Utilizing smartphone-based electrocardiography and thoracic radiography to evaluate cardiac function and morphology in geriatric Sika deer (Cervus nippon)

Author(s):  
Hugo A. Gonzalez-Jassi ◽  
Nicole LeBlanc ◽  
Benjamin E. Alcantar ◽  
Rodrigo S. Garces Torres

Abstract OBJECTIVE To describe qualitative and quantitative cardiothoracic values in geriatric Sika deer (Cervus nippon) using digital radiography, 6-lead ECG (sECG), and smartphone-based ECG (aECG). ANIMALS 10 healthy geriatric Sika deer (9 females and 1 male). PROCEDURES Deer were chemically immobilized, thoracic radiographs were obtained, and inhalant anesthesia was initiated. An sECG and aECG were simultaneously recorded for each animal using the same ECG specifications. Results were compared between devices. RESULTS Radiographically, no deer had any cardiopulmonary abnormalities. Median (range) values for the most important cardiac measurements were 170 (153–193) mm for cardiac height, 135 (122–146) mm for cardiac width, 9 (8–9) for vertebral heart score, and 99 (69–124) mm for cardiosternal contact. All deer had a normal sinus rhythm with no pathological arrhythmias noted. A significant difference between sECG and aECG was identified for minimum heart rate (49 vs 51 beats/min, respectively), P wave duration (0.05 vs 0.03 seconds), P wave amplitude (0.28 vs 0.10 mV), PR interval (0.15 vs 0.12 seconds), and QT interval (0.39 vs 0.30 seconds). CLINICAL RELEVANCE Thoracic radiographs were suitable to evaluate basic cardiothoracic morphology in Sika deer. The aECG was useful for assessing heart rate and rhythm but, compared with sECG, proved no substitute for evaluating duration and amplitude of ECG waveforms.

2018 ◽  
Vol 91 (2) ◽  
pp. 166-175 ◽  
Author(s):  
Ram Sewak Singh ◽  
Barjinder Singh Saini ◽  
Ramesh Kumar Sunkaria

Objective. Cardiovascular diseases generate the highest mortality in the globe population, mainly due to coronary artery disease (CAD) like arrhythmia, myocardial infarction and heart failure. Therefore, an early identification of CAD and diagnosis is essential. For this, we have proposed a new approach to detect the CAD patients using heart rate variability (HRV) signals. This approach is based on subspaces decomposition of HRV signals using multiscale wavelet packet (MSWP) transform and entropy features extracted from decomposed HRV signals. The detection performance was analyzed using Fisher ranking method, generalized discriminant analysis (GDA) and binary classifier as extreme learning machine (ELM). The ranking strategies designate rank to the available features extracted by entropy methods from decomposed heart rate variability (HRV) signals and organize them according to their clinical importance. The GDA diminishes the dimension of ranked features. In addition, it can enhance the classification accuracy by picking the best discerning of ranked features. The main advantage of ELM is that the hidden layer does not require tuning and it also has a fast rate of detection.Methodology. For the detection of CAD patients, the HRV data of healthy normal sinus rhythm (NSR) and CAD patients were obtained from  a standard database. Self recorded data as normal sinus rhythm (Self_NSR) of healthy subjects were also used in this work. Initially, the HRV time-series was decomposed to 4 levels using MSWP transform. Sixty two features were extracted from decomposed HRV signals by non-linear methods for HRV analysis, fuzzy entropy (FZE) and Kraskov nearest neighbour entropy (K-NNE). Out of sixty-two features, 31 entropy features were extracted by FZE and 31 entropy features were extracted by K-NNE method. These features were selected since every feature has a different physical premise and in this manner concentrates and uses HRV signals information in an assorted technique. Out of 62 features, top ten features were selected, ranked by a ranking method called as Fisher score. The top ten features were applied to the proposed model, GDA with Gaussian or RBF kernal + ELM having hidden node as sigmoid or multiquadric. The GDA method transforms top ten features to only one feature and ELM has been used for classification.Results. Numerical experimentations were performed on the combination of datasets as NSR-CAD and Self_NSR- CAD subjects. The proposed approach has shown better performance using top ten ranked entropy features. The GDA with RBF kernel + ELM having hidden node as multiquadric method and GDA with Gaussian kernel + ELM having hidden node as sigmoid or multiquadric method achieved an approximate detection accuracy of 100% compared to ELM and linear discriminant analysis (LDA)+ELM for both datasets. The subspaces level-4 and level-3 decomposition of HRV signals by MSWP transform can be used for detection and analysis of CAD patients.


2018 ◽  
Vol 7 (2.24) ◽  
pp. 453
Author(s):  
S. Sathish ◽  
K Mohanasundaram

Atrial fibrillation is an irregular heartbeat (arrhythmia) that can lead to the stroke, blood clots, heart failure and other heart related complications. This causes the symptoms like rapid and irregular heartbeat, fluttering, shortness of breath etc. In India for every around 4000 people eight of them are suffering from Atrial Fibrillation. P-wave Morphology.  Abnormality of P-wave (Atrial ECG components) seen during sinus rhythm are associated with Atrial fibrillation. P-wave duration is the best predictor of preoperative atrial fibrillation. but the small amplitudes of atrial ECG and its gradual increase from isometric line create difficulties in defining the onset of P wave in the Standard Lead Limb system (SLL).Studies shows that prolonged P-wave have duration in patients (PAF) In this Study, a Modified Lead Limb (MLL) which solves the practical difficulties in analyzing the P-ta interval for both in healthy subjects and Atrial Fibrillation patients. P-Ta wave interval and P-wave duration can be estimated with following proposed steps which is applicable for both filtered and unfiltered atrial ECG components which follows as the clinical database trials. For the same the p-wave fibrillated signals that escalates the diagnosis follows by providing minimal energy to recurrent into a normal sinus rhythm.  


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4246-4246
Author(s):  
Henri M.H. Spronk ◽  
Anne-Margreet de Jong ◽  
Hetty C. de Boer ◽  
Alexander Maas ◽  
Sander Verheule ◽  
...  

Abstract Background: It is well known that atrial fibrillation (AF) induces a hypercoagulable state, which significantly increases stroke risk in patients with AF contributing to morbidity and mortality in these patients. Active coagulation factors can also provoke diverse cellular responses through stimulation of protease-activated receptors (PARs). In the heart and vessels, coagulation factor mediated PAR activation may provoke and mediate pro-inflammatory and tissue remodeling responses, potentially contributing to organ damage. We hypothesized that the onset and progression of AF, may be affected by hypercoagulability-mediated cell signaling responses, in the heart. Methods and results: To study the potential role of PARs in the structural remodeling process that renders the atria more prone to AF we first investigated whether thrombin or factor Xa could induce atrial fibroblast remodeling. In isolated rat cardiac fibroblasts, thrombin enhanced the phosphorylation of the pro-fibrotic signaling molecules Akt and Erk, and increased expression of TGFβ1 (2.7 fold) and the pro-inflammatory factor monocyte chemo-attractant protein-1 (6.1 fold). Thrombin also increased the incorporation of 3H-proline suggesting enhanced collagen synthesis by cardiac fibroblasts (2.5 fold). Differentiation towards myofibroblasts was indicated by increased expression of smooth muscle actin (2 fold). All effects could be prevented by the direct thrombin inhibitor dabigatran and comparable results were obtained for stimulation with factor Xa and inhibition with rivaroxaban, respectively. Next we studied whether enhanced stimulation of PARs
by chronic elevation of thrombin levels would lead to an enhanced vulnerability to AF in transgenic mice. In mice with enhanced thrombin activity due to a mutation in the thrombomodulin gene resulting in impaired thrombin inhibition (TMpro/pro), inducibility of AF episodes provoked by burst pacing was higher (6 out of 10 versus 1 out of 10 in wild type) and the duration of AF episodes was longer (episodes >2s in 6 out of 10 versus 0 out of 10 in wild type). Finally, we showed that inhibition of the coagulation cascade attenuated the development of AF in a goat model of AF. In 6 goats with persistent AF and treated with the anticoagulant nadroparine (4 weeks, 150 IU/kg twice daily) the complexity of the AF substrate was less pronounced compared to control animals. The conduction heterogeneity and block were 33% shorter in the nadroparine treated animals (maximal conduction time 23.3±3.1ms in control versus 15.7±2.1ms in nadroparine, p<0.05) and AF-induced a-SMA expression and endomysial fibrosis were less pronounced. Conclusion: The hypercoagulable state during AF provokes pro-fibrotic and pro-inflammatory responses in cardiac fibroblasts, as well as promotes the development of a substrate for AF in transgenic mice and in goats with persistent AF. Together, these results strongly support the role of hypercoagulability and PAR activation in the development of a substrate for AF. In addition, direct anticoagulant treatment may protect against AF-related cellular atrial remodelling. Figure 1: Enhanced AF inducibility and prolonged AF duration in TMpro/pro mice. Transesophageal stimulation was used to test AF inducibility. A surface electrocardiogram (lead I, sampled at 2.5 kHz) was recorded to detect AF. A) Traces show an example of a Wt mouse, returning to normal sinus rhythm immediately after the burst (upper panel) and a TMpro/pro mouse, showing a 3s episode of AF before returning to sinus rhythm (lower panel). In both cases, the first P wave observed after the burst is indicated. B) AF was inducible in 1 out of 10 Wt mice and 6 out of 10 TMpro/pro mice. C) Distribution of the longest AF episode duration observed in each Wt and TMpro/pro mouse. Figure 1:. Enhanced AF inducibility and prolonged AF duration in TMpro/pro mice. Transesophageal stimulation was used to test AF inducibility. A surface electrocardiogram (lead I, sampled at 2.5 kHz) was recorded to detect AF. A) Traces show an example of a Wt mouse, returning to normal sinus rhythm immediately after the burst (upper panel) and a TMpro/pro mouse, showing a 3s episode of AF before returning to sinus rhythm (lower panel). In both cases, the first P wave observed after the burst is indicated. B) AF was inducible in 1 out of 10 Wt mice and 6 out of 10 TMpro/pro mice. C) Distribution of the longest AF episode duration observed in each Wt and TMpro/pro mouse. Disclosures No relevant conflicts of interest to declare.


Author(s):  
Syed Hassan Zaidi ◽  
Imran Akhtar ◽  
Syed Imran Majeed ◽  
Tahir Zaidi ◽  
Muhammad Saif Ullah Khalid

This paper highlights the application of methods and techniques from nonlinear analysis to illustrate their far superior capability in revealing complex cardiac dynamics under various physiological and pathological states. The purpose is to augment conventional (time and frequency based) heart rate variability analysis, and to extract significant prognostic and clinically relevant information for risk stratification and improved diagnosis. In this work, several nonlinear indices are estimated for RR intervals based time series data acquired for Healthy Sinus Rhythm (HSR) and Congestive Heart Failure (CHF), as the two groups represent different cases of Normal Sinus Rhythm (NSR). In addition to this, nonlinear algorithms are also applied to investigate the internal dynamics of Atrial Fibrillation (AFib). Application of nonlinear tools in normal and diseased cardiovascular states manifest their strong ability to support clinical decision support systems and highlights the internal complex properties of physiological time series data such as complexity, irregularity, determinism and recurrence trends in cardiovascular regulation mechanisms.


Author(s):  
Sinare B R ◽  
Annasaheb Gagare ◽  
Chinmaye Batwal ◽  
Liz Thaliath ◽  
Prashant Patel ◽  
...  

Background: Systemic absorption of local anesthetics occurs due to its local vasodilator effects. This leads to inhibitory action on the heart which is represented in the form of a decrease in conduction rate, the excitability of myocardium and force of contraction. The aim of the present study was to evaluate the effects of Lignocaine and adrenaline combinations on electrocardiogram undergoing dental procedures. Methods: This was a prospective, observational clinical study done in collaboration with the Department of Oral & Maxillofacial Surgery. All patients scheduled for oral surgeries under local anesthesia with Lignocaine 2% and adrenaline (1:80000 or 1:200000) combination of age 18 years or above 150 patients were included in the study. Patients with a history of hepatic, renal, cardiovascular and thyroid disorders were excluded from the study. A standard 12-lead ECG (25 mm/s) was recorded for each patient before administration of drugs (Basal), during the dental procedure (Intraoperative) and immediately after completion of surgical procedure. Results: There was no statistically significant difference seen between the Group A (Lignocaine 2% with 1:80000 adrenaline) and B (Lignocaine 2% with 1:200000 adrenaline) when the age, gender, PR interval, RR interval, mean QT & QTc dispersion, and heart rate were compared. Statistically significant difference was seen in comparing the mean QT & QTc interval, which was higher in Group A. ECG parameters in Group A and B showed a statistically significant decrease in PR interval, RR interval, QT interval, QTc interval, QT dispersion and QTc dispersion, with the basal, was compared with intraoperative and postoperative findings. The increase in heart rate although was statistically significant in both the groups, it was always within normal limits suggestive of no clinical significance. There was a statistically significant decrease in QT and QTc interval, QT and QTc dispersion. The change in all these parameters was within the physiologic range. All these relevant parameters for cardiac arrhythmias did not show any arrhythmogenic potential of lignocaine-adrenaline combination in both the groups. Both the combinations are comparable with each other in terms of ECG parameters with changes more with group A suggesting the effect of increased concentration of adrenaline. The change in the heart rate and ECG parameters in both the study group might be attributed to the presence of adrenaline in the combination. No cardiovascular morbidities were observed except palpitation. Conclusion: Thus it can be very well concluded that the effects of lignocaine-adrenaline combinations on electrocardiographic parameters are minimal and clinically irrelevant. Both the combination appears to be safe to use in healthy individuals. Keywords: Adrenaline; Lignocaine; ECG parameters; Dental procedures.


2021 ◽  
Vol 12 ◽  
Author(s):  
Ricardo Salinas-Martínez ◽  
Johannes de Bie ◽  
Nicoletta Marzocchi ◽  
Frida Sandberg

Background: Brief episodes of atrial fibrillation (AF) may evolve into longer AF episodes increasing the chances of thrombus formation, stroke, and death. Classical methods for AF detection investigate rhythm irregularity or P-wave absence in the ECG, while deep learning approaches profit from the availability of annotated ECG databases to learn discriminatory features linked to different diagnosis. However, some deep learning approaches do not provide analysis of the features used for classification. This paper introduces a convolutional neural network (CNN) approach for automatic detection of brief AF episodes based on electrocardiomatrix-images (ECM-images) aiming to link deep learning to features with clinical meaning.Materials and Methods: The CNN is trained using two databases: the Long-Term Atrial Fibrillation and the MIT-BIH Normal Sinus Rhythm, and tested on three databases: the MIT-BIH Atrial Fibrillation, the MIT-BIH Arrhythmia, and the Monzino-AF. Detection of AF is done using a sliding window of 10 beats plus 3 s. Performance is quantified using both standard classification metrics and the EC57 standard for arrhythmia detection. Layer-wise relevance propagation analysis was applied to link the decisions made by the CNN to clinical characteristics in the ECG.Results: For all three testing databases, episode sensitivity was greater than 80.22, 89.66, and 97.45% for AF episodes shorter than 15, 30 s, and for all episodes, respectively.Conclusions: Rhythm and morphological characteristics of the electrocardiogram can be learned by a CNN from ECM-images for the detection of brief episodes of AF.


2020 ◽  
Vol 15 (16) ◽  
pp. 62-68
Author(s):  
A.V. Martynenko ◽  

Introduction. Non-linear methods of analysis have found widespread use in the Heart Rate Variability (HRV) technology, when the long-term HRV records are available. Using one of the effective nonlinear methods of analysis of HRV correlation dimension D2 for the standard 5-min HRV records is suppressed by unsatisfactory accuracy of available methods in case of short records (usually, doctors have about 500 RRs during standard 5-min HRV record), as well as complexity and ambiguity of choosing additional parameters for known methods of calculating D2. The purpose of the work. Building a robust estimator for calculating correlation dimension D2 with high accuracy for limited se-ries of RR-intervals observed in a standard 5-minute HRV record, i. e. with N  500. As well as demonstrating the capabilities of the D2 formula on a well known attractors (Lorenz, Duffing, Hennon and etc.) and in applications for Normal Sinus Rhythm (NSR), Congestive Heart Failure (CHF) and Atrial Fibrillation (AF). Materials and Methods. We used MIT-BIH long-term HRV records for normal sinus rhythm, congestive heart failure and atrial fibrillation. In order to analyze the accuracy of new robust estimator for D2, we used the known theoretical values for some famous attractors (Lorenz, Duffing, Hennon and etc.) and the most popular Grassberger-Procaccia (G-P) algorithm for D2. The results of the study. We have shown the effectiveness of the developed D2 formula for time series of limited length (N = 500–1000) by some famous attractors (Lorenz, Duffing, Hennon and etc.) and with the most popular Grassberger-Procaccia (G-P) algorithm for D2. It was demonstrated statistically significant difference of D2 for normal sinus rhythm and congestive heart failure by standard 5 min HRV segments from MIT-BIH database. The promised technology for early prediction of atrial fibrillation episodes by current D2 algorithm was shown for standard 5 min HRV segments from MIT-BIH Atrial Fibrillation database. Conclusion. Robust correlation dimension D2 estimator suggested in the article allows for time series of limited length (N ≈ 500) to calculate D2 value that differs at mean from a precise one by 5 ± 4%, as demonstrated for various well known attractors (Lorenz, Duffing, Hennon and etc.). We have shown on the standard 5-min segments from MIT-BIH database of HRV records: - the statistically significant difference of D2 for cases of normal sinus rhythm and congestive heart failure; - D2 drop significantly for the about 30 min. before of AF and D2 growth drastically under AF there was shown for HRV records with Atrial Fibrillation (AF) episodes. The suggested robust correlation dimension D2 estimator is perfect suitable for real time HRV monitoring as accurate, fast and non-consuming for computing resources. Key words: Hearth rate variability; Correlation dimension; Congestive heart failure; Atrial fibrillation.


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