bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of amplified P-wave analysis to artificial intelligence-derived analysis for diagnosis of atrial cardiomyopathy and outcome prediction following pvi for persistent atrial fibrillation
Authors: Jadidi A , Pilia N , Huang T , Mueller-Edenborn B , Allgeier J , Nairn D , Loewe A , Westermann D , Arentz T 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Introduction
Left atrial cardiomyopathy (ACM) is invasively diagnosed by presence of low voltage substrate (LVS) in electro-anatomical mapping. ACM is associated with high (50%) AF recurrence rates after PVI, but also with increased risk for de-novo AF and ischemic stroke.

Aims
We establish and compare ACM-diagnosis based on 12-lead-ECG analysis, using (A) digital amplified p-wave analysis during SR versus (B) a neural network trained to diagnose ACM using automatically determined sinus-p-wave features (duration, morphology) in 12-lead-ECG as inputs.

Methods
Left atrial (LA) voltage mapping was acquired during SR in 270 AF (50% paroxysmal; 43% female; age: 64+/-11years) prior to PVI. ACM was defined as presence of left atrial LVS&lt;0.5mV at &gt;2cm2 during SR, and was detected in 95/270 (35.2%) of patients. P-wave-analysis was assessed for outcome prediction in a prospective cohort of persistent AF patients undergoing rhythm monitoring using 7-day Holter at 6 and 12 months post PVI-only approach.

Results
The duration of amplified sinus-p-wave (APWD) &gt;151ms (left top panel) enabled to diagnose ACM with an AUC 0.87 (sensitivity: 78% and specificity: 76%, left bottom panel). The accuracy of the AI-neural-network-derived ECG-analysis (using automatically determined APWD and p-morphology criteria) for ACM diagnosis was: AUC 0.85, sensitivity 74%, specificity 78%, accuracy: 77% (see right panel top and bottom). Application of AI-derived ACM-diagnosis on a prospective cohort of persistent AF patients undergoing PVI-only approach (n=58) enabled arrhythmia outcome prediction: Patients with vs. without ACM (based on AI-derived p-wave-analysis) had significantly higher arrhythmia recurrences at 12 months following PVI (46% vs. 23%, p=0.017).

Conclusion
Both the measurement of the APWD and the automatic neural network-based p-wave-analysis enable diagnosis of individuals with left atrial cardiomyopathy with high accuracy in a large cohort of patients with paroxysmal and persistent AF. Diagnosis of ACM based on automatic neural-network-based P-wave analysis enables identification of patients at high risk for arrhythmia recurrence post PVI-only ablation approach.
Analysis of the Amplified P-Wave or Artificial Intelligence-Derived P-wave-Analysis Enable Identification of Patients with Atrial Fibrillation during Sinus Rhythm
Authors: Jadidi A , Huang T , Pilia N , Mueller-Edenborn B , Eichenlaub M , Allgeier J , Trenk D , Westermann D , Arentz T 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Introduction / Aims
This study sought to develop and validate diagnostic models to identify individuals with atrial fibrillation (AF) using amplified p-wave analysis or neural-network-trained p-wave-analysis during sinus rhythm (SR).

Methods
1492 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 including duration of standard p-wave (standard PWD; 10mm/mV, 25mm/sec, see ECG in the left panel), amplified digital p-wave (APWD, 60-100mm/mV, 175mm/sec; see ECG in the middle panel) and advanced inter-atrial block (aIAB) along with the parameters body surface area (BSA) and LA diameter (LAD) 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. A neural-network was trained to identify the p-wave and its features (duration, morphology) to differentiate between individuals with known versus those without AF.

Results
Compared to standard PWD (Reference model, AUC=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 ECG-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 ECG-based model, achieved the highest diagnostic performance (AUC=0.916 and 0.902). Notably, the neural network-based p-wave-analysis identified AF patients with high accuracy during sinus rhythm (AUC: 0.85; sensitivity: 77%; specificity: 78%).

Conclusions
Both, the analysis of amplified p-wave and a neural-network-based automatic p-wave analysis during sinus rhythm allow identification of individuals with atrial fibrillation. The current diagnostic models provide a new basis for identifying individuals at high risk for AF, who would most benefit from AF screening.
Artificial intelligence-enhanced electrocardiography for predicting severity prognosis in patients with COVID-19
Authors: Baek Y , Jo Y , Lee D H , Lee S C , Choi W I , Kim D H 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
There were no artificial intelligence (AI) tools to predict the severity and prognosis of patients hospitalized with COVID-19 using initial electrocardiography (ECG).

Purpose
We assessed whether AI using 12-lead ECG could assist in the early determination of COVID-19 severity and predict prognosis of hospitalized patients.

Methods
Patients diagnosed with COVID-19 via polymerase chain reaction and admitted to our institution during February 2020–October 2021 were enrolled. We identified 642 patients (mean age, 56±19 years; 41.7% male) who underwent 12-lead ECGs within 2 days of admission for COVID-19. Patients were divided according to severity: mild-to-moderate illness (oxygen or low-flow oxygen therapy not required) and severe-to-critical illness (required high-flow oxygen, invasive mechanical ventilation, or extra corporeal membrane oxygenation).

Results
Severe-to-critical illness occurred in 243 (37.8%) patients, including 23 (3.6%) in-hospital mortalities. Experimental results using our developed AI enhanced ECG demonstrated better outcomes for mild-to-moderate illness based on an area under the curve (AUC), sensitivity, specificity, and F1 score of 0.71, 0.95, 0.70, and 0.81, respectively. The AUC for detecting severe-to-critical illness was 0.71 (95% confidence interval [CI]: 0.58– 0.82; sensitivity: 0.70; specificity: 0.35; F1 score: 0.35; and overall accuracy: 0.70). When analyzing individuals without COVID-19, the AI algorithm for identifying COVID-19 showed an AUC of 0.85 (95% CI: 0.82–0.88; sensitivity: 0.60; specificity: 0.84; F1 score: 0.70; overall accuracy: 0.85).

Conclusion
AI-enhanced ECG could reasonably predict severity in patients hospitalized for COVID-19, suggesting that AI-ECG assists in the early determination of COVID-19 severity, helping physicians improve patient management.
sST2 association with atrial fibrillation development in patients with acute myocardial infarction with ST elevation
Authors: Rodionova I , Kutya I N N A , Hilova Y , Kopytsya M Y K O L A , Samburg Y A N A , Shelest B O R Y S 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
Atrial fibrillation (AF) is considered a significant myocardial infarction complication. Recent investigations found that soluble suppression of tumorigenicity 2 (sST2) is an important player in ST-segment elevation myocardial infarction (STEMI) development. However, sST2 role in the prognosis for atrial fibrillations in STEMI patients remains not fully clear.

Purpose
The study aimed to investigate the sST2 role in the prognosis of atrial fibrillations development in STEMI patients.

Methods
193 STEMI patients were enrolled into the study. 101 males, 92 females, with average age of 61.23±7.45 years. The follow-up period was 6 month. Plasma sST2 levels were measured at admission by ELISA.

Results
Plasma sST2 concentrations in patients with developed AF were 47.56 IQR [29.87; 61.33] ng / mL, which was significantly higher than in those patients without developed AF 39.67 IQR [22.16; 49.77] ng / mL, p &lt; 0.01.Logistic regression analysis indicated that increased sST2 as a significant predictor for AF development (OR = 1.121, 95% CI: 1.055–1.971, p &lt; 0.01). It remained significant even after adjustment for age and sex (OR = 1.023, 95% CI: 1.009–1.865, p &lt; 0.01). ROC analysis showed that sST2 cut-off level for AF development was 49.12 ng/ml with a sensitivity of 77.8% and specificity of 73.5%, AUC 0.811; 95 % CI 0.633-0.873; p &lt;0.001

Conclusion
The elevated sST2 plasma level is associated with an increased risk of atrial fibrillation in STEMI patients. Our findings suggest new approaches for better management of high-risk STEMI patients.
Cardiac digital twins of the adult population: linking electrophysiological functions to anatomy
Authors: Qian S , Ugurlu D , Fairweather E , Strocchi M , Dal Toso L , Deng Y , Young A , Bishop M , Lamata P , Niederer S 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This project is supported by the Wellcome Trust and EPSRC Centre for Medical Engineering.

Background
QRS duration derived from 12-lead ECGs provides an estimate of the ventricular depolarization time and is an important metric to assess cardiac function. The QRS duration is determined in part by the combination of heart size and conduction velocity (CV). Differences in QRS duration in terms of gender, body mass index (BMI) and age have been well-documented, however, the relative impact of concurrent changes in heart size and CV on QRS duration is poorly understood. Cardiac digital twins, as in-silico replicas, provide a non-invasive physics and physiology-constrained framework to separate the impact of CV and heart anatomy on the QRS duration across populations.

Purpose
This study aims to identify the impact of CV and heart size on differences in QRS duration and quantify their difference in the general population in different groups of gender, BMI and age.

Methods
Patient-specific biventricular models (n=400) were constructed using long- and short-axis cardiac magnetic resonance (CMR) images from patients without self-reported cardiovascular diseases in the UK Biobank. Cardiac electrophysiology was simulated using a physiological-detailed model that includes fiber orientation, anisotropic conductivity, the His-Purkinje system activation, and fast endocardial conductivity[1]. 12-lead ECGs were reconstructed from the simulations and the QRS duration was computed based on corresponding vectorcardiogram (VCG) reconstructed from ECG data [2]. We calibrated patient-specific CVs to match the clinically measured QRS duration in ECGs at rest and then compare the heart size, QRS duration and estimated CVs for different patient groups.

Results
QRS duration was approx. 7% longer in males than females (median: 90ms vs 84ms, P&lt;0.001). Consistent with a longer QRS duration in males had larger hearts (male: 165.5 mL vs 123 mL, P&lt;0.001), while the median CVs were the same between genders (both: 0.594 m/s). QRS duration was longer for obese (BMI≥30) and overweight group compared to healthy (BMI&lt;25) groups (88ms and 86 ms vs 84 ms, P=0.05 and 0.3). Again, the change in QRS duration with BMI was reflected with a corresponding increase in heart size (healthy: 127 mL, overweight: 147.6 mL, obese:160 mL), while CV remained unchanged (healthy: 0.58 m/s vs overweight and obese: 0.594 m/s, P=0.051 and 0.32). There was no significant difference in QRS duration, CV or myocardial volume for different age groups (medians: 86-88 ms and 0.573-0.594 m/s and 138.7-143 mL).

Conclusions
QRS duration is shorter in females and individuals with healthy weights. Most of the change in QRS duration can be explained by heart size, with the estimated CV remaining consistent across groups.
Evidence of cytokine activation in patients with post-acute COVID-19 syndrome with- and without postural orthostatic tachycardia syndrome
Authors: Fredengren E , Mahdi A , Fedorowski A , Brodin P , Nygren-Bonnier M , Runold M , Bruchfeld J , Nickander J , Desta L , Pernow J , Stahlberg M 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Swedish Research Council
Swedish Heart- and Lungfoundation

Introduction
Post-acute COVID-19 syndrome (PACS) affects approximately 10% of non-hospitalized COVID-19 patients with mild primary infection and constitutes an increasing burden for society and healthcare systems. We have previously reported that a proportion of PACS patients develop postural orthostatic tachycardia syndrome (POTS). The pathophysiological mechanisms behind PACS and associated POTS remain largely unknown but cytokine activation and inflammation have been proposed.

Purpose
To test the hypothesis that PACS and POTS-specific phenotype are associated with cytokine activation.

Methods
We recruited 20 patients with PACS and POTS verified by head-up TILT test (95% female, 39±11 years, 18±3 months after acute SARS-CoV-2 infection) and 22 patients with PACS without POTS (100% female, 44±11years, 19±3 months after acute SARS-CoV-2 infection). Age- and sex matched healthy volunteers (n=21; 95% female, 43±6 years) without- (n=16) and with (n=5) a history of SARS-Cov-2 infection but without symptoms served as control group. Peripheral blood samples were collected and analyzed for concentrations of 45 cytokines and inflammatory markers using Proximity Extension Assay. Protein-protein interactions and signaling pathway analysis were assessed using String database, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO).

Results
Several cytokines and inflammatory biomarkers were overexpressed in patients with PACS compared to healthy controls irrespective of the presence of POTS (Figure 1). Protein-protein interaction analysis revealed a cluster including IL-7, CXCL12, CXCL11, CCL8 and CCL13. Cytokine-receptor activation, viral protein – cytokine receptor interaction and chemokine signaling were the most significantly upregulated KEGG pathways. Cytokine-mediated signaling, and cell- and leukocyte migration and chemotaxis were the most significantly upregulated GO biological processes.

Conclusion
PACS is associated with increased levels of circulating cytokines regardless of concomitant POTS up to 18 months after a mild primary SARS-CoV-2 infection. This suggests that PACS-associated POTS exist on a background of cytokine activation but other specific pathophysiological mechanisms for PACS induced POTS needs to be established. Whether the cytokine profile of PACS is associated with persistent viral load or prolonged activation of the innate immune system and chronic inflammation, constituting a potential treatment target should be explored in future studies.
Added value of 12-lead 24-hour ambulatory ECG monitoring in the identification of a spontaneous type 1 Brugada pattern and its prognostic role. A sub-study of the BHF RASE Brugada project
Authors: Scrocco C , Ben-Haim Y , Ensam B , Aldous R , Miles C , Specterman M , Tome M , Papadakis M , Sharma S , Behr E R 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: Foundation. Main funding source(s): British Heart Foundation

Background
A spontaneous type 1 Brugada (spT1-BrS) pattern is a recognised marker of arrhythmic risk. However, its fluctuations may underestimate the risk in subjects with concealed T1-BrS at presentation.

Aim
To investigate the yield of repeat resting and high-lead 12-lead ECG and the additional role of 12-lead 24-hour Holter monitoring with leads V1 and V2 in standard and high precordial ECG positions (12-HPL Holter), and evaluate the prognostic role of spT1-BrS in a large, single-centre, cohort of BrS patients.

Methods
Three-hundred and eighty-one subjects with BrS enrolled in our Registry from 2008 to December 2021 and with at least 3 months follow-up data were included in this study. Seventy-seven had spT1-BrS pattern at presentation (Group 1), and 304 did not (Group 2). All received lifestyle recommendations and had regular follow-up appointments with 12-lead ECG; the majority of them were also screened with 12-HPL Holter. Medical notes and tracings were reviewed to identify a dynamic spT1-BrS and events at f-up (SCD/appropriate ICD shock).

Results
The mean age at presentation was 44±15 years; 52% of participants were males. All had at least 2 resting ECGs recorded; in 281 subjects at least one 12-HPL Holter was available (total 643, median 2, range 1-8). Over a median follow-up of 66 months (IQR 75), 37 subjects in Group 2 showed a spT1-BrS at least once: 10 during a repeat resting ECG, 2 during/after exercise tolerance test, 25 at 12-HPL Holter. The average time at spT1 appearance during follow-up was 23 months (range 1- 225). Those with a newly detected spT1-BrS were more frequently males and less likely to have a familial history of sudden cardiac death (Table 1). Excluding subjects with previous aCA/documented VT, 6 events occurred at f-up, all in subjects with spT1 (Figure 1). Univariate models showed that the presence of a spT1-BrS pattern was consistently associated with increased risk of events (at presentation: HR 10, 95% C.I. 1.8-54; at follow-up: HR 5.3, 95% C.I. 1.6-17).

Conclusions
A spontaneous T1-BrS can be detected in up to 12% of subjects with concealed BrS at presentation using 12-HPL Holter monitoring. Its presence is consistently associated with arrhythmic risk at f-up up, regardless of the time at detection. Prolonged ambulatory ECG monitoring is fundamental for risk stratification in this population.
Precordial reverse pattern break on ECG: could it be a discriminator endo/epicardial ablation site of left posteroseptal accessory pathways
Authors: Turan O E , Yilancioglu R Y , Ozcan E E 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: None.

Backrounds
The posteroseptal (PS) region may pose difficulty in WPW ablation due to its complex anatomical structure. The posteroseptal region may require the need for a transeptal puncture, CS venogram or coronary angiography due to its right and left endocardial and epicardial proximity. ECG prediction may prevent unnecessary procedures. Negative V1 double QRS transition pattern in the precordial leads is highly specific and validated for a right endocardial AP

Purpose
To investigate the presence of a reverse pattern break in the left posteroseptal [V1 (+) V3 (+)] WPW patient and compare between endocardial-epicardial ablation localization.

Methods
We retrospectively included 338 WPW patients into the study. 97 of them successfully ablated with posteroseptal area.

Results
Thirty-two of the total PS patient (33%) patients had a reverse pattern break or double transition pattern. A total of 4 patients with the middle cardiac vein (MCV) and diverticulum origin were identified. The left pattern break predicts endocardial localization 75% of the time while the right pattern predicts it 95% of the time.

Conclusion
Double transition and reverse pattern break are common in posteroseptal AP’s ECG. Left reverse pattern break is also highly predictive of endocardial ablation, similar to the right.
Using a smartwatch to record precordial electrocardiograms: a validation study
Authors: Van Der Zande J L , Strik M , Dubois R , Ploux S , Abu-Alrub S , Donker D W , Oppersma E , Bordachar P 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This work received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR)

Background
Smartwatches which support recording of a single-lead electrocardiogram (ECG) are increasingly being used worldwide, mainly for detection of atrial fibrillation. Recordings beyond the wrist are anecdotal as their reliability remains unknown.

Aim
This clinical validation study assessed the reliability of an Apple Watch (AW) to obtain frontal and precordial leads as compared with standard 12-lead ECGs in both healthy subjects and patients with underlying heart disease.

Methods
In 100 subjects (80 with ECG anomalies), a standard 12-lead ECG was performed, followed by AW recordings of the standard Einthoven leads (leads I, II, and III) and precordial leads V1, V3, and V6. Seven parameters (P, QRS, ST and T-wave amplitudes, PR, QRS, and QT intervals) were compared through a Bland-Altman analysis including bias (mean difference), absolute offset (mean absolute difference), and 95% limits of agreement.

Results
No significant differences were observed for any parameter across any lead, except for R-wave measured across precordial leads V1, V3, and V6 where significantly greater amplitudes were measured by the AW, (0.20 mV; 0.19mV; 0.49 mV respectively; p = 9x10-7; p = 7x10-4; p = 6x10-14, respectively), indicating overestimation by the AW. There were no significant differences in absolute offset or bias for any parameters of any leads (p &gt; 0.05).

Conclusion
ECGs recorded with the AW on the wrist but also on other positions had comparable durations and amplitudes compared to standard 12-lead ECG. The AW can be used to record frontal and precordial leads, paving the way for broader clinical applications.