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Background P‐wave parameters, readily obtainable from standard 12‐lead ECGs, have been associated with atrial fibrillation (AF), ischemic stroke, and other cardiovascular conditions. Left atrial cardiomyopathy (AtCM), characterized by atrial fibrosis and functional impairment, is considered a central substrate in the development of AF and embolic stroke of undetermined source. This study examines the relationship between P‐wave parameters and left atrial hemodynamics and evaluates their potential diagnostic utility in identifying AtCM. Methods We conducted a monocentric, prospective study in hospitalized patients. Inclusion criteria were sinus rhythm and age ≥ 18 years. P‐wave parameters were assessed in conjunction with echocardiographic measures of left atrial function. Statistical analyses compared patients with and without pathological P‐wave parameters. Results A total of 416 patients were included. Pathological P‐wave parameters were highly prevalent, with 55% of patients exhibiting ≥ 3 abnormalities. Advanced interatrial block (IAB) showed a robust association with impaired left atrial hemodynamics, whereas other parameters, such as PTFV1, demonstrated only weak correlations. Patients with advanced IAB exhibited significant alterations in left atrial size, function, and NT‐proBNP levels. Conclusions Advanced IAB emerged as the most reliable P‐wave parameter for detecting left atrial dysfunction in AtCM, whereas other P‐wave indices, including PTFV1, were less informative. These findings highlight the diagnostic value of advanced IAB in identifying AtCM, particularly in patients with embolic stroke of undetermined source, and emphasize the need for more refined diagnostic criteria in future investigations. In the present study, the validity of seven established P‐wave parameters in relation to left atrial hemodynamics was investigated. Our study suggests that advanced IAB is the strongest indicator of altered left atrial hemodynamics and, thus, AtCM.

Background The aim of this study was to examine the prevalence of abnormal P‐wave parameters in patients with thrombus and/or spontaneous echo contrast (SEC) in the left atrial appendage (LAA), and to identify P‐wave parameters particularly associated with thrombus and SEC formation. Hypothesis We presume a significant relationship of P‐wave parameters with thrombi and SEC. Methods All patients in whom a thrombus or SEC was detected in the LAA on transoesophageal echocardiography were included in this study. Patients at risk (CHA2DS2‐VASc Score ≥3) and routine transoesophageal echocardiography to exclude thrombi served as the control group. A detailed ECG analysis was performed. Results Of a total of 4062 transoesophageal echocardiographies, thrombi and SEC were detected in 302 patients (7.4%). Of these patients, 27 (8.9%) presented with sinus rhythm. The control group included 79 patients. There was no difference in mean CHA2DS2‐VASc score in the two groups (p = .182). A high prevalence of abnormal P‐wave parameters was detected in patients with thrombus/SEC. Indicators for the presence of thrombi or SEC in the LAA were P‐wave duration >118 ms (Odds ratio (OR) 3.418, Confidence interval (CI) 1.522–7.674, p < .001), P‐wave dispersion >40 ms (OR 2.521, CI 1.390–4.571, p < .001) and advanced interatrial block (OR 1.431, CI 1.033–1.984, p = .005). Conclusion Our study revealed that several P‐wave parameters are associated with thrombi and SEC in the LAA. The results may help identify patients who are at particularly high risk for thromboembolic events (e.g., in patients with embolic stroke of undetermined source). Several P‐wave parameters are associated with atrial fibrillation and with ischemic stroke. However, it is uncertain whether P‐wave parameters are associated with thrombus or spontaneous echo contrast in the left atrial appendage. Our study demonstrated a significant association of P‐wave duration, P‐wave dispersion, and advanced interatrial block with thrombus or spontaneous echo contrast in the left atrial appendage. IAB, interatrial block; PTFV1, P‐wave terminal force in V1.

Objectives The objective of this study is to analyze the relationship between atypical ECG patterns in typical atrial flutter (AFL) and cardiac structure, as well as sinus rhythm P-wave parameters. Materials and methods 389 consecutive patients diagnosed with typical AFL who were treated at our center were included. The morphology of the flutter wave was assessed in each lead. Counterclockwise AFL could be classified into three typical groups and two kinds of atypical groups based on the flutter ECG patterns. Sinus rhythm P-wave parameters, including PtfV1 ( P Wave Terminal Force of V1 ), P-wave area, axis, and interatrial block (IAB), etc. were measured manually. The analysis focused on examining the correlation between flutter wave and atrial structure characteristics, as well as the influence of prior cardiac surgery. Furthermore, an analysis was conducted on the correlation between P-wave parameters and F-wave morphology. Results The size of the atrium and previous cardiac surgery have an impact on the AFL ECG pattern. P-wave amplitude in lead II ( p  < 0.0001), lead III ( p  < 0.0001), V1 terminal interval ( p  = 0.01), and P-wave area ( p  < 0.0001) exhibited significant differences between the typical and atypical groups. Furthermore, the SR P-wave axis and the presence of IAB may also be associated with an atypical AFL pattern. Conclusion Typical AFL may exhibit various ECG patterns and two new patterns were found. SR P-wave, such as IAB and P wave amplitude, duration, etc. has the potential to predict atypical ECG patterns in typical AFL. The size of the right atrium significantly influence the characteristic ECG patterns observed in typical AFL.

Highlights Abnormal changes in P-wave parameters indicative of atrial electrical remodeling often manifest earlier than changes in other indicators reflecting atrial structural remodeling in paroxysmal atrial fibrillation. Preoperative absolute values of Maximum P Wave Duration, P Wave Dispersion, and P Wave Terminal Force of V1, as well as postoperative absolute values of Maximum P Wave Duration, P Wave Duration, P Wave Dispersion, P Wave Terminal Force of V1, and P Wave Area, demonstrate strong predictive value for recurrence risk of paroxysmal atrial fibrillation after Catheter Ablation. The nomogram model based on P-wave parameters before and after catheter ablation exhibits notably strong predictive performance and offers significant clinical benefits. Objective The objective of this study is to assess the predictive utility of perioperative P-wave parameters in patients with paroxysmal atrial fibrillation (PAF) undergoing catheter ablation, and to develop a predictive model using these parameters. Methods A total of 213 patients with PAF undergoing catheter ablation were retrospectively analyzed. P-wave parameters were measured within 3 days preoperatively and on the day postoperatively to determine their predictive significance for postoperative PAF recurrence. Results Post-ablation, PAF did not recur in 168 patients, while 45 experienced recurrence. Significant differences were observed in preoperative P-wave parameters as Maximum P Wave Duration(Pmax), absolute value of P Wave Terminal Force of V1 (PtfV1) and P Wave Dispersion(Pd), postoperative P-wave parameters as P Wave Duration (PWD II, III, aVF ), Pmax, P Wave Area(P-area), absolute value of PtfV1 and Pd, and changes in perioperative P-wave parameters (Delta-Pmax, Delta-PtfV1 absolute value, Delta-Pd, Delta-PWD II, III, aVF ). Univariate logistic regression, receiver operating characteristic (ROC) curve analysis, and hazard ratio assessment identified predictive indicators for postoperative recurrence, including Pmax, PtfV1 absolute value, Pd, post-P area, post-PWD II, III, aVF and Delta-pwd II, III, aVF ). A personalized nomogram model based on these P-wave parameters was developed. Calibration curve assessment demonstrated that the predictive performance of the nomogram for PAF recurrence following catheter ablation closely matched actual observed outcomes. ROC curve analysis indicated a sensitivity of 89.3% for the model, and decision curve analysis confirmed its significantly favorable predictive use and clinical benefits. Conclusions P-wave parameters like PWD Ш , PWDaVF, Pmax, Pd, and PtfV1 serve as predictors of PAF recurrence following catheter ablation. The nomogram model constructed using these P-wave parameters demonstrates robust predictive performance.

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.

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.

Numerous studies have confirmed a significant association between obstructive sleep apnea hypopnea syndrome (OSAHS) and both the increased prevalence and incidence of atrial fibrillation (AF). This study advanced the endpoint event to complex atrial arrhythmias, a group that potentially develops into AF. It innovatively used non-invasive P-wave parameters (PWPs) as predictive indicators for the occurrence of complex atrial arrhythmias in OSAHS, thereby achieving early identification. A retrospective analysis was performed on the medical records of patients presenting with sleep disorders who were admitted to the Fifth Affiliated Hospital of Sun Yat-sen University between June 2019 and June 2022. Based on their apnea-hypopnea index (AHI), patients were categorized into control, mild, moderate, and severe OSAHS groups. Clinical characteristics, PWPs, occurrences of atrial arrhythmias, and echocardiographic findings were collected for analysis. Using the Kleiger grading method, atrial arrhythmias were classified into simple and complex groups. Analysis of variance (ANOVA) was employed to examine differences among the groups, while independent sample -tests were used for pairwise comparisons. Logistic regression analysis was applied to identify independent risk factors contributing to complex atrial arrhythmias, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of PWPs. Patients with severe OSAHS exhibited significantly prolonged P-wave duration (PWD) and elevated Macruz Index compared to those with mild or moderate OSAHS (  < 0.01), while the P terminal force in lead V1 (PtfV1) was notably higher in moderate and severe groups relative to the mild and control groups (  < 0.01). Logistic regression analysis identified PtfV1 (odds ratio [OR] = 1.61) and the Macruz Index (OR = 2.95) as independent predictors of complex atrial arrhythmias. Furthermore, ROC curve analysis demonstrated that both PtfV1 and the Macruz Index had moderate predictive value, with area under the curve (AUC) values of 0.701 and 0.681, respectively, for identifying complex atrial arrhythmias. PWPs, especially the PtfV1 and Macruz index, provide a powerful non-invasive predictor of atrial arrhythmia risk in patients with OSAHS.

Atrial fibrillation is the most common arrhythmia encountered in clinical practice affecting both patients’ survival and well-being. Apart from aging, many cardiovascular risk factors may cause structural remodeling of the atrial myocardium leading to atrial fibrillation development. Structural remodelling refers to the development of atrial fibrosis, as well as to alterations in atrial size and cellular ultrastructure. The latter includes myolysis, the development of glycogen accumulation, altered Connexin expression, subcellular changes, and sinus rhythm alterations. The structural remodeling of the atrial myocardium is commonly associated with the presence of interatrial block. On the other hand, prolongation of the interatrial conduction time is encountered when atrial pressure is acutely increased. Electrical correlates of conduction disturbances include alterations in P wave parameters, such as partial or advanced interatrial block, alterations in P wave axis, voltage, area, morphology, or abnormal electrophysiological characteristics, such as alterations in bipolar or unipolar voltage mapping, electrogram fractionation, endo-epicardial asynchrony of the atrial wall, or slower cardiac conduction velocity. Functional correlates of conduction disturbances may incorporate alterations in left atrial diameter, volume, or strain. Echocardiography or cardiac magnetic resonance imaging (MRI) is commonly used to assess these parameters. Finally, the echocardiography-derived total atrial conduction time (PA-TDI duration) may reflect both atrial electrical and structural alterations.

The rapid and accurate prediction of earthquake Strong-Shaking Zone (SSZ) is crucial for issuing precise early warnings to regions at high risk of strong ground shaking. Generally, the SSZ is derived from the real-time spatial distribution of observed ground motions. However, during the initial stages of large earthquakes, the SSZ is often underestimated and provide alerts without enough lead-time (the time interval between the alert declaration and the S-wave arrival to the target area). In this study, we propose an innovative approach termed Near-epicenter-based Partial Matching Crossover. Leveraging the characteristic that reliable magnitude estimates for large earthquakes are available earlier than accurate predictions of the peak ground velocity (PGV) distribution, this approach utilizes near-epicenter station data to rapidly estimate the SSZ. It achieves this by matching a segment of the fault, defined by a predetermined length, with the predicted PGV map within a 120 km radius centered at the epicenter. Application of our method to strong motion data from China, Japan and Turkey demonstrates its efficacy in quickly anticipating the post-earthquake intensity distributions for large earthquakes. Specifically, it offers a lead time of 5 s or more for 51.5% (39,354 km2), 43.3% (5772 km2), 31%(47,107 km2) and 75.3% (81,966 km2) of the IMM = V region during the M 8 Wenchuan earthquake, the M 7.3 Kumamoto earthquake, the M 7.8 Syria earthquake and M 7.6 Turkey earthquake, respectively. The presented approach introduces a novel methodology to extend the lead time for earthquake early warnings.

To construct a risk prediction nomogram combining P-wave electrocardiographic indicators with serum brain natriuretic peptide (BNP) levels for predicting recurrence risk after radiofrequency ablation (RFA) for atrial fibrillation (AF), and to propose follow-up care strategies, thereby providing a theoretical basis for clinical prevention of early AF recurrence after RFA. A retrospective study was conducted on 200 AF patients who underwent radiofrequency ablation at our hospital between March 2023 and December 2024. All patients were confirmed to be in sinus rhythm at the time of preoperative electrocardiographic recording. Based on recurrence status at 3-month follow-up, patients were divided into recurrence (  = 62) and non-recurrence (  = 138) groups. Recurrence was assessed through a standardized rhythm monitoring protocol including scheduled electrocardiograms, 24 h Holter monitoring, and symptom-driven event recordings. The last enrolled patient completed follow-up on March 31, 2025. Comparisons of AF type, left atrial diameter (LAD), P-wave duration (PWD), maximum P-wave duration (Pmax), P-wave dispersion (Pd), and BNP levels between groups showed statistically significant differences (  < 0.05). Logistic regression analysis confirmed that AF type, LAD, PWD, Pmax, Pd, and BNP were independent risk factors for post-AF radiofrequency ablation recurrence (OR > 1,  < 0.05). A risk prediction nomogram model was constructed. In the derivation cohort, the area under the receiver operating characteristic curve (AUC) was 0.959 (95% CI: 0.925-0.993). Apparent calibration was acceptable (Hosmer-Lemeshow test  = 0.726). Risk stratification analysis identified a total nomogram score of 85 points as an optimal threshold to distinguish low-risk from medium-to-high-risk patients. Formal internal validation was not performed. The derivation-cohort risk prediction nomogram based on P-wave ECG indicators combined with serum BNP demonstrates potential value for estimating early recurrence after AF radiofrequency ablation. Clinicians should interpret the model cautiously and develop personalized follow-up care strategies based on individual risk profiles to reduce recurrence risk and improve patient quality of life.