Electrocardiographic Analysis Research Articles

12. Predicting Mortality in COVID-19 Patients with Hypertension using ECLA Score (ECG, Chest X-Ray and Laboratory Analysis)

Background: COVID-19 patients with hypertension are at higher risk for complications and have higher mortality rate. Rapid scoring can be important to determine the prognosis of COVID-19. Objective: We developed a scoring system to predict mortality to facilitate coordinated care planning. Methods: This study included 406 data confirmed COVID-19 with hypertension in East Java. Electrocardiography (ECG), laboratory analysis and chest x-ray (CXR) findings are examined to develop scoring system to predict mortality. Results: After multivariable adjustment and stepwise elimination, seven of 13 variables: cardiomegaly (p = 0.036), sinus tachycardia (p = 0.001), ST-segment abnormalities (p = 0.036), right bundle branch block (p = 0.008), left bundle branch block (p = 0.046), left ventricle hypertrophy (p = 0,023), and creatinine (p = 0.000) were retained and compared. Each variable has a different risk score and is used to classify the patients into risk groups: low risk (0–2 points), moderate risk (3–6 points), and high risk ($ 7 points), determined by calculating the sum of the risk in the scoring system. ROC curve analysis of the ability of the scoring system to predict mortality showed an area under the curve (AUC) of 75,8% (confidence interval: 95%), a cutoff point of # 1,5 with a sensitivity of 76,3% and specificity of 62,1%. Conclusion: We concluded that the final model has the potential to predict mortality in hypertensive COVID-19 patients during hospital admission. The mortality rate is therefore expected to regress following risk group determination using our scoring model, which would yield a more comprehensive treatment plan.

Electrocardiographic and biochemical analysis of anthracycline induced cardiotoxicity in breast cancer patients from Southern Sri Lanka

BackgroundThe clinical application of anthracycline chemotherapy is hindered due to the cumulative dose-dependent cardiotoxicity followed by the oxidative stress initiated during the mechanism of action of anthracyclines. Due to a lack of prevalence data regarding anthracycline-induced cardiotoxicity in Sri Lanka, this study was conducted to determine the prevalence of cardiotoxicity among breast cancer patients in Southern Sri Lanka in terms of electrocardiographic and cardiac biomarker investigations.MethodsA cross-sectional study with longitudinal follow-up was conducted among 196 cancer patients at the Teaching Hospital, Karapitiya, Sri Lanka to determine the incidence of acute and early-onset chronic cardiotoxicity. Data on electrocardiography and cardiac biomarkers were collected from each patient, one day before anthracycline (doxorubicin and epirubicin) chemotherapy, one day after the first dose, one day and six months after the last dose of anthracycline chemotherapy.ResultsPrevalence of sub-clinical anthracycline-induced cardiotoxicity six months after the completion of anthracycline chemotherapy was significantly higher (p < 0.05) and there were strong, significant (p < 0.05) associations among echocardiography, electrocardiography measurements and cardiac biomarkers including troponin I and N-terminal pro-brain natriuretic peptides. The cumulative anthracycline dose, > 350 mg/m2 was the most significant risk factor associated with the sub-clinical cardiotoxicity in breast cancer patients under study.ConclusionSince these results confirmed the unavoidable cardiotoxic changes following anthracycline chemotherapy, it is recommended to carry out long-term follow-ups in all patients who were treated with anthracycline therapy to increase their quality of life as cancer survivors.

Role of P Wave Duration and Tissue Doppler Imaging as Predictive Indicators for Paroxysmal Atrial Fibrillation in Hypertensive Patients

Background: Atrial fibrillation (AF) is the most prevalent chronic arrhythmia in the heart. AF accounts for one-third of rhythm disorder hospitalizations. AF increases profoundly the risk of stroke, heart failure, and death. This study used P-wave and transthoracic echocardiography with tissue Doppler imaging (TDI) to determine paroxysmal AF predictors in hypertensive individuals.&#x0D; Methods: This case control study was performed on 100 hypertensive adult patients. They were classified into two equal group: Group I included hypertensive patients diagnosed to have paroxysmal AF. Group II (control group) included hypertensive patients with normal sinus rhythm. All subjects were subjected to electrocardiographic and conventional and tissue Doppler Imaging measurements.&#x0D; Results: Pmax had significantly increased in PAF patients compared to sinus rhythm patients. PAL, PAR, PAI, LR, LI and IR had significantly increased in PAF patients compared to sinus rhythm patients. In Multivariate logistic regression analysis, Pmax, PAL, PAI, PAR, LR, LI and IR were found to be independent predictors for PAF. Therefore, Pmax, PAL PAI, PAR, LR, LI and IR were found to be significant predictors for PAF. Best cut-off values for Pmax, PAL, PAI, PAR, LR, LI and IR were: (118, 81, 61, 49.9, 34, 20 and 16 ms) with sensitivity (76, 96, 96, 88, 82, 86 and 77.5 ), specificity (84, 100, 98, 92, 78, 82 and 76) and the AUC of (0.850, 0.979, 0.987, 0.961, 0.836, 0.891 and 0.798) respectively.&#x0D; Conclusions: Electrocardiographic P-wave analysis and echocardiographic TDI may identify hypertension patients at risk for paroxysmal AF, since the combination of Pmax and TDI may help in predicting the development of AF in hypertensive individuals.

QT interval instability and QRS interval dispersion in healthy cats and cats with a hypertrophic cardiomyopathy phenotype.

Hypertrophic cardiomyopathy (HCM) is the most common heart disease in cats. Electrocardiographic (ECG) analysis can help with the diagnosis of HCM and also in the investigation of the secondary consequences of the disease. This study investigated ECG markers of QT interval variability (total instability [TI], short-term instability [STI], long-term instability [LTI], QT variance [QTv]), mean QT interval (QTa) and QT interval corrected for heart rate (QTac), as well as the duration (QRSd) and dispersion (QRSv) of the QRS interval in healthy cats and in those with HCM. Data were collected from 63 domestic cats: 40 in the control group and 23 in the HCM group. Fifty consecutive QT intervals were recorded for all cats and then QTa, QTac, QTv, TI, LTI and STI were calculated. QRSd and QRSv were also obtained for all animals. A Mann-Whitney U-test was used for group comparison. Receiver operating characteristic curves were plotted to evaluate the sensitivity and specificity of all markers for HCM. Logistic regression analysis was performed to assess the risks of cats having HCM, based on the studied indexes. QTa (P <0.01), QTac (P <0.01), QRSd (P <0.01) and STI (P = 0.02) were higher in the HCM group. QTa >158.8 ms, QTac >27.4 ms and QRSd >0.045 s had an accuracy of 77.4%, 68.2% and 80.9%, respectively, in detecting HCM. Logistic regression showed that cats with QTa >158 ms, QTac >27.4 ms and QRSd >0.045 s had a 1.58-, 1,23- and 6.5-fold higher risk, respectively, of developing HCM. Cats with HCM had higher ventricular instability as assessed by STI and showed a prolongation of the QT and QRS intervals via the QTa, QTac and QRSd markers. These markers show potential as ancillary screening tools for identifying the presence of HCM.

Effects of balloon pulmonary angioplasty procedure on electrocardiographic parameters in patients with chronic thromboembolic pulmonary hypertension

AimThe aim of the present study was to evaluate the value of electrocardiography (ECG) in predicting postoperative hemodynamic improvement in patients with chronic thromboembolic pulmonary hypertension (CTEPH) undergoing balloon pulmonary angioplasty (BPA). Material and methodsA total of 32 patients were included in the study. During ECG analysis, parameters that have been suggested to be related to right ventricular hypertrophy and/or dilatation were evaluated. The significance of the change in each parameter obtained at the pre-BPA visit and at the scheduled control visit 6 months after BPA was tested. In addition to ECG analysis, data related to right heart catheterization (RHC) and echocardiography, B-type natriuretic peptide (BNP) levels and World Health Organization (WHO) functional classifications of all patients were also recorded. The relationship between the amount of possible change in ECG parameters and the amount of possible change in hemodynamic parameters was investigated. ResultsThe Daniel score, which has been suggested to have prognostic value in acute pulmonary embolism, decreased from 8.22 ± 5.68 to 6.56 ± 5.55 after the BPA procedure (p: 0.035). Among all parameters studied, only T wave height (V2 t) in V2 derivation changed significantly from −0.77 ± 2.39 to 1.27 ± 2.58 mm (p: 0.036). The amount of change in V2 T was found to significantly correlate with the amount of change in systolic right ventricular pressure, mean pulmonary artery pressure, pulmonary vascular resistance, and systemic vascular resistance. ConclusionPostprocedural T wave changes in lead V2 might serve as a marker of hemodynamic improvement in patients with CTEPH who undergo BPA.

COVID-19's influence on cardiac function: a machine learning perspective on ECG analysis.

In December 2019, the spread of the SARS-CoV-2 virus to the world gave rise to probably the biggest public health problem in the world: the COVID-19 pandemic. Initially seen only as a disease of the respiratory system, COVID-19 is actually a blood disease with effects on the respiratory tract. Considering its influence on hematological parameters, how does COVID-19 affect cardiac function? Is it possible to support the clinical diagnosis of COVID-19 from the automatic analysis of electrocardiography? In this work, we sought to investigate how COVID-19 affects cardiac function using a machine learning approach to analyze electrocardiography (ECG) signals. We used a public database of ECG signals expressed as photographs of printed signals, obtained in the context of emergency care. This database has signals associated with abnormal heartbeat, myocardial infarction, history of myocardial infarction, COVID-19, and healthy heartbeat. We propose a system to support the diagnosis of COVID-19 based on hybrid deep architectures composed of pre-trained convolutional neural networks for feature extraction and Random Forests for classification. We investigated the LeNet, ResNet, and VGG16 networks. The best results were obtained with the VGG16 and Random Forest network with 100 trees, with attribute selection using particle swarm optimization. The instance size has been reduced from 4096 to 773 attributes. In the validation step, we obtained an accuracy of 94%, kappa index of 0.91, and sensitivity, specificity, and area under the ROC curve of 100%. This work showed that the influence of COVID-19 on cardiac function is quite considerable: COVID-19 did not present confusion with any heart disease, nor with signs of healthy individuals. It is also possible to build a solution to support the clinical diagnosis of COVID-19 in the context of emergency care from a non-invasive and technologically scalable solution, based on hybrid deep learning architectures.

Electrocardiographic Analysis of Patients with Suspicion of Acute Coronary Syndrome in Yaounde, Cameroon

Electrocardiographic Analysis of Patients with Suspicion of Acute Coronary Syndrome in Yaounde, Cameroon

Atrial fibrillation can be diagnosed using a combined wrist-worn photoplethysmography and electrocardiography

Abstract Background Current ESC Clinical Practice Guideline for management of atrial fibrillation requires a minimum of 30-seconds of atrial fibrillation (AF) to be visually confirmed from an electrocardiography (ECG) recording for diagnosis. Single-channel ECG recorded from any measurement lead is sufficient. The current method of 24–48 h Holter ECG may not detect rarely occurring AF episodes, and thus extended duration recording devices are needed. Intermittent portable ECG devices intended for clinical use exist but those lack continuous rhythm monitoring and are thus unable to notify the user in case of asymptomatic episode. Purpose We evaluated the performance of a wrist-worn solution (Fig. 1) intended for clinical use that combines continuous photoplethysmography (PPG) -based rhythm assessment with intermittent ECG measurements in the detection of atrial fibrillation in ambulatory conditions. Methods 30 adult patients with previous diagnosis of AF were recruited for 48-hour measurements. Simultaneous 5-lead Holter monitoring was used as the reference. The patients were taking intermittent ECG measurements at pre-scheduled times (4 times a day), when notified by the device (irregular rhythm detected by PPG), and if feeling symptoms of AF. Results The obtained sensitivity and specificity for PPG-based AF detection were 95.5% and 99.2%, respectively when evaluated in 5-minute segments. Only the segments during which adequate amount, approximately 30-seconds, of good quality PPG data was available, were considered in the analysis. On average this equals 54% of the segments. Patients took in total 456 30-second ECG measurements. Out of these 411 and 392 were assessed as analysable quality by ECG algorithm and visually by two cardiologists, HS and KK, respectively. Automatic ECG analysis algorithm labelled ECG measurements taken during atrial fibrillation correctly as “Possible arrhythmia” with 95.7% sensitivity and 92.0% specificity. 99.5% of the analysable quality ECGs measured during AF were marked with any type of label e.g., tachycardia that highlights them to the clinician. An example ECG measurement with markings of the analysis algorithm an overall classification is shown in Fig. 2. All patients having AF during the 48-hour monitoring (14/30) were correctly identified based on the wrist device data. Conclusion Based on the obtained results, wrist-worn device combining continuous PPG and intermittent ECG measurements can be reliably used in detecting atrial fibrillation in ambulatory conditions. The user-friendliness and unobtrusiveness of wrist-worn technology enables virtually unlimited monitoring time thus facilitating the detection of rarely occurring AF episodes. The information of continuous rhythm monitoring can also be used for the estimation of AF burden. The solution used in the study has received medical device CE certification in early 2022. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The study was funded by PulseOn company.

Carotid Artery Revascularization Improves Cardiac Sympathetic Nerve Activity in Patients With Carotid Artery Stenosis.

The carotid sinus baroreceptor reflex controls the neural regulation of blood pressure. Baroreceptor disorders due to carotid sinus atherosclerosis have detrimental cardiovascular effects. This study investigated the medium-term effects of carotid artery revascularization (CAR) on sympathetic and cardiac function and systemic blood pressure variability in patients with carotid artery stenosis. This study included 21 consecutive patients (median age 70 years, 18 men) with carotid artery stenosis scheduled for CAR. 123I metaiodobenzylguanidine (MIBG) scintigraphy, echocardiography, brain natriuretic peptide levels, 24-h Holter electrocardiography (ECG), and ambulatory blood pressure monitoring assessed approximately 3 months postoperatively were compared to preoperative data. All 21 enrolled patients underwent CAR. Carotid artery stenting was done in three patients with cardiovascular risk or anatomical difficult for carotid endarterectomy. The mean common carotid artery end-diastolic velocity improved significantly (P < 0.01) by 1.6-fold, from 10.8 ± 3.2 to 16.1 ± 7.1 cm/s. In 123I-MIBG scintigraphy, the heart-to-mediastinum (H/M) count ratio was significantly higher than preoperatively (from 2.66 ± 0.48 to 2.86 ± 0.56, P = 0.03). Holter ECG analysis revealed a significant decrease in the low-frequency/high-frequency (LF/HF) ratio compared to preoperatively (from 2.17 ± 1.20 to 1.62 ± 0.68, P = 0.04). These findings suggest decreased myocardial sympathetic activation. In echocardiography, the tissue Doppler-derived e' increased, and E/e' decreased significantly (P < 0.05) from 11.7 ± 5.1 to 10.1 ± 4.0, suggesting an improved left ventricular diastolic capacity. The mean 24-h and nighttime blood pressures were unchanged. CAR in patients with carotid stenosis may provide medium-term improvement in cardiac sympathetic nerve activity and left ventricular diastolic dysfunction.

Predicting Patients With Troponin Positive Chest Pain and Unobstructed Coronary Arteries With Electrocardiogram, Troponin Kinetics and GRACE Score.

Troponin positive chest-pain with unobstructed coronary arteries (TPCP-UCA), occurs in 6% of cases of patients presenting with acute coronary syndrome (ACS). Whilst TPCP-UCA patients are known to be younger with less cardiovascular risk factors when compared to obstructive coronary disease (MICAD), no validated methods exist to reliably delineate these two conditions prior to coronary angiography. We analysed 142 patients with MICAD and 127 patients with TPCP-UCA from 2015 to 2019. Several key predetermined clinical, biochemical and electrocardiograph (ECG) parameters, as well as Global Registry of Acute Coronary Events (GRACE) score, were collected for all patients. All TPCP-UCA patients underwent cardiac magnetic resonance imaging (cMRI). Patients with TPCP-UCA were younger than MICAD (44 vs 68 yrs, p<0.01), and with less cardiac risk factors of hypertension (31% vs 68%, p<0.01), hypercholesterolaemia (23% vs 56%, p<0.01), diabetes (11% vs 45%, p<0.01), prior ischaemic heart disease (8% vs 42%, p<0.01) and smoking history (29% vs 50%, p<0.01). Peak troponin (MICAD 2,084.5 ng/L vs TPCP-UCA 847.0 ng/L, p=0.02), serial-to-initial troponin ratio (MICAD 13.5 vs TPCP-UCA 5.1, p<0.01), and peak-to-initial troponin ratio (MICAD 69.6 vs TPCP-UCA 14.0, p<0.01) were all higher in the MICAD group. GRACE scores were significantly different across the two cohorts (TPCP UCA 74 vs MICAD 106, p<0.01), with a receiver operator characteristic (ROC) curve statistic of 0.794 (95% CI 0.739-0.850). On ECG analysis, MICAD had greater prevalence and sum of ST depression (40% vs 19% p<0.01; 1.6 mm vs 0.44 mm, p<0.01) and T wave inversion (37% vs 17%, p<0.01), whilst TPCP-UCA had greater presence of PR depression (20% vs 3% p<0.01), and longer repolarisation (T wave peak to end 89 ms vs 83 ms, p=0.04; T wave peak to end/corrected QT 0.208 ms vs 0.193 ms, p=0.03). All TPCP-UCA patients underwent cMRI. Aetiology was found in 82% of cases, with the leading diagnosis being myocarditis (58%), followed by infarction (8%), whilst 18% had a normal cMRI. TPCP-UCA is an important differential for patients presenting with ACS, and has several key demographic, biochemical and electrocardiographic differences. The present findings are hypothesis generating, thus prospective studies are required to determine and validate potential clinical utility.

Myocardial infarction detection using ITD, DWT and deterministic learning based on ECG signals.

Nowadays, cardiovascular diseases (CVD) is one of the prime causes of human mortality, which has received tremendous and elaborative research interests regarding the prevention issue. Myocardial ischemia is a kind of CVD which will lead to myocardial infarction (MI). The diagnostic criterion of MI is supplemented with clinical judgement and several electrocardiographic (ECG) or vectorcardiographic (VCG) programs. However the visual inspection of ECG or VCG signals by cardiologists is tedious, laborious and subjective. To overcome such disadvantages, numerous MI detection techniques including signal processing and artificial intelligence tools have been developed. In this study, we propose a novel technique for automatic detection of MI based on disparity of cardiac system dynamics and synthesis of the standard 12-lead and Frank XYZ leads. First, 12-lead ECG signals are synthesized with Frank XYZ leads to build a hybrid 4-dimensional cardiac vector, which is decomposed into a series of proper rotation components (PRCs) by using the intrinsic time-scale decomposition (ITD) method. The novel cardiac vector may fully reflect the pathological alterations provoked by MI and may be correlated to the disparity of cardiac system dynamics between healthy and MI subjects. ITD is employed to measure the variability of cardiac vector and the first PRCs are extracted as predominant PRCs which contain most of the cardiac vector's energy. Second, four levels discrete wavelet transform with third-order Daubechies (db3) wavelet function is employed to decompose the predominant PRCs into different frequency bands, which combines with three-dimensional phase space reconstruction to derive features. The properties associated with the cardiac system dynamics are preserved. Since the frequency components above 40 Hz are lack of use in ECG analysis, in order to reduce the feature dimension, the advisable sub-band (D4) is selected for feature acquisition. Third, neural networks are then used to model, identify and classify cardiac system dynamics between normal (healthy) and MI cardiac vector signals. The difference of cardiac system dynamics between healthy control and MI cardiac vector is computed and used for the detection of MI based on a bank of estimators. Finally, experiments are carried out on the PhysioNet PTB database to assess the effectiveness of the proposed method, in which conventional 12-lead and Frank XYZ leads ECG signal fragments from 148 patients with MI and 52 healthy controls were extracted. By using the tenfold cross-validation style, the achieved average classification accuracy is reported to be 98.20%. Results verify the effectiveness of the proposed method which can serve as a potential candidate for the automatic detection of MI in the clinical application.

Electrocardiographic signs of impaired depolarization (fragmented QRS, early ventricular repolarization, etc.) as markers of left ventricular systolic dysfunction

Aim. To study the relationship between a decrease in left ventricular (LV) ejection fraction (EF) and conventional electrocardiographic (ECG) signs associated with myocardial structure changes (pathological Q wave, ventricular arrhythmias), and relatively novel and less studied (fragmented QRS (fQRS), early ventricular repolarization (EVR)) and to evaluate their significance for identifying patients with mildly-reduced EF (mrEF).Material and methods. The study included 148 patients who were treated and examined at the Almazov National Medical Research Center. During the ECG analysis, fQRS, EVR, pathological Q wave, and ventricular arrhythmias (VAs) were assessed. Echocardiography data were analyzed. Statistical processing was carried out, including Fisher and chi-squared test, as well as correlation and ROC analysis.Results. Depending on the EF level, patients were divided into three groups: group 1 — patients with reduced EF (rEF) (&lt;40%); group 2 — patients with mrEF (40-49%); group 3 — patients with preserved EF (pEF) (&gt;50%). In the 1st group (with rEF), fQRS was registered in 16 (51,6%) patients, in the 2nd (with mrEF) — in 13 (44,8%), in the 3rd (with EF &gt;50%) — in 16 (18,2%). Pathological Q wave was detected in the 1st group (rEF) in 20 (65%) patients, in the 2nd (mrEF) — in 10 (35%); in the 3rd (pEF) — in 15 (18%) (p&lt;0,001). ROC analysis found that fQRS is more important for identifying patients with mrEF. In the 1st group (rEF), EVR was registered in 2 (6,5%) patients, in the 2nd (pEF) — in 2 (6,9%), in the 3rd (EF&gt;50%) — in 11 (12,5%); the differences were not significant (p=0,5). The relationship of EVR, the number of PVCs and the presence of ventricular tachycardia with EF was not revealed.Conclusion. FQRS is significantly more often observed with a decrease in EF and may be a marker of an mildly-reduced EF. There were no significant correlations between EVR and EF. There was also no relationship between VAs and LV systolic dysfunction.

Inferior Vena Cava as a Trigger for Paroxysmal Atrial Fibrillation: Incidence, Characteristics, and Implications.

Identifying nonpulmonary vein triggers during atrial fibrillation (AF) ablation is of great importance. Currently, there are limited data on AF triggered by the inferior vena cava (IVC). This study was performed to investigate the incidence, characteristics, and implications of IVC triggers for AF. A total of 661 patients who underwent initial paroxysmal AF ablation were included. After pulmonary vein isolation, ectopic beats that triggered AF were further studied. Activation mapping and angiography were performed to confirm the location of ectopic origin. Electrocardiographic analysis of the ectopic P-wave (P'-wave) was performed. Six patients (0.91%) with AF triggered by the IVC were confirmed. The mean distance from the earliest activation site to the IVC ostium was 6.8 ± 2.5mm (5.2 to 11.2mm). Furthermore, the arrhythmogenic foci within the IVCwere all located at the apical hemisphere of the IVC (3 at the septal side and 3 at the anterior side). A total of 2.3±0.5 applications of radiofrequency energy were delivered to eliminate IVC triggers. The mean duration of the P'wave was 91.2 ± 11.2 milliseconds (81 to 108 milliseconds), which was narrower than that of the sinus P-wave (115.2±19.3 milliseconds [87 to 139 milliseconds]; P = 0.002). Moreover, the configuration of all P' waves in the inferior leads was negative. During a mean follow-up period of 25.5 ± 7.3months, all 6 patients remained arrhythmia free without antiarrhythmic drugs. IVC trigger, a rare but latent source of paroxysmal AF, could be identified and safely eliminated by focal radiofrequency ablation. Ectopic beats originating from the IVC presented with narrow P'-wave duration and negative P'waves in all inferior leads.

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

(1) Background: Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated levels of blood glucose. Recently, some studies approached the diabetes care domain through the analysis of the modifications of cardiovascular system parameters. In fact, cardiovascular diseases are the first leading cause of death in diabetic subjects. Thanks to their cost effectiveness and their ease of use, electrocardiographic (ECG) and photoplethysmographic (PPG) signals have recently been used in diabetes detection, blood glucose estimation and diabetes-related complication detection. This review’s aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (2) Method: We performed a systematic review based on articles that focus on the use of ECG and PPG signals in diabetes care. The search was focused on keywords related to the topic, such as “Diabetes”, “ECG”, “PPG”, “Machine Learning”, etc. This was performed using databases, such as PubMed, Google Scholar, Semantic Scholar and IEEE Xplore. This review’s aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (3) Results: A total of 78 studies were included. The majority of the selected studies focused on blood glucose estimation (41) and diabetes detection (31). Only 7 studies focused on diabetes complications detection. We present these studies by approach: traditional, machine learning and deep learning approaches. (4) Conclusions: ECG and PPG analysis in diabetes care showed to be very promising. Clinical validation and data processing standardization need to be improved in order to employ these techniques in a clinical environment.

Electrocardiographic analysis of left bundle branch area pacing induced right ventricular activation delay

Abstract Funding Acknowledgements Type of funding sources: None. Background Left bundle branch area pacing (LBBAP) aims to capture the area of left bundle branch, resulting in fast activation of the left ventricle (LV) but delayed right ventricular (RV) activation. During intrinsic cardiac conduction, delayed RV activation results on the electrocardiogram (ECG) in a right bundle branch block (RBBB) pattern and is generally considered benign. As such, LBBAP-induced delayed RV activation is thought not to be harmful. However, to what extent left and right ventricular activation times during LBBAP resembles that of healthy individuals with acquired RBBB is currently not known. Methods Individuals with incomplete RBBB (iRBBB), complete RBBB (cRBBB) and LBBAP were included. Standard twelve lead electrocardiograms (ECG) were stored and analysed digitally using the MUSE ECG database. QRS duration was measured as global QRS duration. Left and right ventricular activation times were estimated by R-wave peak time in lead V6 (V6RWPT) and R’ peak time in lead V1 (V1RWPT), respectively. Delayed RV activation was further characterized by duration and area of R’ wave in lead V1. Results Paced QRS duration during LBBAP (n=86) measured 129±15ms whereas QRS duration of iRBBB (n=422) and cRBBB (n=223) individuals measured 103±8ms and 142±17ms respectively (p&amp;lt;0.001). V6RWPT during LBBAP (47±15ms) was significantly longer than V6RWPT in iRBBB (40±5ms) and cRBBB (39±7ms) (p&amp;lt;0.001). With LBBAP, V1RWPT (83±15ms) became delayed compared to iRBBB (74±9ms, p&amp;lt; 0.001), but remained shorter in comparison to cRBBB (98±17ms, p&amp;lt;0.001). Patients with LBBAP were further characterized by V1 R’ duration and R’ area which were shorter and smaller compared to cRBBB but similar to iRBBB individuals. Conclusion LBBAP-induced delayed RV activation resembles electrocardiographically more closely to the delayed RV activation as seen in individuals with incomplete rather than complete RBBB. Left ventricular activation times remain slightly prolonged during LBBAP as compared to RBBB individuals.

Electrocardiographic, echocardiographic and lipid parameters in predicting obstructive coronary artery disease in patients with non-ST elevation acute coronary syndrome

Aim. To assess the predictive potential of electrocardiographic (ECG), echocardiographic, and lipid parameters for predicting obstructive coronary artery disease (oCAD) in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) prior to invasive coronary angiography (CA).Material and methods. This prospective observational cohort study included 525 patients with NSTE-ACS with a median age of 62 years who underwent invasive coronary angiography. Two groups were distinguished, the first of which consisted of 351 (67%) patients with oCAD (stenosis 50%), and the second — 174 (33%) without oCAD (&lt;50%). Clinical and functional status of patients before CAG was assessed by 40 indicators. Mann-Whitney, Fisher, chi-squared, univariate logistic regression (LR) methods were used for data processing and analysis, while miltivariate LR (MLR), gradient boosting (XGBoost) and artificial neural networks (ANN) were used to develop predictive models. The quality of the models was assessed using 4 following metrics: area under the ROC curve (AUC), sensitivity (Se), specificity (Sp), and accuracy (Ac).Results. A comprehensive analysis of ECG, echocardiography and lipid profile parameters made it possible to identify factors that had linear and non-linear association with oCAD. LR were used to determine their weight coefficients and threshold values with the highest predictive potential. The quality metrics of the best predictive algorithm based on MLR were 0,81 for AUC, 0,74 for Sp and Ac, and 0,75 for Se. The predictors of this model were 4 categorical parameters (left ventricular (LV) ejection fraction of 42-60%, global LV longitudinal systolic strain &lt;19%, low-density lipoprotein cholesterol &gt;3,5 mmol/l, age &gt;55 years in men and &gt;65 years for women).Conclusion. The prognostic model developed on the basis of MLR made it possible to verify oCAD with high accuracy in patients with NSTE-ACS before invasive CA. Models based on XGBoost and ANN had less predictive value.

Physiological shift of the ventricular mean electrical axis in healthy French Bulldogs: a retrospective electrocardiographic analysis of 80 healthy dogs

Introduction/objectivesWhether a brachymorphic conformation may lead to electrocardiographic peculiarities diverging from generic reference intervals (RIs) cited in textbooks remains to be established. Therefore, this study aimed at evaluating electrocardiographic variables in one of the most common brachymorphic breed, namely the French Bulldog (FB). Animals, materials and methodsMedical records were retrospectively reviewed to identify healthy FBs ≥1-year-old that underwent an electrocardiogram. The Mann–Whitney U test or the Student's t-test was used to compare continuous variables among male and female dogs, while the χ2 test was used for categorical variables. Spearman's correlation coefficients between electrocardiographic measurements and age and body weight were also calculated. Moreover, electrocardiographic RIs were determined. ResultsEighty healthy FBs were enrolled; their electrocardiographic variables fitted with generic RIs, with the exception of the QRS-complex mean electrical axis (QRS-MEA). The median QRS-MEA value was 43.5° (from −18° to +90°). A QRS-MEA shift was found in 24/80 (30%) dogs; in all cases, it was a left shift (median 26°, from −18° to +39°). Specifically, 20 dogs showed a slight left shift (from +39° to +14°), while four dogs showed a marked one (from +9° to −18°). No meaningful differences were found when comparing electrocardiographic variables between males and females. No significant correlations between electrocardiographic variables and age or body weight were found, with the exceptions of the P-wave amplitude, PQ-interval duration and QT-interval duration. ConclusionsHealthy FBs can present a left shift of QRS-MEA. These data should be considered when interpreting FBs’ electrocardiograms.

Beneficial Effects of Black Cardamom (Amomum subulatum) on Hemodynamic Parameters in Normotensive and Spontaneously Hypertensive Rats.

&lt;b&gt;Background and Objectives:&lt;/b&gt; &lt;i&gt;Amomum subulatum&lt;/i&gt; (AS) is used to improve cardiac health in traditional medicine practice. The present study evaluates the pharmacological effect of AS aqueous extract on blood pressure in Normotensive (NR) and Spontaneously Hypertensive Rats (SHR). &lt;b&gt;Materials and Methods:&lt;/b&gt; Blood pressure, Heart Rate (HR) and Heart Rate Variability (HRV), was recorded in catheterized Sprague-Dawley rats before and after AS intravenous administration by using Mikro-Tip Pressure-Volume System (MPVS), PowerLab. The receptor activity was assessed by using the drugs Acetylcholine (ACh) and Atropine (Atr). &lt;b&gt;Results:&lt;/b&gt; Preliminary phytochemistry of AS suggests that it contains tannins, flavonoids and saponins. Mean Arterial Pressure (MAP) was found to decrease significantly in NR and SHR as compared with the control. The lowest dose (1 mg kg&lt;sup&gt;&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;) produced the least (16%) while 30 mg kg&lt;sup&gt;&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt; caused the maximum reduction (40%) in MAP. Electrocardiograph analysis revealed a significant increase in RR interval (decreased heart rate), time-domain Standard Deviation of Interbeat Interval (SDNN) and the Root Mean Square of the Successive Differences (RMSSD) and High-frequency Domain (HF%) parameters and a decrease in the Low-Frequency (LF) range, suggesting the activation and involvement of the parasympathetic limb. It was also observed that the cardiovascular effects of AS were comparable to Acetylcholine (ACh) and both were completely blocked by Atropine (1 μg kg&lt;sup&gt;&lt;/sup&gt;&lt;sup&gt;1&lt;/sup&gt;). &lt;b&gt;Conclusion:&lt;/b&gt; The obtained results suggest that AS has a hypotensive effect, with an impact on the HRV of NR and SHR. &lt;i&gt;Amomum subulatum&lt;/i&gt; might cause an augmented effect on the cholinergic limb of the Autonomic Nervous System (ANS) and decrease the blood pressure and heart rate significantly.

Horizons in Single-Lead ECG Analysis From Devices to Data

Single-lead wearable electrocardiographic (ECG) devices for remote monitoring are emerging as critical components of the viability of long-term continuous health and wellness monitoring applications. These sensors make it simple to monitor chronically ill patients and the elderly in long-term care homes, as well as empower users focused on fitness and wellbeing with timely health and lifestyle information and metrics. This article addresses the future developments in single-lead electrocardiogram (ECG) wearables, their design concepts, signal processing, machine learning (ML), and emerging healthcare applications. A literature review of multiple wearable ECG remote monitoring devices is first performed; Apple Watch, Kardia, Zio, BioHarness, Bittium Faros and Carnation Ambulatory Monitor. Zio showed the longest wear time with patients wearing the patch for 14 days maximum but required users to mail the device to a processing center for analysis. While the Apple Watch and Kardia showed good quality acquisition of raw ECG but are not continuous monitoring devices. The design considerations for single-lead ECG wearable devices could be classified as follows: power needs, computational complexity, signal quality, and human factors. These dimensions shadow hardware and software characteristics of ECG wearables and can act as a checklist for future single-lead ECG wearable designs. Trends in ECG de-noising, signal processing, feature extraction, compressive sensing (CS), and remote monitoring applications are later followed to show the emerging opportunities and recent innovations in single-lead ECG wearables.

Non Selective his Bundle Pacing: As Physiological as S-HBP but Simpler and Faster

We have read with interest Dr. Burri’s Electrocardiographic Analysis for His Bundle Pacing at Implantation and Follow up [1]. A comprehensive guide to understand electrocardiographic (ECG) nuances of His Bundle Pacing (HBP) is presented in this review. The authors, with outstanding didactics, describe a well-organized analysis of challenging HBP electrocardiographic characteristics to confirm conduction tissue (selective or non-selective HBP) at implant and follow-up. Caught our interest, in particular, the paragraph where practical pacing characteristics and benefits of non-selective HBP pacing (NSHBP) are emphasized. In this context we would like to point out the statement that pacing “ventricular myocardium adjacent to the atrioventricular septum, near the His bundle can also result in NSHBP”. Above all, of paramount clinical importance, when Dr. Burri et al. conclude that “No significant differences in cardiac mechanical synchrony or clinical outcome have been found between SHBP and NSHBP”. Our group is in total agreement with these essential features, having abandoned SHBP many years ago by developing a very simple technique to place standard pacing leads in the para-Hisian area (Figure 1). Concordant with the authors, we understand that “With non-selective His bundle pacing (NS-HBP), the lead is usually positioned in the ventricle at a site where the His bundle (HB) is surrounded by or at proximity to myocardial tissue”. That is why we named “para-Hisian pacing”. In our daily practice, at the same time, to verify and prove physiological capture of the conduction system we monitor synchrony online by analyzing the ECG signal variance [8] (Synchromax®) [2].