Electrocardiographic Arrhythmias Research Articles

Genetik Algoritmalar Kullanarak EKG Vuru Sınıflandırması için Öznitelik Seçimi

In this study, genetic algorithm method was used to select the most suitable set of features for classification of arrhythmia types of heart beats. Normal, right branch block, left branch block and pace rhythm samples of electrocardiography (ECG) signals which obtained from the MIT-BIH cardiac arrhythmia database were used in the classification. Mean, standard deviation, energy and entropy of discrete wavelet transform (DWT) coefficients were proposed as the features for the classification. By using the proposed DWT method, 16 features which have high classification accuracy were obtained among the 208 feature sets constructed from 13 different wavelet types by applying the genetic algorithm method. It was observed that the features that increase accuracy can be detected by the genetic algorithm and the feature set obtained from the coefficients of the different types of wavelets selected at different levels show higher performance than the coefficients obtained from the standard individual wavelet in the ECG arrhythmia classification.

Rhythm and orthopedics: The effect of music therapy in cast room procedures, a prospective clinical trial

IntroductionCast room procedures generally cause anxiety in patients. Anxiety complicates the procedure as well as increases the risk of a complication. Listening to music was found to be the safest and most common non-drug treatment method. The aim of this study is to evaluate the effect of listening to music on adult patients in cast room procedures. This study points out the relation between anxiety and anxiety relevant cardiac arrhythmia. Materials and methodsThe study was performed on 199 patients with stable general condition, aged above 18. The patients were divided into two groups. Randomization method used in the study was coin flip. The first group (Group 1) listened to music during cast room procedures whereby the second group (Group 2) did not listen to music. Length of the procedure, complication, blood pressure and heart rate evaluations before and after the procedure, Visual Analogue Scale (VAS scores for pain), State-Trait Anxiety Inventory (STAI) anxiety score, patient satisfaction, willingness of the patient to repeat the procedure, P wave dispersion (Pd) and corrected QT interval dispersion (QTcd) as electrocardiographic arrhythmia predictors were evaluated. The Clinical Research Ethics Committee approval was obtained for this study. ResultsSignificant difference was shown between the two groups for the following criteria: VAS scores (p = 0.005), anxiety scores (p = 0.032), processing time (p = 0.027), and QTcd values (p = 0.031). Patient satisfaction (p < 0.001) and willingness to repeat the procedure (p < 0.001) were higher for the group who listened to music. No significant difference in Pd values, blood pressure and heart rate was reported within the groups. ConclusionMusic therapy is a non-invasive, safe, nonpharmacologic, anxiolytic, and analgesic treatment. Music therapy should become standard protocol in cast room procedures. One of the most important achievements of this study was the fact that music decreases anxiety and anxiety-related cardiac arrhythmia. Therefore, conducting further prospective studies including high cardiac risk patients especially with arrhythmia is crucial.

The Effects of Continuous Positive Airway Pressure on Premature Ventricular Contractions and Ventricular Wall Stress in Patients with Heart Failure and Sleep Apnea.

Background We aimed to investigate the effects of continuous positive airway pressure (CPAP) treatment on electrocardiography (ECG), premature ventricular contraction load on 24-hour Holter recordings, and implantable cardioverter defibrillator (ICD) shocks in patients with obstructive sleep apnea syndrome (OSAS) and heart failure. Methods Patients with heart failure and ICD and patients with newly diagnosed OSAS were divided into two groups according to CPAP treatment. To compare the impact of CPAP on ECG parameters, both baseline and 6-month ECG, 24-hour Holter ECG, ambulatory blood pressure monitoring, echocardiography, polysomnography, and laboratory parameters were collected. Results CPAP treatment significantly reduced the frequency of premature ventricular contractions, T-peak to T-end, corrected QT, corrected QT dispersion, and T-peak to T-end/corrected QT ratio in the study group (p < 0.001 for all). Although the baseline NT-pro-BNP levels were similar between study and control groups, after six months, the NT-pro-BNP levels of the study group were significantly lower than that of the control group (39.18 ± 7.57 versus 46.11 ± 7.65; p < 0.001). Conclusions CPAP treatment in patients with heart failure and ICD and in patients with newly diagnosed OSAS may have beneficial effects on premature ventricular contractions and electrocardiographic arrhythmia indices and NT-pro-BNP levels. However, these results are needed to be clarified with further studies.

Automatic detection of electrocardiographic arrhythmias by parallel continuous neural networks implemented in FPGA

In the developed world, heart diseases are the major cause of death among adults. Often, the sufferers of heart disease are not aware of their condition until a catastrophic medical event occurs. Therefore, early online detection and continuous monitoring of abnormal heart rhythms shall reduce this occurrence. There are four main types of arrhythmia: ventricular arrhythmia, supraventricular arrhythmia, premature beats and asynchronous arrhythmia. In this study, an algorithm for automatic detection of atrial premature contraction, supraventricular tachyarrhythmias, fusion of ventricular and normal beat (FUSION), isolated QRS-like artifact (ARFCT), ST change, T-wave change, premature or ectopic supraventricular beat and normal beat (NORMAL) using a continuous neural network (CoNN) is presented. This kind of continuous classifier offers an online detection of classical arrhythmia observed in electrocardiographic (EKG) signals. Typically, due to its complexity and recursive nature of arrhythmia classification algorithms, they are difficult to be implemented in real time. In this work, automatic signal classification was attained by implementing a parallel CoNN algorithm using fixed point arithmetic on a field-programmable gate array (FPGA). First, the classification algorithm using a floating-point MATLAB implementation was developed and validated. This procedure served as a benchmark for the fixed point FPGA implementation on a Xilinx Zinq board. The performance of the classification algorithm was evaluated by using a fivefold cross-validation method, achieving a 93.80% accuracy and a sensitivity (TPR) average of 98% when performing the classification of the entire set of EKG signal samples.

Electrocardiogram Signal Quality Assessment Based on Structural Image Similarity Metric.

We developed an image-based electrocardiographic (ECG) quality assessment technique that mimics how clinicians annotate ECG signal quality. We adopted the structural similarity measure (SSIM) to compare images of two ECG records that are obtained from displaying ECGs in a standard scale. Then, a subset of representative ECG images from the training set was selected as templates through a clustering method. SSIM between each image and all the templates were used as the feature vector for the linear discriminant analysis classifier. We also employed three commonly used ECG signal quality index (SQI) measures: baseSQI, kSQI, and sSQI to compare with the proposed image quality index (IQI) approach. We used 1926 annotated ECGs, recorded from patient monitors, and associated with six different ECG arrhythmia alarm types which were obtained previously from an ECG alarm study at the University of California, San Francisco (UCSF). In addition, we applied the templates from the UCSF database to test the SSIM approach on the publicly available PhysioNet Challenge 2011 data. For the UCSF database, the proposed IQI algorithm achieved an accuracy of 93.1% and outperformed all the SQI metrics, baseSQI, kSQI, and sSQI, with accuracies of 85.7%, 63.7%, and 73.8% respectively. Moreover, evaluation of our algorithm on the PhysioNet data showed an accuracy of 82.5%. The proposed algorithm showed better performance for assessing ECG signal quality than traditional signal processing methods. A more accurate assessment of ECG signal quality can lead to a more robust ECG-based diagnosis of cardiovascular conditions.

Paroxysmal atrial fibrillation in seven dogs with presumed neurally-mediated syncope

ObjectivesTo document the electrocardiographic findings of vagally-induced paroxysmal atrial fibrillation following a presumed reflex syncopal episode in the dog. AnimalsSeven dogs with a syncopal episode followed by a paroxysm of atrial fibrillation recorded on a 24-hour Holter. MethodsTwenty-four hour Holter monitors were retrospectively reviewed, analysing the cardiac rhythm associated with syncopal events. Each recording was analysed from 10 min before the syncopal episode to until 10 min after a normal sinus rhythm had returned. ResultsNine episodes were recorded in seven dogs, with one patient experiencing three events during one Holter recording. Five of the seven dogs presented with underlying structural heart disease. In two the syncopal episodes occurred following exercise, two associated with coughing and three were during a period of rest. All dogs had documented on the Holter recording a rhythm abnormality during syncope. The most common finding leading up to the syncopal event was development of a progressive sinus bradycardia, followed by sinus arrest interrupted by a ventricular escape rhythm and then ventricular arrest. This was then followed by an atrial fibrillation. The atrial fibrillation was paroxysmal in seven recordings and persistent in two. In two dogs, the atrial fibrillation reorganised into self-limiting runs of atypical atrial flutter. ConclusionsThis combination of electrocardiographic arrhythmias are probably caused by an inappropriate parasympathetic stimulation initiating a reflex or neurally-mediated syncope, with abnormal automaticity of the sinus node and of the subsidiary pacemaker cells and changes in the electrophysiological properties of the atrial muscle, which promoted the paroxysmal atrial fibrillation.

Design of Electrocardiography Signal Acquisition and Processing Software Module

This paper presents the design of electrocardiography (ECG) signal acquisition and processing using graphic programming language LabVIEW 2012. The module software is designed towards applying in researches, monitoring and diagnosing cardiovascular diseases. The module software includes several main functions such as acquiring and displaying ECG signals in real time; filtering common artifacts in ECG signal using different algorithms and techniques; reading, displaying, analyzing and processing available ECG database; computing heart rate; saving ECG signals before and after noises filtering in data and graphs format; analyzing ECG signals before and after noises filtering by spectral analysis method. The designed module software is tested with arrhythmia ECG database and 12-lead ECG database from physionet.org and experimented with measuring from volunteer in the lab. The experimented results show that this module could support for researches, monitoring and diagnosing cardiovascular diseases.

Abnormal ECG Findings In Turkish Adults: An Epidemiologic Observational Study

Objective: Atherosclerotic cardiovascular disease (CVD) is the leading cause of death worldwide. Abnormal electrocardiography (ECG) findings are predictors of short-term cardiovascular risk. We aimed to contribute lacking national epidemiologic data regarding the prevalence of abnormal ECG findings in Turkish adults. Methods: The prevalence of abnormal ECG findings and arrhythmias were investigated in the west Black sea region of Turkey. A total of 2239 subjects over 18 years old were examined with 12 derivation resting ECG in this large epidemiological observational cohort study. Pathological Q waves, axis deviation, high R amplitude, ST-T changes, atrioventricular (AV) blocks, intraventricular (IV) blocks, arrhythmias and low QRS voltage were interpreted as ECG parameters. ECG findings were classified according to the Minnesota coding system. Results: Mean age was 50 ± 15 (age=18 to 92) years. Age-adjusted (over 40 years old) prevalence of abnormal ECG findings and arrhythmias were detailed in the following respectively; pathological Q waves 2.06%, left axis deviation 9.64%, high R wave amplitude 6.57%, ST segment depression 2.01%, T inversion 3.25%, left bundle branch block (LBBB) 2.63%, extra systoles 3.26% and atrial fibrillation 2.01%. Conclusion: This observation reveals the increasing trend of the prevalence of arterial hypertension, coronary artery disease (CAD) and atrial fibrillation in the last two decades in Turkey.

Risk factors for perioperative major adverse cardiac events in elderly patients with coronary heart disease undergoing orthopedic surgery

Objective To identify the risk factors for perioperative major adverse cardiac events (MACEs)in elderly patients with coronary heart disease (CHD) undergoing orthopedic surgery.Methods One hundred and twenty-nine patients with CHD,aged ≥65 yr,undergoing elective major orthopedic surgery in our hospital from January 2004 to December 2009,were selected.The patients were assigned into MACE group or non-MACE group according to the occurrence of MACEs during surgery and within 30 days after surgery.Age,sex,history of coronary reconstruction,myocardial infarction,heart failure,angina,systemic angionosis,cerebrovascular disease and diabetes,basic and preoperative blood pressure,routine blood test,serum creatinine,blood glucose,preoperative electrocardiography (ECG) and ultrasonic cardiography,ASA,intraoperative blood transfusion,operation and anesthesia time,entering ICU after surgery and postoperative volume of drainage were recorded.If there was significant difference between the 2 groups,the factor was analyzed using multi-factor logistic regression to select the risk factors for incidence of MACEs.Results Twenty-one patients developed perioperative MACEs (16.3 %).Logistic regression analysis showed that unstable angina within 6 months,preoperative haematocrit ≤ 35%,preoperative ECG arrhythmia and wall motion abnormality were risk factors for incidence of perioperative MACEs in this population (P ＜ 0.05),and the risk indexes of the factors were 5,3,3 and 4,respectively.Conclusion Unstable angina within 6 months,preoperative haematocrit ≤ 35 %,preoperative ECG arrhythmia and wall motion abnormality are risk factors for perioperative MACEs in elderly patients with CHD undergoing orthopedic surgery. Key words: Aged ; Coronary heart disease; Heart diseases; Risk factors; Intraoperative period

Are patients admitted to emergency departments with regular supraventricular tachycardia (SVT) treated appropriately?

Regular supraventricular tachycardia (SVT) is frequently encountered in clinical practice. Guidelines are available from the National Service Framework (NSF) for the treatment of patients attending emergency departments (ED) with SVT. These recommend a thyroid-function test (TFT) and arrhythmia electrocardiography (ECG), and referral to a heart-rhythm specialist on discharge. Hospital admission is rarely required. In our multicentre study, we examined the implementation of these guidelines among patients attending the ED with SVT. Only 34% of patients had specialist referrals, with an average wait of 50.3 days (the majority of delays resulted from referral requests from general practitioners). A history of previous SVT, the mode of tachycardia termination, patient age and/or comorbidities were similar for the 27 (23.5%) patients who were admitted overnight. Of these, 15 (13%) of the total 115 patients who attended ED with regular SVT were referred for Holter monitoring despite having ECGs demonstrating arrhythmia. Low referral rates, unnecessary investigations and admissions indicate a need for improvement for better patient care and to minimise healthcare costs. We have formulated a standard operating procedure, which will be available via the College of Emergency Medicine website.

Study on Real-time Monitoring Technique for Cardiac Arrhythmia Based on Smartphone

Electrocardiography (ECG) monitoring is an important method for cardiac disease detection and prevention. With the development of telemedicine, ECG real-time monitoring becomes more convenient. The rise and popularization of smartphone provide a new technical means for ECG monitoring. This paper focuses on the development of software for an ECG monitoring system on a smartphone platform. The system includes a client and a center. The client is developed on smartphone. Its main function is process and diagnose ECG signal. A wavelet method is used to detect the QRS-complex and diagnostic criteria are formulated to diagnose 14 kinds of arrhythmia disease. The tele-monitoring center is developed on a PC with LabVIEW, which receives ECG signal and diagnosis from smartphone by GPRS. Results show that the system can monitor ECG and diagnose arrhythmia by calculating the heart rate in real time. The proposed system is reliable and gives good real-time performance.

Electrocardiographic abnormalities in acute cerebrovascular events in patients with/without cardiovascular disease

Objectives:Electrocardiographic (ECG) changes are reported frequently after acute strokes. It seems that cardiovascular effects of strokes are modulated by concomitant or pre-existent cardiac diseases, and are also related to the type of cerebrovascular disease and its localization. We aimed to determine the pattern of ECG changes associated with pathophysiologic categories of acute stroke among patients with/without cardiovascular disease and to determine if specific ECG changes are related to the location of the lesion.Materials and MethodsThe electrocardiographic records of 361 patients with acute stroke were studied to assess the relative frequencies of ECG abnormalities among the pathophysiologic categories of stroke.Results:In the present study, the most common ECG abnormalities associated with stroke were T-wave abnormalities, prolonged QTc interval and arrhythmias, which were respectively found in 39.9%, 32.4%, and 27.1% of the stroke patients and 28.9%, 30.7%, and 16.2 of the patients with no primary cardiac disease. We observed that other ECG changes comprising pathologic Q- wave, ST-segment depression, ST-segment elevation, and prominent U wave may also occur in selected or non-selected stroke patients; thereby simulate an acute myocardial injury. We observed an increased number of patients with abnormal T-wave and posterior fossa bleedings and more rhythm disturbances for ischemic lesions, localized in the anterior fossa.Conclusion:Ischemia-like ECG changes and arrhythmias are frequently seen in stroke patients, even in those with no history or signs of primary heart disease, which support a central nervous system origin of these ECG abnormalities. Further study is necessary to better define the brain-heart interaction.

Flow-gated radial phase-contrast imaging in the presence of weak flow

To implement a flow-gating method to acquire phase-contrast (PC) images of carotid arteries without use of an electrocardiography (ECG) signal to synchronize the acquisition of imaging data with pulsatile arterial flow. The flow-gating method was realized through radial scanning and sophisticated post-processing methods including downsampling, complex difference, and correlation analysis to improve the evaluation of flow-gating times in radial phase-contrast scans. Quantitatively comparable results (R=0.92-0.96, n=9) of flow-related parameters, including mean velocity, mean flow rate, and flow volume, with conventional ECG-gated imaging demonstrated that the proposed method is highly feasible. The radial flow-gating PC imaging method is applicable in carotid arteries. The proposed flow-gating method can potentially avoid the setting up of ECG-related equipment for brain imaging. This technique has potential use in patients with arrhythmia or weak ECG signals.

Brugada syndrome: Insights of ST elevation, arrhythmogenicity, and risk stratification from experimental observations

Brugada syndrome (BrS), caused by ion channel abnormalities, is characterized by ST segment elevation and negative T waves in the right precordial electrocardiographic (ECG) leads recorded over the right ventricular outflow tract (RVOT). BrS is sensitive to body temperature and can lead to T-wave alternans (TWA), ventricular tachycardia, and sudden death. Recent studies in an isolated canine RVOT model of BrS demonstrated that reversal of the transmural gradient of repolarization caused the ECG characteristics and that major intraepicardial and transmural dispersion of action potentials (APs) initiated phase 2 reentry, premature ventricular activations, and tachyarrhythmias. Hypothermia enhanced the heterogeneity of the AP and promoted the origination of phase 2 reentry in the epicardium of the RVOT, but the prolonged AP duration frequently blocked reentry. Hyperthermia abbreviated the AP and facilitated the maintenance of reentry and tachyarrhythmias. Bradycardia promoted alternans in the phase 2 dome of the AP within the epicardium of the RVOT, resulting in TWA. The above phenomena were localized in the epicardium of the RVOT. Blockade of the transient outward current, I(to), reduced AP heterogeneity and prevented arrhythmias in the BrS model. In addition, epicardial activation delay led to fragmented QRS, a risk marker of prognosis in BrS. Body surface mapping in patients with BrS supported these experimental findings. In conclusion, the AP heterogeneity within the epicardium of the RVOT contributes to the ECG characteristics, temperature sensitivity, TWA, and arrhythmias in BrS, and body surface mapping and fragmented QRS can be effective predictors of risk in patients with BrS.

A novel approach in ECG beat recognition using adaptive neural fuzzy filter

Accurate and computationally efficient means of electrocardiography (ECG) arrhythmia detec-tion has been the subject of considerable re-search efforts in recent years. Intelligent com-puting tools such as artificial neural network (ANN) and fuzzy logic approaches are demon-strated to be competent when applied individu-ally to a variety of problems. Recently, there has been a growing interest in combining both of these approaches, and as a result, adaptive neural fuzzy filters (ANFF) [1] have been evolved. This study presents a comparative study of the classification accuracy of ECG signals using (MLP) with back propagation training algorithm, and a new adaptive neural fuzzy filter architec-ture (ANFF) for early diagnosis of ECG ar-rhythmia. ANFF is inherently a feed forward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules [1]. In this paper we used an adap-tive neural fuzzy filter as an ECG beat classifier. We combined 3 famous wavelet transforms and used them mid 4 the order AR model coefficient as features. Our results suggest that a new proposed classifier (ANFF) with these features can generalize better than ordinary MLP archi-tecture and also learn better and faster. The results of proposed method show high accu-racy in ECG beat classification (97.6%) with 100% specificity and high sensitivity.

Unveiling electrocardiographic mysteries

I read with interest the letter from Dewilde and Desmet [1] on mysterious electrocardiographic arrhythmia in an old woman presenting irregular heart rhythm, characterized by idioventricular rhythmic bigeminy with left bundle branch block pattern, and cardiac dysfunction underlying severe hyperkalemia. Hyperkalemia has been known for a long time to be associated to abnormal impulse formation manifested by either acceleration of normal pacemaker or emergence of ectopic pacemakers [2] in atria and ventricles. In limited series studies, conduction disturbances presenting with right bundle branch block (roughly 25% prevalence) are slightly more prevalent than left bundle branch block (17% prevalence) [3–5]. Impulse formation and conduction may co-exist among electrocardiographic findings of hyperkalemia [3,6], determining junctional rhythm with bundle branch block pattern. However, association of abnormal idioventricular rhythm and overt heart failure represents a medical emergency [6], making cardiac life support mandatory on presentation, and perhaps retarding a more accurate diagnostic procedure. Additionally, association of angiotensin II blockers and potassium-sparing diuretics increases the risk of hyperkalemia [7], especially in elderly due to age-related depressed renal function. Finally, disopyramide has been known to be a potent cardiac depressant [8] with negative dromotropic effect and administration to patients with left ventricular systolic dysfunction must be made with extreme caution [8]. In

A fuzzy clustering neural network architecture for classification of ECG arrhythmias

Accurate and computationally efficient means of classifying electrocardiography (ECG) arrhythmias has been the subject of considerable research effort in recent years. This study presents a comparative study of the classification accuracy of ECG signals using a well-known neural network architecture named multi-layered perceptron (MLP) with backpropagation training algorithm, and a new fuzzy clustering NN architecture (FCNN) for early diagnosis. The ECG signals are taken from MIT-BIH ECG database, which are used to classify 10 different arrhythmias for training. These are normal sinus rhythm, sinus bradycardia, ventricular tachycardia, sinus arrhythmia, atrial premature contraction, paced beat, right bundle branch block, left bundle branch block, atrial fibrillation and atrial flutter. For testing, the proposed structures were trained by backpropagation algorithm. Both of them tested using experimental ECG records of 92 patients (40 male and 52 female, average age is 39.75 ± 19.06 ). The test results suggest that a new proposed FCNN architecture can generalize better than ordinary MLP architecture and also learn better and faster. The advantage of proposed structure is a result of decreasing the number of segments by grouping similar segments in training data with fuzzy c-means clustering.

Chagasic Cardiomyopathy Is Independently Associated With Ischemic Stroke in Chagas Disease

Chagasic cardiomyopathy is independently associated with ischemic stroke in Chagas disease. American trypanosomiasis, Chagas disease (CD), is a major public health problem in South America. We sought to evaluate prevalence of vascular risk factors for stroke in patients with stroke caused by CD. Ninety-four consecutive CD stroke patients and 150 consecutive nonchagasic stroke patients were studied. CD was confirmed when both immunofluorescence and hemagglutination serology were positive. Data collected included age, sex, vascular risk factors, diagnostic stroke subtype (TOAST classification), and echocardiography findings. Fasting plasma levels of protein C, protein S, antithrombin III, homocysteine, activated protein C resistance, IgG anticardiolipin antibodies, lupus anticoagulant, and genetic tests for the factor V Leiden and the C677T methylene tetrahydrofolate reductase gene mutation were determined. CD patients had a mean age of 56.31 years compared with 61.59 years for non-CD stroke patients (P=0.0002). Cardioembolism occurred in 56.38% of CD stroke patients compared with 9.33% in controls (P=0.000), whereas atherothrombotic strokes occurred in 8.51% of CD strokes versus 20% in controls (P=0.016), and small-vessel stroke in 9.57% of CD stroke patients versus 34.67% in controls (P=0.000). Apical aneurysm (37.23% versus 0.67%; OR, 88.39), left ventricular dilatation (23.4% versus 5.33%; OR, 5.42), mural thrombus (11.7 versus 2%; OR, 6.49) and abnormal electrocardiography (ECG) (66% versus 23.33%; OR, 2.87) were significantly higher in the group of chagasic stroke patients. No statistical differences were observed in thrombophilia between both groups. The significant variables that predicted CD stroke patients on a stepwise logistical regression model were apical aneurysm, cardiac insufficiency, ECG arrhythmia, female gender, and hypertension. Chagasic cardiomyopathy is independently associated with ischemic stroke, whereas hypercoagulable states do not appear to be major contributors to the excess stroke risk seen in patients with CD.

Electrocardiographic changes in patients with ischaemic stroke and their prognostic importance.

We investigated prognostic importance of electrocardiographic (ECG) changes in ischaemic stroke patients without primary heart disease because of the limited evidence. This study consisted of 162 patients (92 male, age 64 +/- 14 years) with first ischaemic stroke presenting to hospital during 18 months. One-month mortality was analysed by means of ischaemia-like ECG changes, long QT and arrhythmia. Ischaemia-like ECG changes were observed in 79% of stroke patients and long QTc in 26% and arrhythmias in 44%. Early mortality rate was 27% (n = 44). Age, ST-segment change and abnormal U wave were univariate predictors of early mortality (each p < 0.05). In multivariate analysis, age > 65 years (OR = 1.4, p = 0.02) and presence of ST-segment change (OR = 2.6, p = 0.01) were only independent predictors. Although sensitivity and specificity of ST-segment change were relatively low to identify patients at risk of death, its negative predictive value was 82%. The ECG changes are frequently seen in selected patients with ischaemic stroke. Regardless of origin, ST-segment change can be a predictor of early mortality.

Arrhythmias in rat hearts exposed to pulsed ultrasound after intravenous injection of a contrast agent.

To develop an animal model suitable for characterizing electrocardiographic arrhythmias in hearts exposed to ultrasound after injection of a microbubble contrast agent. Conduction complex and heart lesion data were recorded from 20 rats that received intravenous injections of 0.25 mL of a contrast agent and were exposed to pulsed ultrasound (frequency, 3.1 MHz; pulse duration, 1.3 microseconds; pulse repetition frequency, 1700 Hz; and in situ peak rarefactional pressure, 15.9 MPa). The volume of the contrast agent based on body weight and the mechanical index (ultrasonic pressure) exceeded those used in echocardiography by 14 to 345 and 3 to 29 times, respectively. Premature atrial complexes, premature ventricular complexes, or polymorphic ventricular tachycardia occurred in 10 rats. When ultrasound exposure was halted, arrhythmias ceased but reoccurred in 4 of the 10 rats when exposure resumed. Myocardial degeneration identified by histochemical staining (hematoxylin-basic fuchsinpicric acid) was observed in 16 rats; however, only 10 rats had arrhythmias. There was no significant difference in the amount of histochemical staining in hearts from rats with arrhythmias when compared with rats without arrhythmias. An animal model suitable for characterizing electrocardiographic arrhythmias in rat hearts exposed to ultrasound after injection of a microbubble contrast agent was developed. Because arrhythmias were induced principally when the contrast agent interacted with ultrasound during exposure, the presence of myocardial degeneration alone was not a sufficient explanation for ectopic electrical activity. Under these extreme exposure conditions, the data suggest that pulsed ultrasound through its biomechanical interactions with contrast agents has the potential to induce arrhythmias.