QRS Complex Research Articles

Fragmented QRS in patients with preeclampsia.

This study aims to investigate the prevalence, clinical correlates, and prognostic implications of fragmented QRS complexes (fQRS) in pregnant women with preeclampsia (PE), shedding light on the potential role of electrocardiographic markers in identifying cardiac involvement in hypertensive disorders of pregnancy. Patients with PE and age-matched low-risk control patients were recruited at a tertiary hospital between January 2015 and January 2023. A comprehensive assessment, including heart rate, PR duration, QRS duration, corrected QT duration, and fragmented QRS, was conducted by 12-lead electrocardiography. Baseline clinical characteristics, laboratory parameters, and electrocardiographic findings were compared between the study groups. 128 preeclampsia patients and 122 age- and comorbidity-matched controls were included in the study. The prevalence of fQRS was significantly higher in preeclamptic women compared to normotensive controls (14.1% vs. 3.3%, p = 0.04). ALT levels of pregnant women with preeclampsia and without preeclampsia groups were 43,77 (35.25-48.22) and 23,18 (13.75-33.00) (p: 0.038), respectively. In univariate regression analyses, Na and fragmented QRS were found to be associated with preeclampsia. (p: 0.016 and 0.009, respectively). After multivariable adjustment for variables, Na and fragmented QRS remained strongly associated with preeclampsia (OR: 4.787 (1.556-14.720), p: 0.06; 0.941 (0.893-0.992), p: 0.023, respectively). This study provides compelling evidence of an association between preeclampsia and fragmented QRS complexes, implicating electrolyte imbalances and hemodynamic stress as potential contributors to myocardial electrical instability in hypertensive disorders of pregnancy. Further research is warranted to validate these findings and improve risk stratification and clinical outcomes in affected women. Number: 2023/4705 Retrospectively Registered.

A Non-Invasive Fetal QRS Complex Detection Method Based on a Multi-Feature Fusion Neural Network

Fetal heart monitoring, as a crucial part of fetal monitoring, can accurately reflect the fetus’s health status in a timely manner. To address the issues of high computational cost, inability to observe fetal heart morphology, and insufficient accuracy associated with the traditional method of calculating the fetal heart rate using a four-channel maternal electrocardiogram (ECG), a method for extracting fetal QRS complexes from a single-channel non-invasive fetal ECG based on a multi-feature fusion neural network is proposed. Firstly, a signal entropy data quality detection algorithm based on the blind source separation method is designed to select maternal ECG signals that meet the quality requirements from all channel ECG data, followed by data preprocessing operations such as denoising and normalization on the signals. After being segmented by the sliding window method, the maternal ECG signals are calculated as data in four modes: time domain, frequency domain, time–frequency domain, and data eigenvalues. Finally, the deep neural network using three multi-feature fusion strategies—feature-level fusion, decision-level fusion, and model-level fusion—achieves the effect of quickly identifying fetal QRS complexes. Among the proposed networks, the one with the best performance has an accuracy of 95.85% and sensitivity of 97%.

Differential diagnosis of tachycardias with wide QRS complexes

Differential diagnosis of tachycardias with wide QRS complexes

Evaluating the predictive efficacy of real-time 3D echocardiography in cardiac resynchronization therapy

BackgroundThe aim of this study is to assess the predictive efficacy of real-time three-dimensional echocardiography (RT-3DE) and QRS wave duration in determining the response to cardiac resynchronization therapy (CRT) and assessing left ventricular systolic function pre- and post-CRT device implantation.MethodA total of 51 patients with heart failure undergoing CRT at the Second Affiliated Hospital of Nantong University between January 1, 2013, and October 31, 2020, were enrolled in this study. Traditional two-dimensional echocardiography and RT-3DE were performed pre and post-CRT, with QRS wave width data from electrocardiograms and additional clinical information collected. Patients were categorized into CRT responder (n = 36) and CRT non-responder (n = 15) groups based on their response to CRT device implantation. Comparative analyses were conducted on the general characteristics of both groups, as well as the predictive efficacy of RT-3DE and QRS wave width for CRT responsiveness and left ventricular systolic function. Data on the standard deviation (Tmsv16-SD, Tmsv12-SD, Tmsv6-SD) and maximum difference (Tmsv16-Dif, Tmsv12-Dif, Tmsv6-Dif) of left ventricular end-systolic volume (LVESV) at segments 16, 12, and 6, as well as QRS wave width, were collected and analyzed.ResultsThe indicators Tmsv6-Dif, Tmsv12-Dif, Tmsv16-Dif, Tmsv6-SD, Tmsv12-SD, Tmsv16-SD, and QRS wave width exhibited significantly higher values in the CRT responder group when compared to the CRT non-responder group (P < 0.05). Among these, Tmsv16-SD demonstrated superior predictive performance for post-CRT response, with a sensitivity of 88.9%, specificity of 80.0%, and a diagnostic cut-off value of 6.19%. This predictive capability exceeded that of the conventional indicator, QRS wave width.ConclusionRT-3DE enables accurate prediction of post-CRT patient response and significantly facilitates quantitative assessment of CRT therapy efficacy.

Clinical case on the use of the Bimod Vet® on a Doberman Pinscher puppy with atrial fibrillation

Similarly as in people, the diagnosis of cardiac diseases in dogs typically relies on echocardiography and electrocardiography, examinations that are usually reserved to cardiologists. A new medical device (footnote: Bimod Vet®) acquiring the electrocardiogram and phonocardiogram of dogs simultaneously and processing them with built-in algorithms has been developed to assist general practitioners in the management of cases suggestive of suffering from a cardiac disorder. This article displays the use of this device in a 5-month-old Doberman Pinscher puppy referred to a cardiologist and eventually diagnosed with cardiomyopathy of dilated phenotype with atrial fibrillation of unknown origin.In this case, Bimod Vet® enabled to acquire some cardiorespiratory parameters highly suggestive of a cardiac disorder, in a fast and stress-free manner. The rhythm analysis performed by the software lead to a suspicion of atrial fibrillation, based on a rapid and irregular rhythm, narrow QRS complexes and absence of P wave on the electrocardiogram tracing. A systolic murmur was also detected and the respiratory rate was measured.The device Bimod Vet® can therefore assist veterinarians in the detection of several abnormalities suggestive of an underlying cardiac disorder.

Study on the feasibility of distinguishing ventricular and pre-excited arrhythmia rhythms by a new algorithm

BackgroundThe differentiation and diagnosis of ventricular tachycardia (VT) and pre-excited tachycardia (PXT) remains a challenging task, especially when typical AV dissociation is not present. The purpose of this article is to study the feasibility of a new theoretical algorithm for identifying ventricular arrhythmias (VA) and pre-excited arrhythmias (PA) rhythms (which can be used to distinguish VT from PXT, etc.). MethodThis study involved the deduction of a new algorithm by combining knowledge of cardiac anatomy, vectorcardiography, and cardiac electrophysiology. The new algorithm evaluated the diagnostic value through intracardiac electrophysiology in 205 cases of VA and PA. The new algorithm diagnoses VA based on the following 4-step process:1.The QRS complex in leads II, III, and aVF shows a unidirectional R wave, and lead aVR shows a QS pattern.2.S waves are predominant in two or more of leads I, aVF, and V6.3.Lead V2 shows ≥3 phase waves or returning branch notching (note: returning branch refers to the band of QRS complexes returning to the baseline).4.Lead V5 shows a negative wave in the initial portion or returning branch notching.If none of these criteria are met, the diagnosis is PA. The diagnostic value of the new algorithm is compared with the Steurer algorithm and the Vereckei algorithm (diagnosed based on the QRS waveform characteristics of the two algorithms during electrophysiological verification, excluding the diagnosis of atrioventricular dissociation). ResultsThe new algorithm showed significant advantages in terms of AUC value (0.83 vs. 0.61 vs. 0.57), sensitivity (83.6 % vs. 23.3 % vs. 24.8 %), and accuracy (82.9 % vs. 48.3 % vs. 46.3 %) compared to the Steurer algorithm and Vereckei algorithm based on QRS waveform characteristics for diagnosing VA (137 cases) and PA (68 cases). This indicates that the new algorithm is more accurate in identifying idiopathic VA. While there was a significant difference in specificity between the New algorithm and Steurer algorithm (82.3 % vs. 98.5 %, p < 0.05), the difference with Vereckei algorithm (82.3 % vs. 89.7 %) was not significant.In the New algorithm, the sensitivity and specificity for each step are as follows:-Step 1: Sensitivity 34.3 %, Specificity 94.1 %.-Step 2: Sensitivity 24.1 %, Specificity 98.5 %.-Step 3: Sensitivity 18.3 %, Specificity 100 %.-Step 4: Sensitivity 6.6 %, Specificity 89.7 %.Step 1 had the highest AUC value, indicating the best overall diagnostic performance among all steps. Step 2 and Step 3 also performed well, while Step 4 had relatively poorer diagnostic performance. ConclusionThe new algorithm is suitable for identifying the origin of VA and PA rhythms.

Global R-wave peak time for diagnosis of left bundle branch capture

BackgroundQRS axis deviation and rS configuration in V6 affect the ability of V6 R-wave peak time (RWPT) criterion to discriminate capture type during left bundle branch area pacing (LBBAP). ObjectiveWe hypothesized that combining RWPTs from lateral leads: I, aVL, V5, and V6 may better reflect left ventricular activation time and that such a global RWPT may be insensitive to changes in QRS configuration. MethodsThe analysis included 519 electrocardiograms (ECGs) with nonselective left bundle branch pacing (nsLBBP) and 176 ECGs with left ventricular septal pacing (LVSP). Optimal RWPT cutoffs and area under the receiver operating curve (AUC) were determined for each lead and combinations of leads, to find the best RWPT criterion for discriminating nsLBBP from LVSP. Values were reported separately for healthy and diseased left conduction system groups. ResultsThe highest AUC of 97.1/89.2% was obtained for the global RWPT, which combined leads I and V6. The AUC for single-lead RWPT, was highest for lead I, followed by V6, V5, and aVL with AUC of 95.1/87.4%, 93.6/87.1%, 93.0/86.5%, and 84.8/74.6%, respectively. The global RWPT criterion was not affected by variations in QRS configuration, as V6 and I RWPTs often showed opposite responses to changes in axis. In contrast, all single-lead RWPT criteria were sensitive to axis deviation and QRS configuration. Diagnostically optimal RWPT cutoffs for global RWPT and lead I RWPT were 162.5/187.5 ms, and 81.5/90.5 ms, respectively. ConclusionThe global RWPT criterion allows a more accurate diagnosis of LBBAP capture type independent of QRS configuration and axis.

Electrocardiographic correlates of cardiac magnetic resonance findings in women with myocardial infarction with non-obstructive coronary arteries

BackgroundMyocardial infarction with nonobstructive coronary arteries (MINOCA) occurs in 6–15 % of MI patients. Cardiac magnetic resonance (CMR) imaging identifies MINOCA etiologies, but access may be limited. MethodsWe assessed associations between the index electrocardiogram (ECG) and CMR in MINOCA. Women with MI and < 50 % angiographic stenosis in all vessels were prospectively enrolled at 16 sites. CMR (median 6d from MI) was analyzed for late gadolinium enhancement (LGE), myocardial edema, and wall motion. We assessed ECGs for T-wave inversions (TWI), Q-waves (QW), ST-elevations (STE), ST-depressions (STD), and fragmented QRS complexes (fQRS). We calculated the DETERMINE score (# leads TWI + # fQRS +2*[# QW], excluding aVR, V1). ResultsAmong 112 women with interpretable ECG, 81.3 % (91/112) had abnormal ECG; 50 % (56/112) had ≥1 TWI. CMR was abnormal in 74.1 % (83/112), with LGE in 49.1 % (55/112) and myocardial edema in 61.6 % (69/112). DETERMINE score ≥ 3 was associated with abnormal CMR (adjusted odds ratio [aOR] aOR 6.06 [1.89, 24.6], p = 0.002) and LGE (aOR 3.10 [1.26, 8.00], p = 0.013), but not edema (aOR 1.86 [0.80, 4.43], p = 0.152). TWI was also associated with abnormal CMR and LGE after adjustment (aOR 3.13 [1.08, 10.1], p = 0.036, aOR 3.23 [1.27, 8.63], p = 0.013, respectively), but not edema (aOR 1.26 [0.54, 2.96], p = 0.589). Specificity for abnormal CMR was 0.83 for DETERMINE score ≥ 3 and 0.75 for TWI. No other ECG findings were associated with CMR abnormality. ConclusionDETERMINE score ≥ 3 and the presence of any TWI were associated with abnormal CMR and with LGE in MINOCA. Our findings demonstrate that the index ECG can provide insight on CMR findings but without sensitivity or specificity required to forgo the CMR. We reaffirm the central role of CMR in elucidating MINOCA pathophysiology.

Class activation map-based slicing-concatenation and contrastive learning: A novel strategy for record-level atrial fibrillation detection

BackgroundDeep learning-based models for atrial fibrillation (AF) detection require extensive training data, which often necessitates labor-intensive professional annotation. While data augmentation techniques have been employed to mitigate the scarcity of annotated electrocardiogram (ECG) data, specific augmentation methods tailored for recording-level ECG annotations are lacking. This gap hampers the development of robust deep learning models for AF detection. MethodsWe propose a novel strategy, a combination of Class Activation Map-based Slicing-Concatenation (CAM-SC) data augmentation and contrastive learning, to address the current challenges. Initially, a baseline model incorporating a global average pooling layer is trained for classification and to generate class activation maps (CAMs), which highlight indicative ECG segments. After that, in each recording, indicative and non-indicative segments are sliced. These segments are subsequently concatenated randomly based on starting and ending Q points of QRS complexes, with indicative segments preserved to maintain label correctness. Finally, the augmented dataset undergoes contrastive learning to learn general representations, thereby enhancing AF detection performance. ResultsUsing ResNet-101 as the baseline model, training with the augmented data yielded the highest F1-score of 0.861 on the Computing in Cardiology (CinC) Challenge 2017 dataset, a typical AF dataset with recording-level annotations. The metrics outperform most previous studies. ConclusionsThis study introduces an innovative data augmentation method specifically designed for recording-level ECG annotations, significantly enhancing AF detection using deep learning models. This approach has substantial implications for future AF detection research.

Mechanical dyssynchrony in patients with chronic heart failure and left bundle branch block

Background. The main problem in patient selection for cardiac resynchronization therapy (CRT) is the lack of unified approaches to the definition of mechanical dyssynchrony (MD) and selection criteria, particularly, in patients with left bundle branch block (LBBB).Aim: To study mechanical dyssynchrony indices and three-dimensional Echo (3DE) criteria of global and local contractility function in patients with chronic heart failure (CHF) and LBBB during different types of isolated left ventricle (LV) pacing.Methodology and Research Methods. The experimental intraoperative study involved 88 points obtained from 12 patients with CRT class IA indications and LBBB. During isolated LV pacing as part of CRT implantation procedure endocardial and epicardial pacing were obtained. Transesophageal Echo (TEE) cineloops recording and paced QRS complex morphology registrations by means of LabSystem Pro Electrophysiological Recording System (Bard Electrophysiology, USA) were performed during each stimulation episode. Philips Qlab 10 software was used for TEE data analysis.Results. The global (3D EF, 23.8 [22; 28.4], GLS, –5.33% [10.90%; –15.4%]) and local contractility (ExсAvg 3.5 [2.1; 5.6]) criteria and dyssyncrony indices (SDI-16, 14.9 [8.9; 23.1]) showed severe systolic dysfunction and intraventricular dyssynchrony – typical signs in this patient group, and differed significantly (3D EF, p = 0.003; GLS, p = 0.004; ExcAvg, p &lt; 0.001; Tmsv-6 SD, р = 0.03) depending on the stimulation method and site. A moderate direct correlation between SDI-16 and the QRS duration (common electical dyssynchrony criterium) and inverse correlation with ExcAvg and 3D LVEF also describes LV response.

Mechanisms underlying the spontaneous termination of torsades de pointes in an experimental model of long QT syndrome

BackgroundTorsades de pointes (TdP) represent a complex polymorphic ventricular tachycardia. While the triggering mechanisms of early afterdepolarization and increased dispersion of repolarization are well investigated, the sudden self-limiting termination remains poorly understood. ObjectiveThe purpose of this study was to perform analysis of TdP to investigate factors causing spontaneous termination. MethodsWe used a large data set from Langendorff experiments in isolated rabbit hearts in which drug-induced QT prolongation, bradycardia, and hypokalemia provoke TdP. We included 427 episodes with typical TdP characteristics of polymorphic self-terminating beats and twisting QRS complexes occurring in the presence of abnormal QT prolongation due to various different QT-prolonging drugs. The use of 8 monophasic action potential catheters allowed the characterization of action potential duration, configuration, and dispersion of repolarization beyond the capabilities of the surface electrocardiogram. To identify possible mechanisms of arrhythmia termination, the initial, midpoint, and terminal 3 ventricular complexes were analyzed for each episode. ResultsAn abrupt decrease in spatial dispersion over the course of a TdP episode was identified as a precursor for termination of TdP. Within the last 3 beats, a sudden significant decrease in the dispersion of repolarization was observed as a predictor of termination. In parallel, there was a decrease in action potential duration (action potential duration at 90% repolarization) before termination. Also, a change in action potential configuration (action potential duration at 90% repolarization/action potential duration at 50% repolarization ratio) in terms of the loss of action potential dome with a restitution of action potential triangulation was observed. ConclusionIn >400 TdP episodes, homogenization of myocardial repolarization with the recovery of an action potential configuration determines the termination of TdP episodes.

Clinical Characteristics and Outcomes inPatients With Atrial Fibrillation and Pathogenic TTN Variants.

TTN encodes a sarcomeric protein called titin. Pathogenic rare variants in TTN are the most common finding in patients with atrial fibrillation (AF) and positive genetic testing. This study sought to define the characteristics and outcomes in patients with AF and pathogenic TTN variants compared with genotype-negative patients with AF. Patients who presented initially with AF were enrolled in an AF registry. Retrospectively they underwent research sequencing for cardiomyopathy and arrhythmia genes. TTN(+) AF cases were defined as participants with pathogenic or likely pathogenic (P/LP) rare variants located in exons with high cardiac expression. They were matched 1:2 with control subjects with no P/LP variants. Phenotyping used retrospective manual chart review. Among 2794 participants; 57 (2.0%) TTN(+) AF cases were identified and matched with 114 control subjects. Low QRS complex voltage was present more often in TTN(+) AF cases (18% vs 5%; P< 0.01), with no difference in PR, QRS interval, or QTc. More TTN(+) AF cases had persistent AF at enrollment (44% vs 30%; P = 0.028) and had undergone multiple cardioversions (61% vs. 37%; P< 0.01). By end of follow-up (median 8.3 years; Q1, Q3: 4.5, 13.7 years), 11% of TTN(+) AF cases developed sustained ventricular tachycardia/ventricular fibrillation, 44% left ventricular (LV) systolic dysfunction (LV ejection fraction<50%), and 47% met a combined endpoint of sustained ventricular tachycardia/ventricular fibrillation or LV systolic dysfunction. TTN(+) AF patients undergo more cardioversions and have more persistent forms of AF. Approximately 50% develop LV systolic dysfunction and/or malignant ventricular arrhythmias. These results highlightthe need for diagnostic evaluation and management in TTN(+) patients beyond the usual care for AF.

A multicenter study of clinical predictors of positive pyrophosphate scintigraphy findings in the diagnosis of transthyretin amyloidosis

BackgroundThe prevalence of wild-type transthyretin (ATTR) amyloidosis is increasing with advancements in diagnostic techniques and growing awareness of the disease worldwide. 99mTc-labeled pyrophosphate (99mTc-PYP) scintigraphy exhibits high performance in diagnosing ATTR cardiac amyloidosis. This study aimed to validate the characteristics of patients with positive 99mTc-PYP scintigraphy results in a multicenter setting to provide more accurate case selection criteria. Methods and resultsIn total, 180 patients with suspected ATTR amyloidosis underwent 99mTc-PYP scintigraphy in participating institutions in Japan between January 2018 and July 2022. Of 135 patients included in the analysis, 62 were 99mTc-PYP-positive. Logistic regression analysis was performed, and the following five factors were adopted to create a scoring system, with each weighted according to its odds ratio value; 1 point was scored for the absence of hypertension, existence of peripheral entrapment neuropathy (carpal tunnel syndrome or spinal canal stenosis), conduction disturbance (the presence of QRS complex ≥120 ms, first-degree atrioventricular block, higher degree of atrioventricular block, or presence of pacemaker implantation), and left ventricular hypertrophy and 2 points for troponin I/T ≥ 0.06 ng/mL. 99mTc-PYP scintigraphy positivity rate in the 0-point group was 0 %, whereas that in the 6-point group was 100 %. The area under the curve of the criteria was 0.820 (95 % confidence interval, 0.752–0.888; P < 0.001). ConclusionsThe combination of clinical information, which is easily available in local clinics, can provide accurate pretest prediction of positive 99mTc-PYP scintigraphy results. This will help clinicians to make an early diagnosis of ATTR amyloidosis.

A Retrospective Analysis of Patients Presenting with Acute Hyperkalemia in an Emergency Care Setting.

We aimed to analyze the clinical characteristics and prognostic factors of patients with severe hyperkalemia in the emergency department. This retrospective cohort study included adult patients diagnosed with severe hyperkalemia who sought medical care at the emergency department of Aerospace Center Hospital between January 2018 and May 2022. Clinical data, including demographics, comorbidities, laboratory findings, and outcomes, were systematically collected. Patients were categorized into survival and deceased groups based on in-hospital mortality. Comparative analysis between these groups identified significant differences, highlighting key clinically covariates. Binary logistic regression was employed to determine the primary factors influencing patient outcomes. Of 90 patients diagnosed with severe hyperkalemia, 64 were in the survival group, and 26 in the deceased group. Binary logistic regression identified several significant predictors of mortality, including higher APACHE II scores (odds ratio [OR] 1.41, P = 0.02), widened QRS wave on electrocardiogram (ECG) (OR 79.39, P = 0.04), and elevated serum potassium levels (OR 1.3, P = 0.04). In contrast, emergency blood purification was associated with a reduced mortality rate (OR 0.29, P = 0.03). Key risk factors for mortality in patients with severe hyperkalemia include widened QRS wave on ECG, elevated APACHE II score, and high serum potassium level. Timely correction of hyperkalemia through emergency blood purification significantly improves patient outcomes.

Correlation of serum zinc and magnesium with reduced heart rate variability in male Parkinson’s disease patients

Background: Parkinson’s disease (PD) is a neurological disorder associated with altered cardiac autonomic function. Heart rate variability (HRV) analysis is a tool to assess the cardiac autonomic status. Altered serum zinc (Zn) and magnesium (Mg) levels are observed in PD. The serum Zn and Mg alteration is associated with nerve function impairment. Objective: To evaluate the relationship between serum zinc, magnesium, and time domain measures of HRV in male patients with PD. Methods: This observational analytical cross-sectional study was conducted in 2023on 30 newly diagnosed male PD patients aged 50-60 years. In this study, 30 healthy volunteers were the control. The 30 patients were divided into different categories based on serum mineral levels. The HRV was recorded by Power Lab 8/35, AD Instruments, Australia and the time domain measures of HRV were used in data analysis. The serum Zn and Mg levels were measured by atomic absorption spectrophotometry. Independent sample ‘t’ test and Pearson’s correlation coefficient test were used for statistical analysis and p&lt;0.05 was considered statistical significance. Results: Significantly higher mean HR (Heart rate) (p&lt;0.01) and significantly lower mean RR (Normal to normal QRS complex) interval,CVRR (Coefficient variation of RR interval) (p&lt;0.01), SDRR (Standard deviation of the RR intervals), SDSD (Standard deviation of the difference between successive RR intervals), RMSSD (Square root of mean squared differences of successive RR intervals), pRR50% (Proportion of RR interval with duration &gt;50 ms) (p&lt;0.001)were observed in PD patients compared to control. In PD patients, significantly lower (p&lt;0.001) serum Zn and significantly higher (p&lt;0.01) serum Mg were observed compared to control. In addition,significant decrement was observed in SDRR, CVRR (p&lt;0.05), SDSD, RMSSD, and pRR50% (p&lt;0.01) in hypozincemic PD patients compared to normozincemic patients. On correlation analysis, significant positive correlations of serum Zn were observed with SDRR (p&lt;0.05),SDSD (p&lt;0.001), RMSSD (p&lt;0.001) and pRR50% (p&lt;0.01). Moreover,serum Mg was positively correlated with SDRR (p&lt;0.05) in PD patients. Conclusion: Hypozincemia and magnesium were directly related to reduced HRV in male PD patients. J Bangladesh Soc Physiol 2023;18(2): 63-71

ELECTRICAL CARDIAC REMODELING IN MEN WITH ARTERIAL HYPERTENSION AFFECTED BY PSORIASIS VULGARIS

Psoriasis and arterial hypertension are often observed in men of working age. Biologically active molecules such as insulin-like growth factor, vascular endothelial growth factor (VEGF), etc. play a significant role in the pathogenesis of these diseases. These factors contribute to cardiac remodeling, which is one of the arrhythmogenic substrates. The aim of the study was a comprehensive assessment of electrical cardiac parameters in male patients suffering from arterial hypertension affected by psoriasis vulgaris. Materials and Methods. The study was conducted in 2021–2023. It involved 110 male patients undergoing outpatient treatment for stage 2 arterial hypertension. Their average age was 52.4±6.9 years. The patients were divided into 2 groups: Group 1 (comparison) – 50 patients with arterial hypertension; Group 2 (control) – 60 patients with hypertension and psoriasis vulgaris in the progressive moderate severity stage (PASI index between 10 and 20). Results. In males with arterial hypertension affected by psoriasis vulgaris, late ventricular potentials were statistically significantly more common (33 %) compared to those with arterial hypertension without psoriasis (16 %) (χ²=4.32; p=0.048). In patients with both arterial hypertension and psoriasis, a greater number of local peaks in the ventricular complex along all Frank orthogonal leads were registered in spectral-temporal mapping of the QRS complex. Conclusion. The concomitant psoriasis vulgaris in males with arterial hypertension negatively effects the parameters of cardiac electrical remodeling.

Comparison of pathological electrocardiographic changes between long-term kidney transplant recipients and hemodialysis patients

Aims: We aimed to reveal electrocardiographic changes in kidney transplant recipients (KTRs) compared with hemodialysis patients. Methods: We included 70 KTRs who had underwent a kidney transplantation for more than one year and 84 patients who had been on hemodialysis for more than one year. We recorded age, sex, body-mass index (BMI) (kg/m2), primary disease (makes chronic kidney disease) and duration of hemodialysis treatment. Standard measurements such as heart rate (HR), P wave, PR interval, P axis, QRS complex, QRS axis, T axis, QT interval and QTc interval were performed for all electrocardiography (ECG). Results: KTRs were younger than the hemodialysis patients group (HPG) (31.5 vs. 54.5, p

Electrocardiographic Patterns and Arrhythmias in Cardiac Amyloidosis: From Diagnosis to Therapeutic Management-A Narrative Review.

Electrophysiological aspects of cardiac amyloidosis (CA) are still poorly explored compared to other aspects of the disease. However, electrocardiogram (ECG) abnormalities play an important role in CA diagnosis and prognosis and the management of arrhythmias is a crucial part of CA treatment. Low voltages and a pseudonecrosis pattern with poor R-wave progression in precordial leads are especially common findings. These are useful for CA diagnosis and risk stratification, especially when combined with clinical or echocardiographic findings. Both ventricular and supraventricular arrhythmias are common in CA, especially in transthyretin amyloidosis (ATTR), and their prevalence is related to disease progression. Sustained and non-sustained ventricular tachycardias' prognostic role is still debated, and, to date, there is a lack of specific indications for implantable cardiac defibrillator (ICD). On the other hand, atrial fibrillation (AF) is the most common supraventricular arrhythmia with a prevalence of up to 88% of ATTR patients. Anticoagulation should be considered irrespective of CHADsVA score. Furthermore, even if AF seems to not be an independent prognostic factor in CA, its treatment for symptom control is still crucial. Finally, conduction disturbances and bradyarrhythmias are also common, requiring pacemaker implantation in up to 40% of patients.

Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems

Abstract Electrocardiogram (ECG) recognition systems now play a leading role in the early detection of cardiovascular diseases. However, the explanation of judgments made by deep learning models in these systems is prominent for clinical acceptance. This article reveals the effect of transfer learning in ECG recognition systems on decision precision. This article investigated the role of transfer learning in ECG image classification using a customized convolutional neural network (CNN) with and without a VGG16 architecture. The customized CNN model with the VGG16 achieved a good test accuracy of 98.40%. Gradient-weighted class activation mapping (Grad-CAM), for this model, gave the wrong information because it focused on parts of the ECG that were not important for making decisions instead of features necessary for clinical diagnosis, like the P wave, QRS complex, and T wave. A proposed model that only used customized CNN layers and did not use transfer learning performed 99.08% on tests gave correct Grad-CAM explanations and correctly identified the influencing areas of decision-making in the ECG image. Because of these results, it seems that transfer learning might provide good performance metrics, but it might also make things harder to understand, which could make it harder for deep learning models that use ECG recognition to be reliable for diagnosis. This article concludes with a call for careful consideration when using transfer learning in the medical field, as model explanations resulting from such learning may not be appropriate when it comes to domain-specific interpretations.

ECG Biometric Verification Incorporating Different Physiological Conditions

The liveness detection criteria of biological signals have become one of the reasons it has been introduced as an ideal biometric recognition system. Electrocardiogram (ECG) is one of the biological signals that records the rhythms of human’s heart in the form of PQRST waves proves the uniqueness of the ECG itself making it suitable to be applied as biometric mechanisms. Previous research had shown the success of proving ECG as a biometric modality however most experimentations were done in normal conditions. Thus, to improve the current research, this work proposed a robust biometric identification by introducing ECG signals incorporating various physiological conditions. After the data collection of cycling, walking, climbing stairs, and jogging, the signals are pre-processed by using MODWT to remove unwanted noises produced during data collection process. Then, Pan Tompkins algorithm is used to segment the QRS complexes. The segmented signals are overlapped and align with each other to observe its pattern. Next, the QRS waveform is classified by using various class of SVM by considering two factors which are same physiological conditions and different physiological conditions. The subjects are compared between same and different physiological condition to validate the proposed method. The results show that the precision achieved up to 100%. In average, Gaussian SVM gives highest precision when compared to other type of SVM classifiers suggesting that Gaussian SVM is the most appropriate to be applied for person identification. Thus, the proposed method proves that biometric recognition can be performed regardless of different physiological conditions and can be applied in real life scenarios.