Standard ECG Research Articles

Characterization of the effects of right ventricular and left bundle branch area pacing on the QRS complex

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): TED2021-130459B-I00 LMP94_21 Introduction Right ventricular pacing (RVP) has been the treatment of choice for patients with atrioventricular block and sinus node disease for the last decades . It is well known that RVP ventricular may cause ventricular dyssynchrony and could lead to left ventricular dysfunction in 20% of patients, and therefore could increase the risk of heart failure, atrial fibrillation and cardiovascular mortality. Left bundle branch area pacing (LBBAP) has recently emerged as a new physiological pacing modality that can circumvent the limitations of RVP. The purpose of this study was to compare changes induced by RVP and LBBAP in the standard 12-lead ECG by the analysis of QRS complex characteristics in order to asses ventricular dyssynchrony. Methods ECG recordings from 134 patients (82 LBBAP, 52 RVP) with indication for anti-bradycardia therapy were acquired before and after pacemaker implantation. Patients were grouped into narrow and wide baseline QRS using a threshold for the QRS duration of 120 ms. Median beats were calculated at baseline and 24 hours post-implantation states for each patient. ECG markers describing ventricular activation were measured, including: 1) QRS duration (QRSd) from QRS onset to QRS end; 2) QRS area (QRSa), computed from the individual areas in orthogonal X, Y and Z leads calculated using the Kors conversion matrix; 3) a new index QRS50 proposed to estimate the ventricular activation time from the first three components of the singular value decomposition of the median QRS complex. Results Note that the QRS characteristics showed similar values in baseline for both pacing techniques. In patients with narrow QRS, we found that paced QRS characteristics remained similar from the basal QRS in LBBAP group whereas in RVP group they worsened. The three markers, QRSd, QRSa and QRS50, increased after RVP by 34 ms, 68 uVs and 22 ms, respectively (p<0,001). In patients with wide QRS, LBBAP significantly reduced QRSd, QRSa and QRS50 while RVP increased QRSa and QRS50 and left QRSd unchanged. Conclusion In patients receiving a pacemaker for anti-bradycardia therapy, LBBAP led to more synchronized ventricular activation than RVP measured from QRS duration- and area-related characteristics.

Hypertrophic cardiomyopathy in a girl with Danon disease

A prospective observation for 4 years (from 14 to 17 years) is presented for a girl with Danone’s disease. The early onset of the disease was noted, the clinical picture was dominated by syncopal and syncopal conditions. According to the clinical picture, presyncopal conditions were of a vasovagal nature, which was verified by the results of the Tilt test when the vasodepressor variant was detected. The disease was characterized by isolated cardiac disorders in the form of concentric hypertrophic cardiomyopathy, widespread fibrous changes in the myocardium. According to the standard ECG and daily ECG monitoring, ventricular preexitation syndrome was detected. Electrophysiological examination established the nodo-ventricular tract. Myopathy, cognitive impairment and visual changes were absent. A mutation in the heterozygous state was detected in exon 5 of 9 exons of the LMP2 gene, leading to the acquisition of a premature stop codon, was identified. X:g.119581719G>A ENST00000434600.2: c.718C>T. The mutation was verified by Sanger. The case in the pedigree is sporadic. As a prevention of sudden cardiac death, implantation of a cardioverter-defibrillator was performed. Effective relief of induced stable ventricular fibrillation (Burst stimulation protocol) was achieved only with the use of a ventricular electrode with two shock coils.

A Comparison of Personalized and Generalized LSTM Neural Networks for Deriving VCG from 12-Lead ECG

Vectorcardiography (VCG) is a valuable diagnostic tool that complements the standard 12-lead ECG by offering additional spatiotemporal information to clinicians. However, due to the need for additional measurement hardware and too many electrodes in a clinical scenario if performed along with a standard 12-lead, there is a need to find methods to derive the VCG from the ECG. We have evaluated the use of Long Short-term Memory (LSTM) neural networks to learn the transformation from 12-lead ECG to VCG that is applicable across subjects and for each subject. We refer to these networks as generalized and personalized, respectively. We calculated the Root Mean Square Error (RMSE), R2, and Pearson correlation coefficient to compare waveforms of derived and actual VCG. We also extracted and compared diagnostic parameters from VCG, namely the QRS-loop magnitude, T-loop magnitude, and QRS-T spatial angle, from actual and derived VCGs using the Pearson correlation coefficient and Bland Altman limits of agreement. The personalized models performed better than generalized models in waveform comparisons and in the error of extracted diagnostic parameters from VCG waveforms. The use of personalized transformations for the derivation of VCG from standard 12-lead has the potential to improve and augment the diagnostic yield and accuracy of a standard 12-lead interpretation.

PO-04-184 ARTIFICIAL INTELLIGENCE-ESTIMATED BIOLOGICAL HEART AGE USING 12 LEAD ELECTROCARDIOGRAM PREDICTS MORTALITY AND CARDIOVASCULAR OUTCOMES

There is a paucity of data on the artificial intelligence-estimated biological ECG heart age (AI ECG-heart age) for predicting cardiovascular outcomes as distinct from the chronological age (CA). We sought to investigate whether a deep learning-based algorithm to estimate the AI ECG-heart age using standard 12-lead ECGs predicted mortality and cardiovascular outcomes. We trained and validated a deep neural network using raw ECG digital data from 425,051 12-lead ECGs acquired between January 2006 and December 2021. The network performed a holdout test using a separate set of 97,058 ECGs. Additionally, randomly age-sex matched patients with reduced and preserved ejection fraction (EF) were compared. The deep neural network was trained to estimate the AI ECG-heart age (the mean absolute error 5.8 ± 3.9 years and R squared of 0.7 (r=0.84, p<0.0001) (Fig 1A). In the Cox proportional-hazards models after adjusting for relevant co-morbidity factors, the subjects with an AI ECG-heart age of seven years older than the chronological age had higher all-cause mortality (HR 1.62 [1.43-1.84]) and major adverse cardiovascular events (MACEs) (HR 1.92 [1.65-2.23]), while those under seven years had an inverse relationship (HR 0.86 [0.77-0.95] for all-cause mortality; HR 0.73 [0.63-0.84] for MACEs). Subjects with a reduced EF had a substantially higher mean AI ECG heart-age, QRS duration, and corrected QT intervals than those with a preserved EF (all p<0.001) (Fig 1B). The biological heart age estimated by AI had a significant impact on mortality and MACE. Those data suggested that the AI ECG-heart age might facilitate the primary prevention and health care for cardiovascular outcomes.

PO-02-228 ASSOCIATION BETWEEN SIGNAL-AVERAGED ECG INDICES AND RV STRUCTURAL ABNORMALITIES IN PATIENTS WITH ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY: INSIGHTS FROM NORDIC ARVC REGISTER

The value of signal-averaged ECG (SAECG) derived ventricular late potentials (LP) as a minor depolarization criterion of arrhythmogenic right ventricular cardiomyopathy (ARVC) has been debated. Another criterion from the same category, terminal activation duration (TAD>55 ms), is obtained from standard V1 ECG lead, which makes it easier for use. However little data exist regarding the relationship between structural right ventricular (RV) ARVC substrate, LP and TAD. We aimed to explore the association between structural and functional RV abnormalities assessed using cardiac magnetic resonance (CMR), SAECG parameters, and abnormal TAD. Patients with definite ARVC diagnosis or genotype-positive family members who were recruited in the Nordic ARVC Registry with SAECG and CMR were included (n=268, mean age 42±16 years, female 46%, probands 49%). RV end-diastolic volume index (RVEDVI), RV ejection fraction (RVEF), and late gadolinium enhancement (LGE) presence were assessed. RV was defined as enlarged if RVEDVI > 100 ml/m2 for men and 90 ml/m2 for women. RVEF was considered reduced if lower than 45%. SAECG components were assessed using TFC2010 definitions: filtered QRS duration (fQRSd)>114 ms, duration of terminal low-amplitude QRS signal below 40 μV (LAS40)> 38 ms and root-mean-square voltage of the terminal 40 ms (RMS40)< 20 μV. An abnormal value of any one or more of these indexes was considered as the presence of LP. We assessed sensitivity and specificity of the SAECG indexes and TAD for association with abnormal RVEF, LGE and/or RVEDVI. C-statistics was used to assess the association between each of SAECG parameters as continuous variables and RV abnormalities. All 3 SAECG indexes were significantly associated with RV structural abnormalities using c-statistics (Table), each of them characterized by higher specificity and lower sensitivity than LP. TAD demonstrated high specificity but poor sensitivity in prediction of RV structural abnormalities. LP had lower specificity, but much higher sensitivity for association with RV structural and functional abnormalities than TAD. In a large cohort of patients with definite ARVC or genotype-positive family members SAECG indexes appear to have lower specificity for detection of structural and functional RV abnormalities compared to TAD, however its sensitivity far exceeds the one of the TAD and supports SAECG value as an ECG indicator of RV substrate.

PO-02-229 AUTOMATED LOCALIZATION OF ATRIAL ECTOPIC BEATS USING 12-LEAD ECG MEAN SPATIO-TEMPORAL VECTOR POSITION: IMPORTANCE OF INCORPORATING PATIENT-SPECIFIC ANATOMIC MODELS

Localizing the origin of atrial ectopic activity from the 12-lead ECG can be challenging, particularly in patients with atrial pathology. To identify the origin of paced atrial ectopic beats (simulating atrial ectopy) using software that quantifies the mean spatio-temporal vector position of cardiac depolarization projected onto generic and patient-specific atrial models. 12-lead ECG data were collected during sinus rhythm (SR) and during regular pacing from the high and low right atrium (HRA/LRA), proximal and distal coronary sinus (CS), pulmonary veins (LSPV, LIPV, RSPV, RIPV), and left atrial appendage (LAA). The origin and trajectory of the atrial signals were calculated with software that analyzes P-waves from the 12-lead ECG and automatically constructs a net vector of electrical activity projected onto a standard generic model of human atria (CineECG; Nieuwerbrug, The Netherlands). The model atria were split into 9 segments, and the software accuracy was scored based on localization of the paced atrial signal origin to the correct segment. To see if patient-specific anatomy improved localization, we also incorporated atrial anatomy from cardiac MRIs acquired from a subset of 12 patients and compared localization to the generic model. We enrolled 19 patients (mean age 70±9, 4 female) with paroxysmal (63%) or persistent (37%) AF and left atrial (LA) enlargement (mean LA volume 58 cc/m2) undergoing pulmonary vein isolation for treating AF. Using the generic atrial model, the software correctly localized 105/142 (74%) beats to the correct atrial segment (Figure). Accuracy was better for RA compared to LA signals (90% vs. 62%, p < 0.05). Localization worked best in the coronary sinus (19/19, 100%) and worst in the LPVs (14/33, 42%). Patient-specific models improved localization of PV signals, particularly left-sided ones (generic vs. patient-specific: RPVs 70% vs 85%, p = 0.36, LPVs 42% vs 76%, p = 0.03). Accuracy improved and was similar for RA vs. LA localization when using patient-specific models (90% vs. 82%, p = 0.48). The novel software algorithm can automatically localize paced signals in both the left and right atria despite significant atrial pathology. Patient-specific anatomic models improve localization. This software holds promise for automatically localizing and classifying atrial arrhythmias and guiding therapy, including catheter ablation, based on standard 12-lead ECG data.

Inverse ECG imaging as a novel solution for acute coronary syndrome classification from standard 12-lead ECG in the emergency department

Spiral wave reentry is a potential mechanism of atrial fibrillation (AF), but is difficult to differentiate clinically from multiple wavelet breakup using standard bipolar recordings. We developed a new methodology using bipolar recordings to estimate the direction of local activation wavefronts during AF by calculating the electrogram conformation (Egm-C). We subsequently used recurrence quantification analysis (RQA) of Egm-C to differentiate regions of spiral wave reentry from wavelet breakup.A 2D computer simulation was created with regions containing a stable spiral wave and also regions of wavebreak. A grid of 40 × 40 unipolar electrodes was superimposed. At each site, the actual wavefront direction (WD) was determined by comparing relative activation timings of the local intracellular recordings, and the estimated wavefront direction (Egm-C) was determined from the morphology of the local bipolar electrogram. RQA of Egm-C was compared to RQA of actual WD in order to differentiate AF mechanisms.RQA of actual WD and Egm-C both distinguished regions of spiral wave reentry from wavelet breakup with high correlation between the two methods (recurrence rate, r = 0.96; determinism, r = 0.61; line max, r = 0.95; entropy, r = 0.84; p < 0.001 for all). In areas of stable spiral wave reentry, the recurrence plots of both Egm-C and actual WD demonstrated stable, periodic dynamics, while regions of wavelet breakup demonstrated chaotic behavior largely devoid of repetitive activation patterns.Calculation of Egm-C allows RQA to be performed on bipolar electrograms during AF and differentiates regions of spiral wave reentry from multiple wavelet breakup.

PO-01-138 NON-INVASIVE 3-D MAPPING (ECGI) OF MACRO-REENTRANT ATRIAL ARRHYTHMIAS

Peri-valvular atrial arrhythmias are the most common macro-reentrant mechanism seen in both de-novo and repeat atrial fibrillation (AF) ablations. Standard 12-lead ECG’s poorly predict tachycardia mechanisms especially post AF ablation. Identifying the mechanism of tachycardia non-invasively could help in procedural planning, expedite the invasive procedure, and identify critical areas sustaining persistent AF in patients with concomitant AF. The objective was to determine if ECGi could identify the mechanism of atrial flutters in patients with or without prior AF ablations. 30 patients (11 de-novo, 19 prior ablation) underwent non-invasive propagation and phase mapping (CardioInsight, Medtronic, Inc) and intracardiac bi-atrial high-density activation mapping (HD Grid and Precision, Abbott Medical). An 8-segment model (RA lateral, RA anterior, CTI, Septum, LA anterior, LA lateral, CS, LA posterior) was used for directionality in the propagation maps, and a 9-segment model for phase map analysis was used for presence and localization of ‘rotational hinge points’ which can occur with wavefronts moving in different directions within close proximity. The precise tachycardia mechanism (counterclockwise (CCW) or clockwise (CW) and cavo-tricuspid isthmus (CTI) or mitral isthmus (MI) dependent) was determined by intracardiac activation maps, entrainment, and confirmed with termination by ablation. Directionality in a region was deemed concordant if non-invasive and intracardiac maps matched or was declared discordant/indeterminate. A total of 31 macro-reentrants maps were analyzed: 16 CCW-CTI; 7 CW-CTI; 4 CCW-MI; 4 CW-MI. Regional directional concordance percentages shown in theTable. A total of 30/31 phase maps identified at least one region as a 'rotational hinge point', with 26/31 maps showing paired 'hinge points'. Location of rotations are shown in the Figure. ECGi can be used in macro-reentant atrial arrhythmias to determine directionality of activation with best concordance on the lateral walls of both atria. In our study, 97% of peri-valvular atrial flutters had at least one 'rotational hinge point' with 84% showing them paired representing macro-reentant circuit. Posterior LA wall rotational area was present in all peri-mitral flutters. Additionally, paired 'hinge points' with lateral atrial wall directionality were the best determinants of the macro-reentant mechanism.Tabled 1Directional ConcordanceRA LatRA AntCTISeptumLA AntLA LatCSLA PostCCW-CTI88%69%88%44%44%--50%--CW-CTI71%43%71%43%43%--29%--CCW-MI100%50%--75%75%100%100%50%CW-MI100%60%--40%40%80%80%20% Open table in a new tab

PO-01-202 HEART RATE FRAGMENTATION AS A MARKER OF ALTERED ACTIVITY OF THE AUTONOMIC NERVOUS SYSTEM ACTIVITY : A NOVEL PREDICTOR OF ATRIAL FIBRILLATION OCCURRENCE IN THE GENERAL POPULATION

The dysfunction of the autonomic nervous system (ANS) plays a crucial role in atrial fibrillation (AF). But the meaning of high heart rate variability (HRV) in predicting AF is still under debate. Short-term HRV is conceptually attributed to physiologic vagal tone modulation. But recent data suggest that a component of short-term HRV, called heart rate fragmentation, is related to ANS breakdown. To assess the predictive capacity of novel short-term HRV-derived metrics regarding the occurrence of AF in the general population during long-term follow-up. A cohort study was designed to prospectively assess the predictive value of ANS activity level regarding cardiovascular events and mortality. 1011 subjects aged 65, without history of AF, and with low cardiovascular risk were enrolled in the study. A 17.8-year follow-up was managed. HRV data were acquired by 24-h Holter ECG monitoring at baseline and assessed by frequency and time-domain methods. Heart rate fragmentation using the percentage of inflection points (PIP) and alpha 1-index (using fractal evaluation of NN intervals) were also calculated. AF occurrence during follow-up was registered and defined as a standard 12-lead ECG recording or Holter recording with ≥ 30 s of AF. AF was diagnosed in 123 patients representing a cumulative incidence of 13.4%. Univariate analyses are presented in the Table. The occurrence of AF was independently predicted by the male gender (HR=1.96,95%CI:1.3-2.9,p<0.01), a higher percentage of NN intervals that differ by more than 50 ms from the previous interval (pnn50) (HR=2.01,95%CI:1.3-3.2,p<0.01), an increased percentage of inflection points (HR=2.48,95%CI:1.5-4.2,p<0.01), and a reduced alpha 1 index (HR=1.63,95%CI:1.04-2.55,p<0.01). Given these results, a predictive score was built up based on the 4 independent predictors (Panel A). A predictive score of AF occurrence during the 18-year follow-up was assigned to every patient from 0 to 4. Compared to the group of patients with a score of 0 (Panel B), AF occurrence was progressively increased in patients with a score of 2 (HR=5.93, 95%CI:0.82-43.08, p=0.08), of 3 (HR=12.75, 95%CI:1.75-92.83, p=0.01), and of 4 (HR=22.31, 95%CI:2.98-167.23, p<0.01). Markers of heart rate fragmentation independently predict the AF occurrence in the general population, such as an increased PIP and a reduced alpha 1-index. A clinical predictive score is able de segregate a population at high risk of AF occurrence among the general population.Tabled 1Univariate analysesVariablesHRCI 95%P-valueCLINICAL FEATURESMale gender1.741.22 - 2.48<0.01Hipertension1.741.22 - 2.50<0.01Overweight1.331.04 - 1.700.02Increased PAC burden2.111.31 - 3.41<0.01ANS FEATURESpnn501.841.28 - 2.64<0.01RMSSD1.901.33 - 2.71<0.01LF/HF0.600.39 - 0.940.02PIP2.201.40 - 3.47<0.01Alpha 12.191.54 - 3.12<0.01Deceleration capacity2.001.30 - 3.09<0.01 Open table in a new tab

PO-04-206 THE TRANSFERABLE ARTIFICIAL INTELLIGENT MODEL BASED ON ELECTROCARDIOGRAM: A PROSPECTIVE OBSERVATIONAL STUDY TOWARD HOME-BASED APPLICATION OF SINGLE-LEAD ECG IN IDENTIFYING HEART FAILURE WITH LOW LEFT VENTRICULAR EJECTION FRACTION

Although heart failure with reduced ejection fraction (HFrEF) can benefit from treatment, it remains underdiagnosed due to the limited accessibility of echocardiography. Several studies have shown that artificial intelligent (AI) models of 12 leads ECG can successfully identify ventricular dysfunction. However, such models are hard to deploy for frequent surveillance of the left ventricular ejection fraction (LVEF), especially under the home-based scenario. We aimed to design a prospective study that used a single-lead 30-second ECG recorded and operated by patients to transfer and test an AI model constructed with convolutional neural network (CNN) analysis of standard 12-lead ECG from a retrospective single medical center cohort. In addition, we also try to leverage the short-term heart rate variability (HRV) to improve the sensitivity and specificity of the model. The 12-lead ECGs of sinus rhythm with LVEF measuring within 90 days of the recording date were included. The dataset was split into training and validation sets at a ratio of 7:3 without patient overlapping. To select feasible models of single-lead ECG for identifying LVEF of 45% or lower, we trained the CNN models using single-lead ECG recorded from each lead placement as input. The models with the top 3 performances were transferred to the corresponding lead of the single-lead ECG datasets acquired prospectively to validate their generalizability. Among all single-lead ECG models trained from 56479 recordings of 33010 patients, the AUC of the top 3 ranked models (lead aVR, I, and V5) were 0.89, 0.88, and 0.88, respectively. While aVR is impossible to derive from single-lead placement, we applied the models of lead I, V5, and lead II instead. For the prospective single-lead ECG datasets, 144 patients with an average age of 64 years old were recruited, and the models were tested. No significant drop in the performance of the lead I model was shown (AUC=0.88). Furthermore, adding HRV to the lead I model can improve overall accuracy (AUC=0.92) and sensitivity and specificity of the optimal cutting threshold. With the assistance of AI algorithm, single-lead ECG recorded and operated by patients from a wristband performed well in detecting low LVEF of 45% or lower. This simple approach can provide an inexpensive and convenient tool for the home-based monitoring of LVEF, and the tool's effectiveness warrants further study.

PO-05-097 FIRST REPORT OF CRYOABLATION OF NON-PAPILLARY MUSCLE PVCS UNDER DIRECT VISUALIZATION DURING MV REPAIR: INTER-LEAFLET TRIANGLE AND THE AORTO-MITRAL CONTINUITY

Up to 60% of patients with mitral valve prolapse (MVP) have premature ventricular contractions (PVC), usually of papillary muscle (PM) origin. However, one-third of PVCs are of non-PM origin, from areas exposed to annular stress forces. We have previously demonstrated the feasibility of intraoperative cryoablation of PM PVCs under direct visualization during mitral valve (MV) repair. To our knowledge, this is the first report of a similar approach for non-PM PVCs. We present two cases of visually-guided surgical cryoablation of non-PM PVCs at the time of elective MV repair. Both were guided by ECG morphology criteria and hybrid PET/MRI imaging pre-operatively. n/a Case 1 (Figure): 73 year old female with degenerative MVP, severe MR and frequent PVCs (27%). There were two PVC morphologies: the dominant PVC was suggestive of interleaflet triangle (ILT) origin (abrupt V3 transition), and the less frequent PVC was consistent with postero-medial PM origin. Hybrid PET-MRI demonstrated focal uptake of FDG in the LV summit region just under the aortic valve. The patient underwent an uncomplicated MV repair, TV repair and cryoablation of the ILT (open endocardial retrograde approach) and then the posterior PM. Follow up TTE showed normal MV and aortic leaflets function without regurgitation or stenosis. An event monitor at 2 months post-op revealed a PVC burden of 2% (off drugs). Case 2: 76 year old male with degenerative MVP, severe mitral regurgitation (MR) and frequent symptomatic PVCs (24%), suggestive of an aortomitral continuity (AMC) origin. Simultaneous cardiac 18F FDG-PET and MRI with LGE imaging demonstrated focal uptake of FDG in the AMC region, no LGE was detected. The patient underwent an uncomplicated MV repair, TV repair and cryoablation of the AMC. The cryo-application was performed on the atrial side of the mitral annulus with forward pressure to reach the ventricular myocardium. There were no PVCs during post-op monitoring and a 6-month follow-up monitor revealed a PVC burden of 1% (off drugs). Surgical cryoablation of non-PM PVCs under direct visualization at the time of MV surgery, using standard ECG criteria and pre-op Hybrid PET-MRI imaging, is feasible. Further studies are needed to determine the safety and effectiveness of adjunctive PVC cryoablation at the time of MV surgery.

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

Pulmonary vein isolation (PVI) modulates the intrinsic cardiac autonomic nervous system and reduces atrial fibrillation (AF) recurrence. 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. PVI acutely (16 ± 8.9h) reduced PWH by 20.7% (from 31 ± 1.9 to 25 ± 1.6µV, p < 0.001) and TWH by 27% (from 111 ± 7.8 to 81 ± 6.5µV, p < 0.001). RWH was unchanged after PVI (p = 0.068). In a subgroup of 20 patients with longer follow-up (mean = 47 ± 3.7days after PVI), PWH remained low (25 ± 1.7µV, 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 3months 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. 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.

Cardiac Magnetic Resonance Imaging Detects Myocardial Abnormalities in Naturally Infected Dogs with Chronic Asymptomatic Chagas Disease.

Trypanosoma cruzi infection causes inflammation and fibrosis, resulting in cardiac damage in dogs. The objectives of this study were to describe cardiac magnetic resonance imaging (CMR) in naturally infected dogs with chronic Chagas disease and the frequency of abnormalities for CMR and cardiac diagnostic tests. Ten asymptomatic, client-owned dogs seropositive for T. cruzi were prospectively enrolled in an observational study evaluating echocardiography, ECG (standard and ambulatory), cardiac troponin I (cTnI), and CMR. Standard ECG measurements (3/10) and cTnI concentration (1/10) outside the reference range were uncommon. Ambulatory ECG abnormalities were documented more frequently (6/10 dogs) than with standard ECG and included ventricular arrhythmias (4), supraventricular premature beats (3), second-degree atrioventricular block (2), and sinus arrest (1). Echocardiographic abnormalities were documented in 6/10 dogs including mildly increased left ventricular internal dimension in diastole (1) and decreased right ventricular (RV) systolic function based on reductions in tricuspid annular plane systolic excursion (3) and RV S' (4). Abnormalities were detected with CMR in 7/10 dogs including delayed myocardial enhancement in 5 of which 2 also had increased extracellular volume, abnormal wall motion in 5, and loss of apical compact myocardium in 1. In conclusion, CMR abnormalities were common, and the results of this study suggest CMR can provide useful information in dogs with T. cruzi infection and may support naturally infected dogs for future clinical investigation as an animal model for Chagas disease.

Utility of an Artificial Intelligence Enabled Electrocardiogram for Risk Assessment in Liver Transplant Candidates.

Post-operative cardiac complications occur infrequently but contribute to mortality after liver transplantation (LT). Artificial intelligence-based algorithms based on electrocardiogram (AI-ECG) are attractive for use during pre-operative evaluation to screen for risk of post-operative cardiac complications, but their use for this purpose is unknown. The aim of this study was to evaluate the performance of an AI-ECG algorithm in predicting cardiac factors such as asymptomatic left ventricular systolic dysfunction or potential for developing post-operative atrial fibrillation (AF) in cohorts of patients with end-stage liver disease either undergoing evaluation for transplant or receiving a liver transplant. A retrospective study was performed in two consecutive adult cohorts of patients who were either evaluated for LT or underwent LT at a single center between 2017 and 2019. ECG were analyzed using an AI-ECG trained to recognize patterns from a standard 12-lead ECG which could identify the presence of left ventricular systolic dysfunction (LVEF < 50%) or subsequent atrial fibrillation. The performance of AI-ECG in patients undergoing LT evaluation is similar to that in a general population but was lower in the presence of prolonged QTc. AI-ECG analysis on ECG in sinus rhythm had an AUROC of 0.69 for prediction of de novo post-transplant AF. Although post-transplant cardiac dysfunction occurred in only 2.3% of patients in the study cohorts, AI-ECG had an AUROC of 0.69 for prediction of subsequent low left ventricular ejection fraction. A positive screen for low EF or AF on AI-ECG can alert to risk of post-operative cardiac dysfunction or predict new onset atrial fibrillation after LT. The use of an AI-ECG can be a useful adjunct in persons undergoing transplant evaluation that can be readily implemented in clinical practice.

High predictive value of paced QRS frequency in verification of left bundle branch pacing.

Left bundle branch area pacing (LBBAP) is a newer technique to deliver more synchronous left ventricular activation. Several criteria have been proposed, but not fully validated, to confirm LBBAP during implantation of the pacing lead. Spectral analysis has been used to characterize the frequency components of the clinical QRS utilizing the Fourier transform algorithm. We hypothesized that higher frequency content of the paced QRS complex may show predictive value of successful LBBAP. We evaluated 84 patients with ejection fraction > 50%, who underwent LBB lead placement (n = 42) using ≥ 1 current criteria and right ventricular midseptal (RVsp) lead placement (n = 42) from 2000 to 2022. Time frequency analysis (Matlab) was used to determine the frequency content of the paced QRS complex. The centroid frequency (CF), which is the weighted average QRS frequency, was calculated. Patients in RVsp group had a longer paced QRS duration (155.6 ± 28.0 vs 127.1 ± 17.2, p < 0.002) compared to the LBBAP group. Of all standard ECG leads, the paced QRS in V2 gave the greatest difference of the CF of the LBBAP group at 8.8 ± 1.6 Hz versus 5.7 ± 0.7 Hz of the RVsp group. This difference was significant by both univariate (p < 0.003) and multivariate (p < 0.010) analysis. Predictive value of the CF for successful LBB pacing in lead V2 was highest with an AUC of 0.98. The sensitivity and specificity were 88.1% and 97.6%, respectively. Spectral analysis predicts successful LBBAP with higher frequency content when compared to RVsp pacing. Given the limitations to the current criteria to confirm LBBAP, intraprocedural use of frequency content analysis of the paced QRS complex in patients may prove useful at verifying LBB capture if verified by prospective clinical trials.

Electrocardiogram Changes in Patients with Positive Troponin I Presenting with Non-ST-Elevation Myocardial Infarction

Objectives: Unlike “ST-segment elevation myocardial infarction (STEMI)”, there is a wide spectrum of ECG changes for Non-STEMI (NSTEMI) patients with varying prognostic implications. Therefore, the purpose of this study was to determine the frequency of ECG changes in patients with positive high-sensitive troponins (hs-cTn) presenting with NSTEMI. Methodology: This Cross sectional study included 282 patients with positive hs-cTn diagnosed with NSTEMI. Standard 12-lead ECG was performed for all the patients. The clinical profile and ECG changes such as ST elevation in aVR, T wave inversion, and ST depression were noted. Results: Out of 282 patients, 68.1% (192) were male, mean age was 58.5 ± 10.6 years, 56.7% (160) were hypertensive, and 39.7% (112) were diabetic. The ECG was normal in 8.2% (23) while, 64.5% (182) had ST-depression, out of which 1.1% (2) had ST-depression of &lt;1mm, 78% (142) had ST-depression of 1-2mm, and remaining 20.9% (38) had ST-depression of &gt;2mm. T-wave inversions were observed in 45.7% (129). ST-elevation of ≥1 mm in lead aVR was noted in 19.1% (54) patients. Conclusion: A considerable number of NSTEMI patients with positive hs-cTn showed no specific ECG changes. ST-depression followed by T wave inversion and ST-elevation in aVR were the most commonly observed ECG findings in these patients. Considering the prognostic implications and association of these changes with the severity of diseases, prompt decision-making regarding invasive management strategy could be helpful in improving the outcomes of these patients.

Study protocol for a pilot trial analysing the usability, validity and safety of an interventional health app programme for the structured prehabilitation of patients before major surgical interventions: the PROTEGO MAXIMA trial

IntroductionMajor surgery is associated with a high risk for postoperative complications, leading to an increase in mortality and morbidity, particularly in frail patients with a reduced cardiopulmonary reserve. Prehabilitation, including...

Association of abnormal p-wave parameters with brain MRI morphology: The atherosclerosis risk in communities neurocognitive study (ARIC-NCS).

Recent evidence indicates that abnormal P-wave parameters (PWPs)-ECG markers of atrial myopathy-are associated with incident dementia, independent of atrial fibrillation (AF) and clinical ischemic stroke. However, the mechanisms remain unclear and may include subclinical vascular brain injury. Hence, we evaluated the association of abnormal PWPs with brain MRI correlates of vascular brain injury in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS). ARIC-NCS participants who underwent 3T brain MRI scans in 2011-2013 were included. PWPs were measured from standard 12-lead ECGs. Brain MRI outcomes included cortical infarcts, lacunar infarcts, cerebral microhemorrhages, brain volumes, and white matter disease (WMD) volume. We used weighted multivariable logistic and linear regression to evaluate the associations of abnormal PWPs with brain MRI outcomes. Among 1715 participants (mean age, 76.1 years; 61% women; 29% Black), 797 (46%) had ≥1 abnormal PWP. After multivariable adjustment, including adjusting for prevalent AF, abnormal P-wave terminal force in lead V1 (aPTFV1) and prolonged P-wave duration (PPWD) were associated with increased odds of both cortical (OR 1.41; 95% CI, 1.14 to 1.74 and OR 1.30; 95% CI, 1.04 to 1.63, respectively) and lacunar infarcts (OR 1.36; 95% CI, 1.15 to 1.63 and OR 1.37; 95% CI, 1.15 to 1.65, respectively). Advanced interatrial block (aIAB) was associated with higher odds of subcortical microhemorrhage (OR 2.04; 95% CI, 1.36 to 3.06). Other than a significant association between aPTFV1 with lower parietal lobe volume, there were no other significant associations with brain or WMD volume. In this exploratory analysis of a US community-based cohort, ECG surrogates of atrial myopathy are associated with a higher prevalence of brain infarcts and microhemorrhage, suggesting subclinical vascular brain injury as a possible mechanism underlying the association of atrial myopathy with dementia.

Smartphone based 12 lead ECG as decision support in STEMI: a prospective, cross sectional study, non-randomised, single blinded and single-center study

Background: When a severe heart attack called a ST segment elevation myocardial infarction (STEMI) is not treated, heart muscle is killed per minute. Hence, early detection and treatment are essential for patient survival. The objectives of this study were to evaluate the accuracy for detection of (a) the ST elevation myocardial infarction of smartphone 12 lead ECG system in comparison to 12 lead gold standard hospital ECG machine; and (b) classification of STEMI in smartphone ECG and hospital ECG. Methods: This prospective, cross sectional study, non-randomised, single blinded and single-center study was carried out at Shri Mahant Indresh Hospital (SMIH), Dehradun, Uttarakhand, India from 30 May 2022 to 17 January 2023. All patients (n=154) with chest pain, shortness of breath, palpitation under the observations before and after the Percutaneous coronary intervention (PCI) like Coronary angioplasty, bypass surgery were enrolled from Critical care unit (CCU) and intensive critical care unit (ICCU). Results: Mean age (SD) was 53.90±11.7 years. The male gender (83.12%) shows the maximum frequency than female gender. True positive cases derived from confusion matrix for 12 lead standard ECG and smartphone ECG in comparison to cardiologist diagnosis was 113 as compared to 129 from 12 lead Gold standard. Sensitivity of smartphone Spandan ECG (87.5%) was comparable to gold standard 12 lead ECG (98.4%). And, specificity and PPV of smartphone Spandan ECG was recorded to be better than gold standard 12 Lead ECG. STEMI was detected correctly in 132 (86.3%) cases and 141 (80.85%) cases by smartphone ECG and 12 lead Gold standard, respectively. Conclusions: Spandan ECG device scored a high accuracy and sensitivity. The overall accuracy of smartphone ECG in detecting the STEMI increased by 5.45%, i.e. the significance rise in accuracy of computer interpretation when compared to the cardiologists’ diagnosis.

Prevalence and Predictors of Coronary Artery Ectasia among Delta Population

Background: Localized or widespread non-obstructive lesions of the epicardial coronary arteries, with a luminal dilatation 1.5 times that of the neighbouring normal segments or vessel diameter, have been identified as CAE. This research was performed to determine prevalence and predictors of CAE among Delta population in Egypt.&#x0D; Methods: This cross-sectional research was conducted on 2850 cases over the age of 18 who came for coronary angiography with positive non-invasive diagnostic tests, acute coronary syndrome and stable CAD. Cases were divided into two groups Group I: CAE cases (n =108) and Group II Non-ectasia cases (n =2742). All cases were subjected to history taking, clinical examination, laboratory investigations, standard 12-leads ECG, resting transthoracic echocardiography (TTE) and coronary angiography.&#x0D; Results: CAE occurred in 108 (3.79%) of the studied cases. Total cholesterol level, serum creatinine, were insignificantly different between both groups. CRP, NLR, MPV, and PLR, were significantly higher in CAE cases versus non-Ectasia cases CRP, NLR, PLR, and MPV is a good predicator for CAE, LVESD and LVEDD, were significantly higher in CAE group.&#x0D; Conclusions: The RCA was the most often affected coronary artery. The existence of CAE can be predicted using easily accessible clinical laboratory values such as CRP, Neutrophil to lymphocyte ratio, mean platelet volume, and platelet to lymphocyte ratio.