bluuebunny/crossref_metadata_2025_split huggingface dataset:
Strauss criteria for left bundle branch block in cardiac resynchronization therapy: improved response with lower ventricular arrhythmic burden
Authors: Saplaouras A , Vlachos K , Mililis P , Batsouli A , Bazoukis G , Xydonas S , Niarchou P , Dragasis S , Kariki O , Patsiotis I , Toulgaridis F , Fragakis N , Efremidis M , Letsas K 
Published: May 2024

Abstract

Objectives
The study sought to evaluate the impact of the stricter Strauss criteria for left bundle branch block (St-LBBB) on cardiac resynchronization therapy (CRT) response, hospitalizations, ventricular arrhythmia (VA) events and mortality.

Background
Although left bundle branch block (LBBB) is a strong predictor of response to CRT, a significant number of patients remain non-responders.

Methods
This is a retrospective analysis of prospectively collected data on heart failure (HF) patients with LBBB admitted for CRT implantation. Patients were divided in two groups according to the fulfillment or not of St-LBBB criteria.

Results
82 patients with ischemic (ICM) and non-ischemic (NICM) HF [46 (56%) with St-LBBB and 36 (44%) with non-St-LBBB] were included. CRT response was more likely to occur in patients with St-LBBB (p&lt;0.01), with the group of NICM exhibiting the greatest benefit (p&lt;0.01). St-LBBB CRT responders displayed significantly lower rates of HF hospitalization (p&lt;0.0001) compared to non-St-LBBB group. This was mostly evident in patients with NICM (p&lt;0.0001) according to Kaplan-Meier time curves. CRT responders displayed significantly fewer VA events (p&lt;0.001) and lower mortality rates (p&lt;0.0001) than non-responders. Kaplan-Meier estimates demonstrated a significantly lower incidence of VAs in NICM patients with St-LBBB (p:0.049) in comparison to ICM patients with St-LBBB (p:0.25). Lower mortality rates were observed in CRT responders than non-responders (p&lt;0.0001) with the group of NICM with St-LBBB criteria exhibiting the greatest benefit (p:0.0238).

Conclusions
Patients with NICM and St-LBBB present the greatest benefit with respect to CRT response, HF hospitalizations, VA events, and mortality. St-LBBB criteria may improve patient selection for CRT.
Deep septal pacing for pacemaker-induced cardiomyopathy
Authors: Merce Klein J , Di Marco A , Rodriguez Garcia M , Faga V , Rodriguez Garcia J , Dallaglio P , San Antonio Darhandas R , Viedma Ustariz J , Payan Jimenez C , Anguera Camos I 
Published: May 2024

Abstract

Background
Conventional right ventricular pacing can impair left ventricular function and cause heart failure, known as pacing induced cardiomyopathy (PICM). Upgrade to cardiac resynchronization therapy (CRT) is the most common treatment for PICM. Recently, left bundle branch area pacing (LBBAP) has emerged as a potential alternative both to conventional RV pacing and to CRT. In Deep septal pacing (DSP), a simplified alternative to LBBAP, the lead is inserted deep in the septum, does not reach the subendocardial area, but is still able to achieve narrower paced QRS than during conventional pacing.

Purpose
The aim of this study was to assess the effect of DSP in a cohort of patients with PICM.

Methods
We included consecutive patients diagnosed with PICM who were referred to our unit between January 2020 and January 2022 for a device upgrade. The aim was to upgrade patients to DSP. In the absence of terminal R wave in V1, the procedure was considered successful if a paced QRS duration ≤140 ms was obtained. Clinical and device follow-up were performed one and 6 months after the procedure, and echocardiography at 6 months. The study was approved by the Clinical Research Ethics Committee and all patients signed informed consent.

Results
Fifteen patients were recruited during the study period. One patient was excluded because a QRS ≤ 140 ms could not be achieved, and 2 other patients because a terminal R wave in paced QRS in V1 was obtained. The characteristics of the 12 included cases are detailed in Table 1. The mean LVEF was 33% (SD 4%) and the mean percentage of RV pacing was 99% (SD 1%). All patients had symptomatic heart failure.
Non stylet-driven electrodes were used in 8 of the 12 patients. Acute threshold was &lt; 1V - 0’4 ms in all, and remained stable during follow-up. No procedure-related complications or lead dislodgements were detected. The mean paced QRS duration with RV pacing was 172 ms (SD 14 ms) whereas after the upgrade it was 130 ms (SD 7 ms). As compared to RV pacing, DSP was associated with a significant reduction in paced QRS duration (mean difference 41 ms, p&lt;0.001).
As shown in Table 1, after DSP all patients except one (11/12, 92%) experienced an increase in LVEF of at least 10%; five patients (42%) achieved an LVEF&gt;50%. The mean LVEF after the upgrade was 46% (SD 9%). The mean improvement in LVEF with DSP was 13% (SD 10%).

Conclusions
In patients with PICM, deep septal pacing achieves narrower QRS as compared to RV pacing and is associated with a significant improvement in LVEF. Deep septal pacing might be an effective and simpler alternative to biventricular or left bundle branch pacing in patients with PICM.Table 1
Real-time assessment of LV synchrony in AV block population undergoing LBB pacing using ECG Imaging
Authors: Martinez-Perez M , Pujol-Lopez M , Regany-Closa M , Pellicer-Sendra B , Molero R , Borras R , R Graterol F , Reventos-Presmanes J , Serrano-Campaner J , Roca-Luque I , Guasch E , Climent A M , Guillem M S , Tolosana J M , Mont L 
Published: May 2024

Abstract

Background
Left bundle branch pacing (LBBP) may prevent right ventricular (RV) pacing-induced dyssynchrony (DYS). Nowadays, real-time assessment of DYS correction is indirectly measured with QRS narrowing. Non-invasive ECG imaging (ECGI) technique may provide an evaluation of electrical resynchronization based on quantitative assessment of ventricular local activation time (LAT) maps.

Purpose
To assess whether real-time ECGI could evaluate LV synchrony achieved through LBBP, in a consecutive AV block (AVB) population.

Methods
A cohort of 12 patients with AVB were included. ECGI was performed during the implant procedure. ECGI signals were computed using an artificial intelligence derived cardiac geometry model. Ventricular LAT maps were obtained when pacing from septal RV and with LBBP (lead placed according to guidelines ECG criteria) for each of the patients.
The following parameters were obtained from ECGI LAT maps to assess intra and interventricular DYS pacing at the RV septal and LBB locations: total activation time (TAT), left ventricular activation time (LVAT), left ventricular dyssynchrony index (LVDI), ventricular electrical uncoupling (VEU = mean LVAT – mean RV activation time) and histogram overlap between LV and RV activation times distribution.
RESULTS: Nine of the 12 patients were men (75%), with a median age of 79[Q1 75-Q3 82]. QRS duration during RV septal pacing was 150 ms [138-172]. Median LVEF was 47% [26-59]. In Figure 1, it can be observed that dyssynchrony variables are corrected across all patients when reaching LBBP. Figure 2 shows activation maps during RV septal pacing and during LBBP, along with the QRS duration, and the RV and LV histogram of activation times.

Conclusion
ECGI is useful for assessing the LV synchrony correction during LBBP in an AV block population.Dyssynchrony variablesActivation maps with QRS and histograms
Optimal timing of of cardiac implantable electronic device reoperation
Authors: Schvartz N , Haidary A , Operhalski F , Hecker F , Zsigmond E J , Miklos M , Saghy L , Szili-Torok T , Erath J W , Vamos M 
Published: May 2024

Abstract

Background
Early re-intervention may increase the risk of infection of cardiac implantable electronic devices (CIED). Some operators therefore delay lead repositioning in case of dislocation by weeks, however there is no evidence to support this practice. The aim of our study was to evaluate the impact of the timing of re-operation on infection risk.

Methods
Data from consecutive patients (n=249) receiving lead/generator repositioning in one Hungarian and one German tertiary centre between January 1995 and August 2022 were retrospectively analysed. Relative risk of CIED infection in the first year was compared among patients undergoing early (≤1 week) vs. delayed (from 1 week to 1 year) re-operation.

Results
Out of 249 patients (mean age 70 ± 13 years, 54% male) requiring CIED re-intervention (30% single-chamber, 48% dual-chamber, and 22% CRT devices), 55 patients underwent right atrial (22%), 145 patients underwent right ventricular (59%), 20 patients underwent coronary sinus (8%), and 28 patients underwent multiple lead (11%) repositioning. Eighty-five patients (34%) went through an early (median 2, interquartile range (IQ): 1-4.5) and 164 (66%) patients had a delayed lead/pocket revision (median 53, IQ 36-209 days).
A total of 9 (3,6%) wound/device infections were identified during the first year of follow-up, 1 (1,2%) vs. 8 (4,9%) in the in the early vs delayed groups. The risk of infection was numerically lower in the early vs. the delayed intervention groups yielding no statistically significant difference (OR=0.232; 95% CI 0.029-1.888; p=0.172). After adjustment for typical risk factors for CIED infection (i.e., number of implanted leads, diabetes, heart failure, fever prior to implant, therapy with corticosteroids, anticoagulation or antiplatelet therapy, temporary pacemaker) this difference remained non-significant (adjusted OR=0.266, 95% CI 0.032-2.246, p=0.224). System explantation/extraction was necessary in 7 cases (2,8 %), all being revised in the delayed group (OR early vs. delayed 0.128, 95% CI 0.01-2.273, p=0.161).

Conclusion
In this bicentric study, delayed re-intervention did not reduce the risk of CIED infection compared to patients undergoing an early (&lt;1 week) re-operation.
The CHOIR study: acute hemodynamic effects of different pacing strategies in hypertrophic obstructive cardiomyopathy
Authors: Ahmed T , Ross S , Helle-Valle T , Gude E , Holm T , Andreassen A K , Broch K , Ravnestad H , Flattum M , Almaas V , Russel K E , Edvardsen T , Kongsgaard E , Stokke M K , Dejgaard L A 
Published: May 2024

Abstract

Background
The majority of patients with hypertrophic cardiomyopathy present with dynamic left ventricular (LV) outflow tract obstruction (LVOTO), referred to as hypertrophic obstructive cardiomyopathy (HOCM). Symptomatic treatment aims at reducing LVOTO with either medical therapy, invasive septal reducing therapies, or pacemaker therapy. There is conflicting evidence regarding the efficacy of pacemaker therapy. The effect of pacing strategies at physical exertion has not been investigated in HOCM.

Purpose
To identify the optimal pacing strategy for reducing LVOTO without compromising cardiac output at rest and exercise in HOCM.

Methods
In this ongoing project, we have so far included eight patients with symptomatic HOCM referred to our hospital for alcohol septal ablation (ASA). The day before ASA, we placed temporary pacing leads in the right atrium, the right ventricular (RV) apex and on the LV lateral wall. We also inserted a pulmonary artery catheter and performed per operative echocardiography. All patients had sinus rhythm. Intrinsic rhythm served as baseline and was followed by atrial sensed RV pacing, LV pacing and biventricular (BiV) pacing at rest and during supine cycling. We assessed LVOTO by echocardiography, and cardiac output by the thermodilution method under intrinsic rhythm and all pacing modalities.

Results
The mean age was 52±15 years, and two of eight patients were female. The mean maximal LV wall thickness was 16±1 mm. The resting LVOTO was 50±23 mmHg. Due to difficulties in placing the LV lead within a reasonable time frame, complete study protocol was not performed in all patients. All eight patients performed RV pace at rest, but only five patients (63 %) were LV and BiV paced at rest. Five patients performed supine cycling but only four patients completed with RV and BiV pacing. The graphs display LVOTO and CO in sinus rhythm and the different pacing maneuvers at rest and during supine cycling. At rest, 6 out of 8 patients (75%) had LVOTO reduction during RV pace, and CO was unchanged. Four of five patients (80%) had LVOTO reduction during BiV and LV pace compared to sinus rhythm, also with unchanged CO. During supine cycling four of five patients (80%) had a reduction of the LVOTO gradient during RV and BiV pacing, without significant CO change. No complications occurred during the interventions.

Conclusion
In this ongoing study on cardiac pacing in HOCM, RV, LV, and BiV pacing reduced LVOTO while CO remained unchanged at rest and during exercise.
Additional factors associated with sudden cardiac death in HCM patients
Authors: Butko O , Tseluyko V 
Published: May 2024

Abstract

Background
Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by an increase in the thickness of the left ventricular (LV) wall, which is not explained only by abnormal loading conditions. Sudden cardiac death (SCD) is the most devastating complication of HCM occurring in asymptomatic or younger patients without warning.

Purpose
To evaluate additional SCD risk factors in Ukrainian population of HCM patients.

Materials and methods
We retrospectively evaluated 350 consecutive HCM patients that were followed from 2006 to 2021 in our Cardiological Department. General clinical examination, standard 12-lead ECG, transthoracic echocardiography and 24 hours Holter ECG monitoring data were estimated. The 5-year SCD risk was calculated according to the HCM Risk-SCD score.
The endpoint of the study was SCD and its surrogates, including adequate performance of the implantable cardioverter-defibrillator and successful resuscitation.

Results
Follow-up time was 5.0 (1.5-9.5) years. During this time, 16 patients (4.6%) reached the end point, which was 0.9%/year. According to the HCM Risk-SCD score, 5 (31.3%) of this group had a high risk of SCD (≥ 6%) and 3 (18.8%) had an intermediate risk (≥ 4% and &lt; 6%).
In multivariable Cox regression analysis adjusted for conventional SCD risk factors it was found that independent predictors of SCD were unexplained syncope (HR 3.81, 95% CI 1.11-13.12, p=0.034), systolic blood pressure (SBP) (HR 0.97 , 95% CI 0.94- 0.99, p=0.026), "infarct-like" ST elevation on ECG (HR 6.81, 95% CI 2.09-22.16, p=0.001) and PQ interval duration (HR 1.03, 95% CI 1.01-1.05, p=0.002), Harrell's C-index 0.84, 95% CI 0.73-0.95, p &lt; 0.0001).

Conclusions
In our study HCM Risk-SCD score predicted SCD or surrogates only in 50% of cases. In order to improve the risk stratification some additional independent predictors of SCD can be proposed. ECG parameters ("infarct-like" ST elevation and PQ interval duration) and level of SBP were found to have SCD predictive value.
Prediction of Atrial Fibrillation with Single-Lead Mobile ECG during Normal Sinus Rhythm using Deep Learning
Authors: Lee K H , Kim Y R , Yoon N S , Park H W 
Published: May 2024

Abstract

Background
Single-lead ECG (electrocardiogram) acquisition from mobile devices provides more convenient way to identify arrhythmia. Prediction of atrial fibrillation (AF) by artificial intelligence facilitates AF screening. However, little is known about the prediction of AF with a single-lead ECG. Therefore, we proposed a method for predicting AF using single-lead mobile ECG during normal sinus rhythm (NSR).

Methods
Three deep learning models RNN, LSTM, and Resnet50 were used. Out of 13,509 ECGs from a total of 6,719 patients, we utilized a total of 10,287 NSR ECGs from 5,170 patients. Single-lead mobile ECGs were adjusted with noise filtering and segmented every 10 seconds. A random under-sampling was applied to reduce bias from data imbalance. Finally, 31,767 ECG segments composed of 15,157 segments labeled as potential AF and 16,610 segments labeled as healthy were entered for final analysis.

Results
The ResNet50 showed recall of 79.3%, precision of 65.8%, F1-score of 71.9%, accuracy of 70.5%, and AUC of 0.79 for the prediction of AF with NSR ECGs. These scores were higher than the other two models followed by RNN at 0.75 and LSTM at 0.74. For the external validation set, ResNet50 showed an F1-score of 64.1%, recall of 68.9%, precision of 60.0%, accuracy of 63.4%, and AUC of 0.68 for the prediction of AF with NSR ECGs.

Conclusion
A deep learning model using a single-lead mobile ECG during NSR predicted AF at risk in future. However, further study is needed to improve the performance of deep learning models for applying in the clinical setting.
Machine learning for outcome prediction of atrial fibrillation recurrence after catheter ablation
Authors: Knecht S , Cyriac J , Badertscher P , Krisai P , Schlageter V , Osswald S , Zellweger M , Kuhne M , Sticherling C 
Published: May 2024

Abstract

Background
Outcome prediction after catheter ablation for atrial fibrillation (AF) based on electronic health records (EHR) using machine learning (ML) is not yet established.

Purpose
The aim of the study was to assess the value of ML methods to predict the risk of AF recurrence after catheter ablation based on easily accessible EHR.

Methods
We analyzed 1362 patients from our prospective registry. Only patients undergoing a first AF ablation were studied. Follow-up was performed at 3, 6 and 12 months after the ablation including 24-hour and 7-day Holter electrocardiogram (ECG). Four different analyses with increasing complexity out of a set of overall 22 features using seven simple and three ensemble method ML algorithms were performed: model 1 (including age, sex, height, weight, and established anamnestic risk factors: AF-type, coronary artery disease, myocardial infarction, stroke, heart failure, hypertension, current smoker, diabetes, renal insufficiency), model 2: model 1 plus additional AF-history features (duration of AF in months, previous typical atrial flutter, number of previous electrical cardioversions, number of failed antiarrhythmic drugs), model 3: model 2 plus simple echocardiographic parameters (left ventricular ejection fraction, LA diameter), model 4: model 3 plus biomarkers (CRP, creatinine, NTproBNP). To evaluate the performance of the prediction, we report C-statistics, accuracy, and recall (sensitivity). The C-statistics of five risk scores for AF recurrence (APPLE, DR-FLASH, BASE-AF2, ATLAS, CHA2DS2-Vasc) and a logistic regression with a forward selection were calculated for comparison.

Results
Of the 1362 patients, 996 (73%) were male, mean age was 62±10 years and 60% presented with paroxysmal AF. Recurrence of AF during 1-year follow-up was observed in 458 patients (34%). The results for the four models using the eleven different ML algorithms are summarized in the Figure. In detail, the C-statistics were modest with a maximal value of 0.602 for the random forest (RF) classifier for the most complex model 4. The performance for the risk scores was maximal for the APPLE score (C-statistics 0.572) and comparable for the forward-selection logistic regression including five features with a C-statistics of 0.607 (95% CI 0.573-0.641).

Conclusion
In conclusion, outcome prediction of AF recurrence after catheter ablation with easily accessible EHR data remains challenging and cannot be improved simply by applying machine learning methods. Whether a more comprehensive feature selection, such as more complex ECG parameters instead of the selection of easily available features from the EHR, a combination with deep neural network-based feature extraction, or unsupervised ML might improve the result in a clinically relevant way needs further investigation.Results of the eleven ML algorithms
Can prediction of acute myocardial infarction using a deep learning-enabled electrocardiogram be used in real-world practice?
Authors: Jung L , Kim D H , Kim S H , Jun H M , Trinh M C 
Published: May 2024

Abstract

Background
Diagnosing acute myocardial infarction (MI) in the emergency department poses challenges. The utilization of a 12-lead electrocardiogram (ECG) is pivotal for detecting ST-segment elevation myocardial infarction (STEMI), yet enhancing ECG interpretation through a systematic algorithm could significantly improve diagnostic accuracy. Nonetheless, delayed diagnosis or misdiagnosis of STEMI is not uncommon in daily practice.

Purpose
This study aims to develop a fully convolutional network (FCN) based on ECG data as a diagnostic support tool and to evaluate its effectiveness in STEMI detection.

Methods
A retrospective cohort study involved 3,298 patients with angiographically confirmed STEMI and 37,393 control ECGs, comprising normal readings, false positives, and ECGs mimicking STEMI. The FCN underwent internal training, external validation, and testing across various data splits (80:10:10, 70:15:15, and 60:20:20). Performance evaluation on validation data included assessing the area under the receiver operating characteristic curve (AUC). Subsequently, the trained model predicted unseen data, and sensitivity, specificity, false positives, and false negatives were calculated to evaluate model performance.

Results
The FCN exhibited exceptional performance in STEMI detection during both internal training and external validation across different data splits. The receiver operating characteristic curves yielded AUC values of 0.995 (80:10:10), 0.994 (70:15:15), and 0.995 (60:20:20). Consistently high values were observed in precision-recall curves, with AUC values of 0.974 (80:10:10), 0.962 (70:15:15), and 0.973 (60:20:20). When utilizing this FCN model in the clinical setting to reanalyze 20 cases of previously misdiagnosed electrocardiograms, it correctly diagnosed 17 cases.

Conclusion
Integrating the FCN into clinical practice can notably improve the timely and accurate diagnosis of acute MI, reducing instances of delayed or erroneous STEMI diagnoses and facilitating prompt reperfusion therapy.
Repolarization dynamics stability in Brugada type-1 pattern subjects with positive and negative genetics
Authors: Sabatini A , Pellegrini N , Varriale A , Piccolo S , Capocci S , Tomasi L , Mugnai G , Tomei R , Franchi E , Ribichini F , Bolzan B 
Published: May 2024

Abstract

Background
Brugada type-1 pattern (Brgd1) risk stratification in asymptomatic subjects and its repolarization dynamics are complex.

Purpose
This study aims to analyze, from alternative standpoints, superficial 12-lead ECG V1 repolarization patterns (repol.). This method diverges from standard ECG pattern characterization. It rather exploits nonlinear dynamics and stability of ECG repol. to assess stability driving cardiac dynamics. This work consists in analyzing 2 subjects with Brgd1: Subject1 with negative genetics and negative EP study. Subect2 with positive genetics.

Target
To deepen knowledge/insight and applications of control-and-stability-theory applied to 12-lead ECG, aiming to eventually diminish the number of invasive EP studies.

Methods
A stability control closed loop system has been designed to model electrophysiology dynamics of cardiac conduction: ECG segments being the input-output of the system. (Figure). A sequence of V1 repol. have been scanned, digitized, and quantitatively processed yielding stability parameters (poles in S-plane). Scanning and signal processing performed by Matlab R_2023b.

Results
Figures.

Conclusions
Based on our data, 12-lead-ECG repol. seem to be associated with increasing stability in Subject1, exhibiting negative genetics. On the other hand, less stability seems to be associated with Subject2, reporting positive genetic tests.
In conclusion, furthering control-and-stability-theory applied to 12-lead ECGs aims to deeper comprehension of physiological and pathological substrates of malignant arrhythmias, and to focus on noninvasive risk stratification strategies for ICD implantation indication in BrS.
Further development of this technique will be largely facilitated by the implementation of AI methodologies in the near future.