardiopathy in Severe Embolic Strokes of Undetermined Source

Background and Purpose

The current definition of embolic strokes of undetermined source (ESUS) seems to be too broad, including strokes due to heterogeneous mechanisms, such as atrial cardiopathy and other occult cardiac conditions, aortic arch plaques, and non-stenosing atherosclerosis, that can be differently associated with clinical stroke severity at the time of presentation. The aim of our study was to assess the possible association between neurological deficit severity and presence of markers of atrial cardiopathy in ESUS.

Methods

We retrospectively reviewed the medical records of a cohort of 226 ESUS patients (105 M, 121 F), that were divided into two groups according to the severity of neurological deficit (99 mild strokes with NIHSS ≤ 5 and 127 severe strokes with NIHSS >5). The following indices of atrial cardiopathy were evaluated: P wave dispersion, P wave max, P wave min, P wave mean, P wave index, P wave axis, left atrial size.

Results

Patients with severe ESUS were significantly older (74 ± 12 vs. 67 ± 14 years, P < 0.001) and female sex was prevalent (67 vs. 36%, P > 0.001); they had higher values of P-wave-dispersion (51 ± 14 vs. 46 ± 13, P = 0.01), P-wave-max (131 ± 20 vs. 125 ± 15 ms, P = 0.01), P-wave-index (16 ± 5 vs. 15 ± 5 ms, P = 0.01), left atrial size (20 ± 6 vs. 18 ± 4 cm², P = 0.01), left atrial volume index (31 ± 14 vs. 27 ± 11 ml/m², P = 0.04), in comparison with mild ESUS. An abnormal P wave axis was detected more frequently in severe ESUS (21 vs. 9%, P = 0.01). Furthermore, multivariate logistic regression showed that age (OR = 1.21 for each 5-year increase, 95% CI 1.09–1.35), sex (OR = 3.24 for female sex, 95% CI 1.82–5.76) and PWD (OR = 1.32 for each 10-ms increase, 95% CI 1.07–1.64) were the best subset of associated variables for severe ESUS.

Conclusions

Our findings shed light on specific clinical characteristics of severe ESUS including the presence of atrial cardiopathy that could play a pathogenic role in this subgroup of patients. Searching for atrial fibrillation in these patients is especially important to perform the most appropriate therapy.