Wave Of Electrocardiogram Research Articles

Automation algorithm to detect and quantify Electrocardiogram waves and intervals

Electrocardiography is the principle of recording the electrical activity of the heart over finite duration of time. It is one of the most practiced methods to detect abnormalities in the heart's electrical, arterial and muscular systems. Electrocardiogram is the voltage versus time graph obtained from the Electrocardiography machine. Automated analysis makes detection of Electrocardiogram findings and consequently determination of pathological abnormalities without human intervention possible. To achieve this goal we process digital Electrocardiograms to quantify the amplitudes and durations of waves and intervals, that is necessary for the automated analysis to find the pathological abnormalities. The proposed method processes Electrocardiograms and localizes the P, Q, R, S and T waves, subsequently it measures the PR, QT and ST intervals and segments.

Characteristics of synthesized right-sided chest electrocardiograms in patients with acute pulmonary embolism

BackgroundThe significance of right-sided chest lead electrocardiogram (ECG) abnormalities in acute pulmonary embolism (APE) is unclear. This study evaluated the characteristics of such abnormalities in APE patients. MethodsThis retrospective study included consecutive patients who were diagnosed with APE by contrast-enhanced computed tomography or pulmonary artery angiography. A standard 12-lead ECG and a synthesized right-sided chest ECG were obtained from these patients. Waveform differences were noted between the acute and post-treatment phases. ResultsIn total, 56 APE patients (18 men and 38 women, mean age 66.7±13.3 years) were included. Traditional ECG findings, such as right-axis deviation, the S1Q3T3 pattern, and clockwise rotation, were found in relatively few patients (14.3%, 32.1%, and 21.4%, respectively). In some cases, a negative T wave in standard 12-lead ECGs was observed in leads III, V1, and V2 (46.4%, 60.7%, and 39.9%, respectively). Syn-V3R ECG showed a higher frequency of negative T waves (66.1%) at the onset and significantly (p<0.01) decreased at the follow-up. Multiple logistic regression analyses for differentiating APE revealed that the negative T waves only in lead syn-V3R were significantly related (odds ratio: 6.95, 95% confidence interval: 2.50–19.32, p<0.001). ConclusionsThe presence of a negative T wave in a synthesized right-sided chest ECG, particularly in the V3R lead, is a new and distinctive finding denoting pulmonary embolism. To confirm the utility of this characteristic using synthesized right-sided chest ECGs for the diagnosis of APE, further studies with larger populations will be required.

Wireless body sensor for electrocardiographic monitoring in dogs and cats

To evaluate the diagnostic utility of electrocardiogram data obtained by a wireless sensor from 36 dogs and four cats with suspected arrhythmias caused by cardiac or systemic diseases. Wireless electrocardiographic recordings were obtained via two precordial electrodes attached to an electrocardiogram sensor connected to a smart device via low-power Bluetooth technology. Cardiac rate, rhythm and duration of P-QRS-T waves were evaluated with VisECG® software. Fifteen- to 30-minute wireless recordings were compared to standard electrocardiograms. Furthermore, the wireless sensor was used in 10 dogs and four cats for 24-hour continuous electrocardiogram monitoring at home. When compared to standard electrocardiogram, equivalent results were obtained for heart rate and duration of different waves. Due to the longer recording time, more arrhythmias were diagnosed with the wireless device in 50% (15 of 30) of animals with arrhythmias. Satisfactory recordings were obtained when the dogs were resting, standing or walking but interpretation of the wireless electrocardiogram signal was not possible during strenuous physical activity. Wireless electrocardiographic monitoring is a reliable and accurate method for identification of heart rate, arrhythmia and duration of electrocardiogram waves. A higher diagnostic yield of arrhythmias was documented with the wireless sensor due to prolonged monitoring. The device offers a good option for the long-term monitoring of canine and feline cardiac rhythm.

The P wave duration in patients with atrial fibrillation undergoing cryoballoon pulmonary vein isolation. Preliminary results.

The pulmonary vein isolation remains the major target of atrial fibrillation ablation. The cryoablation lesions in the left atrium are supposed to disconnect the pulmonary vein from the atrium on the atrial side of the orifices. We hypothesized that the cryoballoon pulmonary vein isolation could result in the prolongation of the P wave duration. The aim of the study was to assess the duration of the P wave in 12-lead electrocardiogram and the influence of pulmonary vein isolation on this parameter. The study group included 21 patients (11 women and 10 men) 66.2+/-7.4 years of age undergoing cryoballoon ablation. In order to measure the P wave duration, we used the constant acquisition of electrogram and the electrocardiographic channels provided by LABSYSTEM™ Pro EP Recording System (Boston Scientific), magnifying the leads 64x. We calculated the duration in the simultaneously recorded 12-lead ECG, from the beginning of the earliest recorded P wave deflection, until the end of the latest P-wave deflection recorded in any lead. The P wave duration in the entire study group was 141.7+/- 12.5 ms before the ablation and increased significantly to 151.1+/-11.5 ms (p<0.05) after the procedure. The respective values in women were 144.1+/-4.3 vs. 156.0+/-4.7 ms (p<0.01) and 139.1+/-4.6 vs. 145.6+/-4.5 ms in men (p<0.05). The mean standard deviation of every single measurement considered separately was 4.4+/- 2.1 ms before the cryoablation and 4.6+/-1.8 ms after the procedure (p= not significant (n.s).), indicating very good reproducibility of the measurements. We concluded, that cryoballoon pulmonary vein isolation leads to the prolongation of the measured P wave duration. It seemed to result from conduction disturbances created by cryoablation. The clinical significance of the observed changes remains unknown.

An SVM approach for identifying atrial fibrillation

Objectives: We designed an automated algorithm to classify short electrocardiogram (ECG) strips into four categories: normal rhythm, atrial fibrillation, noisy segment, or other rhythm disturbances. Approach: The algorithm is based on identification of the R peak and recognition of the other ECG waves. Time-frequency domain features, the average and variability of the intra-beat temporal interval, and the average beat morphology were also calculated. These features (61 features at all) were the input to a support vector machine (SVM) with and without a feed-forward 2-layer neural network consisting of 20 neurons trained on an annotated database. Data were drawn from the PhysioNet Challenge 2017 dataset, consisting of 8528 recordings, of which 60.43% are normal, 0.54% are noisy, 9.04% are AF, and 30% are other rhythm disturbances. The results were validated on 3658 ECG recordings of similar length and percent from each of the four groups. Main results: We used a quadratic SVM classifier with a combination of 61 features to classify the short ECG recordings into one of the four categories mentioned above. The use of an additional neural network to improve the identification of ‘other’ rhythms that were misclassified as ‘normal’ did not statistically affect the results. Our algorithm obtained a total score (F1) of 0.80 on the hidden dataset (placing 18th–24th out of all the algorithms participating in the challenge; places 18–24 received the same score). Significance: Our algorithm was also able to classify AF versus non-AF and normal versus abnormal (arrhythmia or noise) records.

One quarter of total myocardial infarctions are silent manifestation in patients with type 2 diabetes mellitus

BackgroundSilent events with newly developed Q waves in electrocardiogram (ECG) [silent myocardial infarction (MI)] in diabetic patients is reported to be independently associated with an increased risk of fatal MI. However, the incidence rate of silent MI in diabetic patients has yet to be clarified. We sought to determine the incidence rate of first symptomatic MI and silent MI in diabetic patients. MethodsWe conducted a prospective cohort study on patients enrolled in the Japanese primary prevention of atherosclerosis with aspirin for diabetes (JPAD) trial which was started in 2002. It is a randomized controlled trial to examine the efficacy of low-dose aspirin therapy for the primary prevention of atherosclerotic events in type 2 diabetic patients. No patients had Q waves in their ECG before entry to the JPAD trial. We followed-up 1825 patients until July 2015 after completion of the JPAD trial in 2008. The median follow-up period was 10.3 years. We collected 1648 patients’ ECGs to identify patients with silent MI. ResultsSymptomatic MI occurred in 65 patients and silent MI occurred in 22 patients. The incidence rate of symptomatic MI was 4.26 per 1000 patient-years and 1.44 for silent MI in diabetic patients. Thus, 25% of total MIs were silent. Cause-specific Cox proportional hazard model indicated that age (hazard ratio 1.06, 95% confidence interval; 1.03–1.10, p=0.0004) and long history of diabetes (1.00, 1.01–1.07, p=0.01) were independently associated with symptomatic MI, but these were not associated with silent MI. ConclusionsWe demonstrated that incidence rate of first silent MI and that proportion of silent MI to all MIs was 25% in diabetic patients without a history of atherosclerotic events. Diabetic patients frequently need ECG screening for detection of silent MI.

The utility of routine clinical 12-lead ECG in assessing eligibility for subcutaneous implantable cardioverter defibrillator

IntroductionThe subcutaneous implantable cardioverter-defibrillator (S-ICD) is a life-saving device. Recording of a specialized 3-lead electrocardiogram (ECG) is required for S-ICD eligibility assessment. The goals of this study were: (1) evaluate the effect of ECG filtering on S-ICD eligibility, and (2) simplify S-ICD eligibility assessment by development of an S-ICD ineligibility prediction tool, which utilizes the widely available routine 12-lead ECG. Methods and resultsProspective cross-sectional study participants [n = 68; 54% male; 94% white, with wide ranges of age (18–81 y), body mass index (19–53), QRS duration (66–150 ms), and left ventricular ejection fraction (37–77%)] underwent 12-lead supine, 3-lead supine and standing ECG recording. All 3-lead ECG recordings were assessed using the standard S-ICD pre-implantation ECG morphology screening. Backward, stepwise, logistic regression was used to build a model for 12-lead prediction of S-ICD eligibility. Select electrocardiogram waves and complexes: QRS, R-, S, and T-amplitudes on all 12 leads, averaged QT interval, QRS duration, and R/T ratio in the lead with the largest T wave (R/Tmax) were included as predictors. The effect of ECG filtering on ECG morphology was evaluated. A total of 9 participants (13%) failed S-ICD screening prior to filtering. Filtering at 3–40 Hz, similar to the S-ICD default, reduced S-ICD ineligibility to 4%. A regression model that included RII, SII-aVL, TI, II, aVL, aVF, V3-V6, and R/Tmax perfectly predicted S-ICD eligibility, with an Area Under the Receiver Operating Characteristic Curve of 1.0. ConclusionRoutine clinical 12-lead ECG can be used to predict S-ICD eligibility. ECG filtering may improve S-ICD eligibility.

Validity of P-peak to R-peak interval compared to classical PR-interval to assess dynamic beat-to-beat AV conduction variability on surface electrocardiogram

Objective. Duration and dynamic changes of beat-by-beat PR intervals on surface electrocardiogram (ECG) requires accurate determination of QRS complex and P wave boundaries detection, which are influenced by signal-to-noise ratio and morphological variability. Atrioventricular duration (AVD), conventionally measured by PR-interval (ranging from P-onset to QRS-onset), requires adequate signal preprocessing and precise detection of fiducial points of ECG waves. This study aims at applying a method for dynamic beat-to-beat AVD variability measurement, based on the distance between P-wave and R-wave peaks (PR-peaks), and to validate the procedure in two different physical fitness status groups. Approach. The AVD interval was quantified by both conventional (PR-interval) and PR-peaks methods. Fiducial point detection was carried out in three different signal preprocessing conditions (low-pass filtering at 15 Hz, 25 Hz and 35 Hz). A comparative method was adopted to assess ventricular repolarization duration (VRD) measures (conventional QT-interval versus R-wave peak to T-wave interval) as reference of dynamic beat-by-beat variability. Eight male healthy sedentary and eight male elite runners, age, weight and height adjusted underwent 15 min resting ECG recording. Maximal VO2 consumption (VO2MAX) was also assessed defining physical fitness status. Main Results. For 15 Hz, 25 Hz and 35 Hz, the average correlation coefficient (r) values for PR-interval versus PR-peaks and QT-interval versus RT-interval were, respectively, 0.67, 0.59 and 0.50, and 0.76, 0.60 and 0.55. Additionally, for the same cutoff values, correlation coefficient between PSDs of intervals were, respectively, 0.87, 0.81 and 0.73; 0.99, 0.93 and 0.88. Bland Altman plots did not show inter methods differences across all cut-off frequencies. No-significant difference for AVD was observed for inter-group comparison, whereas, on the other hand, VRD was significantly larger in Athletes group. Significance. Assessment of PR-interval using either wave-onset or wave-peak approach as fiducial points provide accurate and precise results, and are appropriate to assess AVD physiological inter-beat interval variation.

Changing Pattern of P and QRS Waves of Electrocardiogram among the Different Grades of Hypertensive Patient of Bangladesh

Background: Determination of the electrocardiographic changes among the hypertensive patients can reveal the early cardiac abnormalities especially of left ventricular hypertrophy.Objectives: The purpose of the present study was to find out the P and QRS waves of electrocardiographic (ECG) changes in different grades of hypertensive patients.Methodology: This cross sectional study was conducted among mild to severe grade hypertensive patients attended in the Department of Medicine at Rajshahi Medical College and Hospital, Rajshahi during the period of July 2009 to June 2010 for a period of one year. Data were collected by face to face interview with a pre-designed structured questionnaire. Measurement of the blood pressure and the 12-lead surface electrocardiogram were done among the study group in a resting state.Results: A total number of 400 hypertensive patients were recruited for this study. In mild hypertension, high voltage QRS complex was noted as the main ECG abnormality (24.8%) which was followed by wide P-wave (15.2%). In moderate hypertension, the high voltage QRS complex was 31.0%, wide P wave 25.0%. In severe hypertension, wide P wave and high voltage QRS complex were 56.0%and 20.0% cases respectively. Chi-square test was done between category of hypertension and ECG changes of the study group. The results were statistically highly significant (p&lt;0.001).Conclusions: The study results revealed an association between hypertension and ECG changes which was more pronounced in severe hypertension.Journal of Current and Advance Medical Research 2016;3(2):33-38

Biometric and Emotion Identification: An ECG Compression Based Method.

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state. The use of information-theoretic data models, associated with data compression algorithms, allowed to effectively compare ECG records and infer the person identity, as well as emotional state at the time of data collection. The proposed method does not require ECG wave delineation or alignment, which reduces preprocessing error. The method is divided into three steps: (1) conversion of the real-valued ECG record into a symbolic time-series, using a quantization process; (2) conditional compression of the symbolic representation of the ECG, using the symbolic ECG records stored in the database as reference; (3) identification of the ECG record class, using a 1-NN (nearest neighbor) classifier. We obtained over 98% of accuracy in biometric identification, whereas in emotion recognition we attained over 90%. Therefore, the method adequately identify the person, and his/her emotion. Also, the proposed method is flexible and may be adapted to different problems, by the alteration of the templates for training the model.

Design of High-Performance ECG Detector for Implantable Cardiac Pacemaker Systems using Biorthogonal Wavelet Transform

A digital electrocardiogram (ECG) detector with low power consumption and high performance based on biorthogonal 2.2 wavelet transform and applicable for the modern implantable cardiac pacemakers is proposed in the present work. Biorthogonal 2.2 wavelet transform is chosen due to its high SNR, less number of coefficients, resemblance of shape with ECG wave and ability to increase QRS complex detection performance. Architecture of the proposed ECG detector includes modified biorthogonal 2.2 wavelet filter bank and a modified soft threshold-based QRS complex detector. Three low-pass filters and one high-pass filter with pipelined architecture are used which are lesser than the earlier designed detectors. Various blocks of proposed detector are designed to denoise the input ECG signal and then to find the correct location of R-wave. Verilog hardware description language for design entry, Modelsim embedded in Xilinx ISE v.14.1 for simulation, Virtex-6 FPGAs for synthesis and Xilinx ISE tools are used to measure the performance, area and power of the proposed ECG detector and its constituent blocks. A low detection error rate of 0.13%, positive predictivity ( $$\hbox {P}^{+}$$ ) of 99.94% and sensitivity ( $$\hbox {S}_{\mathrm{e}}$$ ) of 99.92% are achieved for the proposed ECG detector which are better compared to the previous results. Also, it consumes only 20 mW of total power at 50 KHz and shows the overall delay of 18.924 ns which makes it useful for the low power and high-performance applications.

Optimizing the Detection of Characteristic Waves in ECG Based on Processing Methods Combinations

Accurate detection of characteristic electrocardiogram (ECG) waves is necessary for ECG analysis and interpretation. In this paper, we distinguish four processing steps of detection algorithms: noise and artifacts reduction, transformations, fiducial marks selection of wave candidates, and decision rule. Processing steps combinations from several detection algorithms are used to find QRS, P, and T wave peaks. In addition, we consider the search window parameter modification based on waveform templates extracted by heart cycles clustering. The methods are extensively evaluated on two public ECG databases containing QRS, P, and T wave peaks annotations. We found that the combination of morphological mathematical filtering with Elgendi’s algorithm works best for QRS detection on MIT-BIH Arrhythmia Database (detection error rate (DER = 0.48%, Lead I). The combination of modified Martinez’s PT and wavelet transform (WT) methods gave the best results for P wave peaks detection on both databases, when both leads are considered (MIT-BIH arrhythmia database: DER = 32.13%, Lead I, DER = 42.52%, Lead II; QT Database: DER = 21.23%, Lead I, DER = 26.80%, Lead II). Waveform templates in combination with Martinez’s WT obtained the best results for T wave peaks detection on QT database (DER = 25.15%, Lead II). This paper demonstrates that combining some of the best proposed methods in literature leads to improvements over the original methods for ECG waves detection while maintaining satisfactory computation times.

Effect of Arrhythmias on Tissue Doppler Velocities

Sa wave of tissue Doppler imaging correlates with ventricular systole (QRS-T of electrocardiogram). Ea wave correlates with ventricular filling in early diastole. Aa wave correlates with ventricular filling during atrial contraction and correlates with P wave of electrocardiogram. Therefore, a careful analysis of the relation between Ea and Aa waves gives a correct impression about the underlying cardiac arrhythmia. In sinus bradycardia, all waves are normal, but the distance between Ea and Aa wave is increased. In sinus tachycardia, Aa wave comes closer to Ea wave and may even fuse with Ea wave due to shortened diastole. Prematurely occurring Aa wave suggests atrial premature beat. The absence of Aa wave suggests atrial fibrillation. More than one Aa wave per cardiac cycle suggests atrial flutter. Premature Sa wave suggests ventricular premature beat. Increased distance between Aa wave and Sa wave suggests first-degree atrioventricular (AV) block. Progressive decrease of the distance between Ea and Aa waves till one Aa wave fuses with preceding Ea wave followed by a pause suggests Wenckebach phenomenon. In 2:1 AV block, one Aa wave is fused with Ea wave and the next Aa wave is followed by Sa and Ea waves. Sa and Ea waves occur regularly at a slow rate and Aa wave occurs regularly at a fast rate; thus, total dissociation between Ea and Aa waves suggests complete AV block. Usually, the person performing echocardiography is not aware of electrocardiography (ECG) findings. Clinicians may not be aware of the ECG findings when they are interpreting the tissue Doppler images. Further, arrhythmia recorded during tissue Doppler imaging need not necessarily be present in the 10 s ECG recorded routinely. Knowledge of the effect of arrhythmia on tissue Doppler findings helps in correct interpretation of the tissue Doppler findings.

Ischemia and Arrhythmia Classification Using Time-Frequency Domain Features of QRS Complex

The QRS complex is the significant wave of electrocardiogram (ECG) and occurs during ventricular depolarization. If the synchronization problem (i.e., depolarization) occurs between endocardial cardiomyocytes and outer layers, then abnormal morphological changes in QRS complex take place which is possible in case of arrhythmia and ischemia. The proposed approach describes time domain measures of such alterations (i.e., the ratio of average rise & fall amplitude and interval) of QRS complex along with the frequency domain feature i.e., peak frequency and power of mean QRS complexes. An improvised Difference Operation Method (DOM) (Yeh Yun-Chi et al., 2008) is implemented with added features like preprocessing techniques (e.g., baseline drifts and noise cancellation). The proposed methodology is evaluated with the standard databases, i.e., FANTASIA (healthy subjects), MIT-BIH Arrhythmia database (MITDB), and European ST-T database (EDB) respectively. Linear Discriminant Analysis (LDA) and decision tree are carried out for classification healthy, arrhythmic and ischemic subjects incorporating the time-frequency domain characteristics. The Naive Bayes’ Classifiers also implemented where these two classes, i.e., ischemia and arrhythmia are visually distinguished by convergently spreading in different areas. Real-time hardware validation of this approach has also executed. The future scope of this approach is to be validated with ischemia-induced arrhythmia subjects for precise identification and classification.

Electrocardiogram Delineation in a Wistar Rat Experimental Model

Background and Objectives The extensive use of electrocardiogram (ECG) recordings during experimental protocols using small rodents requires an automatic delineation technique in the ECG with high performance. It has been shown that the wavelet transform (WT) based ECG delineator is a suitable tool to delineate electrocardiographic waveforms. The aim of this work is to implement and evaluate the ECG waves delineation in Wistar rats applying WT. We also describe the ECG signal of the Wistar rats giving the characteristics of its spectrum among other useful information. Methods We evaluated a delineator based on WT in a Wistar rat electrocardiograms database which was annotated manually by experienced observers. Results The delineation showed an “overall performance” such as sensitivity and a positive predictive value of 99.2% and 83.9% for P-wave, 100% and 99.9% for QRS complex, and 100% and 99.8% for T-wave, respectively. We also compared temporal analysis based ECG delineator with the WT based ECG delineator in RR interval, QRS duration, QT interval, and T-wave peak-to-end duration. The results showed that WT outperforms the temporal delineation technique in all parameters analyzed. Conclusions Finally, we propose a WT based ECG delineator as a methodology to implement in a wide diversity of experimental ECG analyses using Wistar rats.

Evaluation of left and right atrial synchrony in patients with sick sinus syndrome before and after pacemaker implantation by tissue Doppler ultrasonography

Objective To evaluate the intra- and interatrial synchronization before and after pacemaker implantation in patients with sick sinus syndrome (SSS) by tissue Doppler imaging (TDI). Methods Thirty-eight patients with SSS (SSS group) underwent pacemaker implantation.Echocardiography was performed before and after operation. Twenty-five volunteers were chosen as control group. Routine measurement of left and right atrial diameter by echocardiography. In apical four chamber view, the sample volume of TDI was located at right atrial lateral wall at tricuspid annulus, interatrial septum and left atrial lateral wall at mitral annulus. The interval time between the early diastolic wave (E wave) and the late diastolic wave (A wave) (E-AR, E-AI, E-AL), and the duration of A wave (AR, AI, AL) were measured. At the same time, the electromechanical coupling time was measured, namely the initiation of the P wave of the synchronous electrocardiogram to the starting point of A wave (P-A0R, P-A0I, P-A0L), and the starting point of the P wave to the peak point of the A wave (P-AR, P-AI, P-AL). And the right atrial electromechanical delay time, P-A0I and P-A0R value (T0IR), P-AI value and P-AR value (TIR) were recorded.Other parameters include left atrial electromechanical delay time: P-A0L and P-A0I value (T0LI), and P-AL and P-AI value (TLI); interatrial electromechanical delay time: P-A0L and P-A0R value (T0LR), P-AL and P-AR (TLR) were recorded. Results Compared with the control group, left atrium and right atrium in SSS group enlarged before operation, E-AR, E-AI, E-AL, P-A0R, P-A0I, P-AR, P-AL prolonged, while T0LR and T0LI were shortened (all P<0.05). Postoperative changes in SSS group patients included shortened E-AR, E-AI and E-AL, and prolonged T0LI and T0LR (all P<0.05). Compared with the control group, the size of left atriums and right atriums in SSS group still increased postoperation, and the P-A0I、P-AR and P-AL remained longer (all P<0.05). The same as the control group, the postoperative AR, AI and AL in SSS group were decreased successively (all P<0.05). Conclusions In SSS patients, electromechanical asynchrony exists in different part of atrium and between left atrium and right atrium. Pacemaker therapy can improve atrial electromechanical synchronicity. Key words: Echocardiography; Sick sinus syndrome; Atrial function; Cardiac pacing, artificial

Impact of right ventricular distensibility on congestive heart failure with preserved left ventricular ejection fraction in the elderly.

To elucidate involvement of age-related impairments of right ventricular (RV) distensibility in the elderly congestive heart failure (CHF), we examined the prevalence of less-distensible right ventricle in patients with preserved left ventricular ejection fraction (LVEF) over a wide range of ages. In 893 patients aged from 40 to 102years, we simultaneously recorded electrocardiogram, phonocardiogram, and jugular venous pulse wave. Using signal-processing techniques, the prominent 'Y' descent of jugular pulse waveform was detected as a hemodynamic sign of a less-distensible right ventricle. Prevalence of less-distensible right ventricle and elevated RV systolic pressure increased along with aging from the 50s to the 90s in an exponential fashion from 3.3 and 12% up to 33 and 61%, respectively (p<0.001 for each). This age-dependent deterioration of ventricular distensibility was not observed for the left ventricle. Higher age and higher RV systolic pressure were independently associated with less-distensible right ventricle (Odds ratio, 1.05 per 1year, p=0.003; and 1.03 per 1mmHg, p=0.026, respectively). The elderly CHF was associated with high prevalence of the less-distensible right ventricle and higher RV systolic pressure, both of which were independent risk factors for CHF (Odds ratio, 5.27, p=0.001, and 1.08 per 1mmHg, p<0.001, respectively). In elderly patients with preserved LVEF, the combination of a less-distensible right ventricle and a high RV systolic pressure seems to be related to developing CHF. The less-distensible right ventricle and elevated RV systolic pressure are closely associated with CHF with preserved LVEF in the elderly patients.

Ventricular Aneurysm: Diagnosis and Treatment.

Ventricular Aneurysm: Diagnosis and Treatment.

Diagnostic decision support systems for atrial fibrillation based on a novel electrocardiogram approach

BackgroundThe electrocardiogram (ECG) is one of the most non-invasive techniques to give support to the atrial fibrillation (AF) diagnosis. Several authors use the temporal difference between two consecutive R waves, a method known as RR interval, to perform the AF diagnosis. However, RR interval-based analysis does not detect distortions on the other ECG waves. PurposeThus, the present work proposes a diagnostic decision support systems for AF based on higher order spectrum analysis of the voltage variation on the ECG.. MethodsThe proposed method was used aiming AF classifying. The classifier is composed by two screening stages: one based on the average and another on the average deviation of kurtosis of the ECG signals. Heartbeat obtained from the MIT-BIH atrial fibrillation and MIT-BIH normal were used. ResultsECG signal featured by kurtosis outperforms second order statistics based metrics in up to 476 times, and up to 110 times above the RR interval. The screening methods obtained sensitivity equal to 100% and specificity is up to 84.04%. The two screening methods combined provided an AF classifier with an accuracy rate at diagnosis of 100%. The results presented take into account windows of up to five heartbeats and a 99.73% confidence interval. ConclusionThe results obtained by the proposed method can be used to support decision-making in clinical practices with a diagnostic accuracy rate of 90.04% to 100%.

Nadir görülen non-kardiyak troponin yüksekliği nedeni: Akut kolesistit; olgu sunumu

Objective: Cardiac troponins are accepted as the standard markers for diagnosis and risk management of patients with acute coronary syndromes. However, cardiac troponins are elevated in some patients presenting with non-cardiac situations. In this paper, a rare case of non-cardiac troponin elevation with acute cholecystitis is presented. Case: A 56 year old female patient admitted to the emergency room with pain in the epigastric region. The abdominal ultrasound revealed acute cholecystitis. She had some coronary risk factors and electrocardiogram showed no segment deviation but troponin was positive. Acute coronary syndrome couldn’t be ruled out and coronary angiography revealed normal coronary arteries. Therefore, elevated troponin was linked to acute cholecystitis. Conclusion: Although troponin elevation is a cornerstone marker for diagnosis the patients with acute coronary syndromes, there are various conditions with non-coronary-related troponin elevations. This can lead to misdiagnosis and unnecessary interventions. As a result, in patients with similar sypmtoms (pain in the epigastric region), electrocardiogram wave changes and elevated troponin levels, acute cholesystitis diagnosis should be considered.