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Dynamic ECG features for atrial fibrillation recognition

Abdul-Kadir NA, Mat Safri N, Othman MA

Comput Methods Programs Biomed, 2016 Nov;136:143-50.
PMID: 27686711 DOI: 10.1016/j.cmpb.2016.08.021

BACKGROUND: Atrial fibrillation (AF) can cause the formation of blood clots in the heart. The clots may move to the brain and cause a stroke. Therefore, this study analyzed the ECG features of AF and normal sinus rhythm signals for AF recognition which were extracted by using a second-order dynamic system (SODS) concept.
OBJECTIVE: To find the appropriate windowing length for feature extraction based on SODS and to determine a machine learning method that could provide higher accuracy in recognizing AF.
METHOD: ECG features were extracted based on a dynamic system (DS) that uses a second-order differential equation to describe the short-term behavior of ECG signals according to the natural frequency (ω), damping coefficient, (ξ), and forcing input (u). The extracted features were windowed into 2, 3, 4, 6, 8, and 10 second episodes to find the appropriate windowing size for AF signal processing. ANOVA and t-tests were used to determine the significant features. In addition, pattern recognition machine learning methods (an artificial neural network (ANN) and a support vector machine (SVM)) with k-fold cross validation (k-CV) were used to develop the ECG recognition system.
RESULTS: Significant differences (p

Matched MeSH terms: Electrocardiography/methods*
Atrial fibrillation classification and association between the natural frequency and the autonomic nervous system

Abdul-Kadir NA, Mat Safri N, Othman MA

Int J Cardiol, 2016 Nov 01;222:504-8.
PMID: 27505342 DOI: 10.1016/j.ijcard.2016.07.196

BACKGROUND: The feasibility study of the natural frequency (ω) obtained from a second-order dynamic system applied to an ECG signal was discovered recently. The heart rate for different ECG signals generates different ω values. The heart rate variability (HRV) and autonomic nervous system (ANS) have an association to represent cardiovascular variations for each individual. This study further analyzed the ω for different ECG signals with HRV for atrial fibrillation classification.
METHODS: This study used the MIT-BIH Normal Sinus Rhythm (nsrdb) and MIT-BIH Atrial Fibrillation (afdb) databases for healthy human (NSR) and atrial fibrillation patient (N and AF) ECG signals, respectively. The extraction of features was based on the dynamic system concept to determine the ω of the ECG signals. There were 35,031 samples used for classification.
RESULTS: There were significant differences between the N & NSR, N & AF, and NSR & AF groups as determined by the statistical t-test (p<0.0001). There was a linear separation at 0.4s(-1) for ω of both databases upon using the thresholding method. The feature ω for afdb and nsrdb falls within the high frequency (HF) and above the HF band, respectively. The feature classification between the nsrdb and afdb ECG signals was 96.53% accurate.
CONCLUSIONS: This study found that features of the ω of atrial fibrillation patients and healthy humans were associated with the frequency analysis of the ANS during parasympathetic activity. The feature ω is significant for different databases, and the classification between afdb and nsrdb was determined.

Matched MeSH terms: Electrocardiography/classification*
Linear and nonlinear analysis of normal and CAD-affected heart rate signals

Acharya UR, Faust O, Sree V, Swapna G, Martis RJ, Kadri NA, et al.

Comput Methods Programs Biomed, 2014;113(1):55-68.
PMID: 24119391 DOI: 10.1016/j.cmpb.2013.08.017

Coronary artery disease (CAD) is one of the dangerous cardiac disease, often may lead to sudden cardiac death. It is difficult to diagnose CAD by manual inspection of electrocardiogram (ECG) signals. To automate this detection task, in this study, we extracted the heart rate (HR) from the ECG signals and used them as base signal for further analysis. We then analyzed the HR signals of both normal and CAD subjects using (i) time domain, (ii) frequency domain and (iii) nonlinear techniques. The following are the nonlinear methods that were used in this work: Poincare plots, Recurrence Quantification Analysis (RQA) parameters, Shannon entropy, Approximate Entropy (ApEn), Sample Entropy (SampEn), Higher Order Spectra (HOS) methods, Detrended Fluctuation Analysis (DFA), Empirical Mode Decomposition (EMD), Cumulants, and Correlation Dimension. As a result of the analysis, we present unique recurrence, Poincare and HOS plots for normal and CAD subjects. We have also observed significant variations in the range of these features with respect to normal and CAD classes, and have presented the same in this paper. We found that the RQA parameters were higher for CAD subjects indicating more rhythm. Since the activity of CAD subjects is less, similar signal patterns repeat more frequently compared to the normal subjects. The entropy based parameters, ApEn and SampEn, are lower for CAD subjects indicating lower entropy (less activity due to impairment) for CAD. Almost all HOS parameters showed higher values for the CAD group, indicating the presence of higher frequency content in the CAD signals. Thus, our study provides a deep insight into how such nonlinear features could be exploited to effectively and reliably detect the presence of CAD.

Matched MeSH terms: Electrocardiography
A deep convolutional neural network model to classify heartbeats

Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adam M, Gertych A, et al.

Comput Biol Med, 2017 10 01;89:389-396.
PMID: 28869899 DOI: 10.1016/j.compbiomed.2017.08.022

The electrocardiogram (ECG) is a standard test used to monitor the activity of the heart. Many cardiac abnormalities will be manifested in the ECG including arrhythmia which is a general term that refers to an abnormal heart rhythm. The basis of arrhythmia diagnosis is the identification of normal versus abnormal individual heart beats, and their correct classification into different diagnoses, based on ECG morphology. Heartbeats can be sub-divided into five categories namely non-ectopic, supraventricular ectopic, ventricular ectopic, fusion, and unknown beats. It is challenging and time-consuming to distinguish these heartbeats on ECG as these signals are typically corrupted by noise. We developed a 9-layer deep convolutional neural network (CNN) to automatically identify 5 different categories of heartbeats in ECG signals. Our experiment was conducted in original and noise attenuated sets of ECG signals derived from a publicly available database. This set was artificially augmented to even out the number of instances the 5 classes of heartbeats and filtered to remove high-frequency noise. The CNN was trained using the augmented data and achieved an accuracy of 94.03% and 93.47% in the diagnostic classification of heartbeats in original and noise free ECGs, respectively. When the CNN was trained with highly imbalanced data (original dataset), the accuracy of the CNN reduced to 89.07%% and 89.3% in noisy and noise-free ECGs. When properly trained, the proposed CNN model can serve as a tool for screening of ECG to quickly identify different types and frequency of arrhythmic heartbeats.

Matched MeSH terms: Electrocardiography*
Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals

Adam M, Oh SL, Sudarshan VK, Koh JE, Hagiwara Y, Tan JH, et al.

Comput Methods Programs Biomed, 2018 Jul;161:133-143.
PMID: 29852956 DOI: 10.1016/j.cmpb.2018.04.018

Cardiovascular diseases (CVDs) are the leading cause of deaths worldwide. The rising mortality rate can be reduced by early detection and treatment interventions. Clinically, electrocardiogram (ECG) signal provides useful information about the cardiac abnormalities and hence employed as a diagnostic modality for the detection of various CVDs. However, subtle changes in these time series indicate a particular disease. Therefore, it may be monotonous, time-consuming and stressful to inspect these ECG beats manually. In order to overcome this limitation of manual ECG signal analysis, this paper uses a novel discrete wavelet transform (DWT) method combined with nonlinear features for automated characterization of CVDs. ECG signals of normal, and dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI) are subjected to five levels of DWT. Relative wavelet of four nonlinear features such as fuzzy entropy, sample entropy, fractal dimension and signal energy are extracted from the DWT coefficients. These features are fed to sequential forward selection (SFS) technique and then ranked using ReliefF method. Our proposed methodology achieved maximum classification accuracy (acc) of 99.27%, sensitivity (sen) of 99.74%, and specificity (spec) of 98.08% with K-nearest neighbor (kNN) classifier using 15 features ranked by the ReliefF method. Our proposed methodology can be used by clinical staff to make faster and accurate diagnosis of CVDs. Thus, the chances of survival can be significantly increased by early detection and treatment of CVDs.

Matched MeSH terms: Electrocardiography*
Fulltext Wellen's syndrome: Challenges in diagnosis

Agarwal A, Vyas S, Kumar R

Malays Fam Physician, 2015;10(3):35-7.
PMID: 27570607

Wellen's syndrome is a pre-infarction stage of coronary artery disease characterised by predefined clinical and electrocardiographic (ECG) criteria of a subgroup of patients with myocardial ischaemia. Early recognition and appropriate intervention of this syndrome carry significant diagnostic and prognostic value. We report this unusual syndrome in an elderly man who presented with recurrent angina and characteristic ECG changes as T-waves inversion in the precordial leads, especially in V2-V6 during pain-free periods and ECG obtained during episodes of pain demonstrating upright T-waves with possible elevated ST segments from V1-V4. Cardiac enzymes were positive and coronary angiography revealed critical stenosis in the proximal left anterior descending artery. It is important to timely identify this condition and intervene appropriately as these patients may develop extensive myocardial infarction that carries a significant morbidity and mortality.

Matched MeSH terms: Electrocardiography
Fulltext A comparison of enoxaparin with unfractionated heparins in patients with coronary heart disease in an emergency department in rural South Indian tertiary care teaching hospital

Ahmad A, Patel I, Asani H, Jagadeesan M, Parimalakrishnan S, Selvamuthukumaran S

Indian J Pharmacol, 2015 Jan-Feb;47(1):90-4.
PMID: 25821318 DOI: 10.4103/0253-7613.150360

Antithrombotic therapy with heparin plus antiplatelets reduces the rate of ischemic events in patients with coronary heart disease. Low molecular weight heparin has a more predictable anticoagulant effect than standard unfractionated heparin, is easier to administer, does not require monitoring and is associated with less ADRs. The purpose of the present study was to evaluate and compare the clinical and cost outcomes of Enoxaparin with a standard unfractionated heparin in patients with coronary heart disease.

Matched MeSH terms: Electrocardiography
Fulltext Age-dependent electrocardiographic changes in Pgc-1β deficient murine hearts

Ahmad S, Valli H, Salvage SC, Grace AA, Jeevaratnam K, Huang CL

Clin Exp Pharmacol Physiol, 2018 02;45(2):174-186.
PMID: 28949414 DOI: 10.1111/1440-1681.12863

Increasing evidence implicates chronic energetic dysfunction in human cardiac arrhythmias. Mitochondrial impairment through Pgc-1β knockout is known to produce a murine arrhythmic phenotype. However, the cumulative effect of this with advancing age and its electrocardiographic basis have not been previously studied. Young (12-16 weeks) and aged (>52 weeks), wild type (WT) (n = 5 and 8) and Pgc-1β-/- (n = 9 and 6), mice were anaesthetised and used for electrocardiographic (ECG) recordings. Time intervals separating successive ECG deflections were analysed for differences between groups before and after β1-adrenergic (intraperitoneal dobutamine 3 mg/kg) challenge. Heart rates before dobutamine challenge were indistinguishable between groups. The Pgc-1β-/- genotype however displayed compromised nodal function in response to adrenergic challenge. This manifested as an impaired heart rate response suggesting a functional defect at the level of the sino-atrial node, and a negative dromotropic response suggesting an atrioventricular conduction defect. Incidences of the latter were most pronounced in the aged Pgc-1β-/- mice. Moreover, Pgc-1β-/- mice displayed electrocardiographic features consistent with the existence of a pro-arrhythmic substrate. Firstly, ventricular activation was prolonged in these mice consistent with slowed action potential conduction and is reported here for the first time. Additionally, Pgc-1β-/- mice had shorter repolarisation intervals. These were likely attributable to altered K+ conductance properties, ultimately resulting in a shortened QTc interval, which is also known to be associated with increased arrhythmic risk. ECG analysis thus yielded electrophysiological findings bearing on potential arrhythmogenicity in intact Pgc-1β-/- systems in widespread cardiac regions.

Matched MeSH terms: Electrocardiography*
Methyl Gallate Attenuates Doxorubicin-Induced Cardiotoxicity in Rats by Suppressing Oxidative Stress

Ahmed AZ, Satyam SM, Shetty P, D'Souza MR

Scientifica (Cairo), 2021;2021:6694340.
PMID: 33510932 DOI: 10.1155/2021/6694340

Doxorubicin-induced cardiotoxicity is the leading cause of morbidity and mortality among cancer survivors. The present study was aimed to investigate the cardioprotective potential of methyl gallate; an active polyphenolic nutraceutical, against doxorubicin-induced cardiotoxicity in Wistar rats. Twenty-four female Wistar rats (150-200 g) were divided into four groups (n = 6) which consist of normal control (group I), doxorubicin control (group II), test-A (group III), and test-B (group IV). Group III and group IV animals were prophylactically treated with methyl gallate 150 mg/kg/day and 300 mg/kg/day orally, respectively, for seven days. Doxorubicin (25 mg/kg; single dose) was administered through an intraperitoneal route to group II, III, and IV animals on the seventh day to induce acute cardiotoxicity. On the 8th day, besides ECG analysis, serum CK, CK-MB, LDH, AST, MDA, and GSH were assayed. Following gross examination of isolated hearts, histopathological evaluation was performed by light microscopy. A significant (p

Matched MeSH terms: Electrocardiography
Fulltext Chia Seed Oil Ameliorates Doxorubicin-Induced Cardiotoxicity in Female Wistar Rats: An Electrocardiographic, Biochemical and Histopathological Approach

Ahmed AZ, Mumbrekar KD, Satyam SM, Shetty P, D'Souza MR, Singh VK

Cardiovasc Toxicol, 2021 Jul;21(7):533-542.
PMID: 33740233 DOI: 10.1007/s12012-021-09644-3

Doxorubicin (DOX) is a potent anti-cancer antibiotic that was widely used for treatment of various cancers. It produces free radicals which result in extreme dose-limiting cardiotoxicity. This study investigated the cardioprotective potential of chia seed oil, an active polyphenolic nutraceutical against doxorubicin-induced cardiotoxicity in Wistar rats. Twenty-four female Wistar rats were divided into four groups (n = 6) which consist of normal control, DOX control, test-A and test-B group. Animals were prophylactically treated with two different doses of test drug, i.e. chia seed oil 2.5 ml/kg/day and 5 ml/kg/day in test-A and test-B groups orally for 7 days. Doxorubicin (25 mg/kg; single dose) was administered intraperitoneally to DOX control, Test-A and Test-B animals on the seventh day to induce cardiotoxicity. ECG analysis was done before and after treatment. Besides ECG, CK, CK-MB, LDH, AST, MDA and GSH were analyzed. DOX had significantly altered ECG, CK, CK-MB, LDH, AST, MDA and GSH. Pre-treatment with chia seed oil significantly alleviated DOX-induced ECG changes and also guarded against DOX-induced rise of serum CK, CK-MB and AST levels. Chia seed oil alleviated histopathological alteration in DOX-treated rats. It also significantly inhibited DOX-induced GSH depletion and elevation of MDA. The present study revealed that chia seed oil exerts cardioprotection against doxorubicin-induced cardiotoxicity in female Wistar rats. Our study opens the perspective to clinical studies to precisely consider chia seed oil as a potential chemoprotectant nutraceutical in the combination chemotherapy with doxorubicin to limit its cardiotoxicity.

Matched MeSH terms: Electrocardiography*
Fulltext Invasive and antiplatelet treatment of patients with non-ST-segment elevation myocardial infarction: Understanding and addressing the global risk-treatment paradox

Ahrens I, Averkov O, Zúñiga EC, Fong AYY, Alhabib KF, Halvorsen S, et al.

Clin Cardiol, 2019 Oct;42(10):1028-1040.
PMID: 31317575 DOI: 10.1002/clc.23232

Clinical guidelines for the treatment of patients with non-ST-segment elevation myocardial infarction (NSTEMI) recommend an invasive strategy with cardiac catheterization, revascularization when clinically appropriate, and initiation of dual antiplatelet therapy regardless of whether the patient receives revascularization. However, although patients with NSTEMI have a higher long-term mortality risk than patients with ST-segment elevation myocardial infarction (STEMI), they are often treated less aggressively; with those who have the highest ischemic risk often receiving the least aggressive treatment (the "treatment-risk paradox"). Here, using evidence gathered from across the world, we examine some reasons behind the suboptimal treatment of patients with NSTEMI, and recommend approaches to address this issue in order to improve the standard of healthcare for this group of patients. The challenges for the treatment of patients with NSTEMI can be categorized into four "P" factors that contribute to poor clinical outcomes: patient characteristics being heterogeneous; physicians underestimating the high ischemic risk compared with bleeding risk; procedure availability; and policy within the healthcare system. To address these challenges, potential approaches include: developing guidelines and protocols that incorporate rigorous definitions of NSTEMI; risk assessment and integrated quality assessment measures; providing education to physicians on the management of long-term cardiovascular risk in patients with NSTEMI; and making stents and antiplatelet therapies more accessible to patients.

Matched MeSH terms: Electrocardiography
Prolonged QT predicts prognosis in COVID-19

Akhtar Z, Gallagher MM, Yap YG, Leung LWM, Elbatran AI, Madden B, et al.

Pacing Clin Electrophysiol, 2021 05;44(5):875-882.
PMID: 33792080 DOI: 10.1111/pace.14232

BACKGROUND: Coronavirus disease-2019 (COVID-19) causes severe illness and multi-organ dysfunction. An abnormal electrocardiogram is associated with poor outcome, and QT prolongation during the illness has been linked to pharmacological effects. This study sought to investigate the effects of the COVID-19 illness on the corrected QT interval (QTc).
METHOD: For 293 consecutive patients admitted to our hospital via the emergency department for COVID-19 between 01/03/20 -18/05/20, demographic data, laboratory findings, admission electrocardiograph and clinical observations were compared in those who survived and those who died within 6 weeks. Hospital records were reviewed for prior electrocardiograms for comparison with those recorded on presentation with COVID-19.
RESULTS: Patients who died were older than survivors (82 vs 69.8 years, p 455 ms (males) and >465 ms (females) (p = 0.028, HR 1.49 [1.04-2.13]), as predictors of mortality. QTc prolongation beyond these dichotomy limits was associated with increased mortality risk (p = 0.0027, HR 1.78 [1.2-2.6]).
CONCLUSION: QTc prolongation occurs in COVID-19 illness and is associated with poor outcome.

Matched MeSH terms: Electrocardiography
Wavelet-based Encoding Scheme for Controlling Size of Compressed ECG Segments in Telecardiology Systems

Al-Busaidi AM, Khriji L, Touati F, Rasid MF, Mnaouer AB

J Med Syst, 2017 Sep 12;41(10):166.
PMID: 28900815 DOI: 10.1007/s10916-017-0817-1

One of the major issues in time-critical medical applications using wireless technology is the size of the payload packet, which is generally designed to be very small to improve the transmission process. Using small packets to transmit continuous ECG data is still costly. Thus, data compression is commonly used to reduce the huge amount of ECG data transmitted through telecardiology devices. In this paper, a new ECG compression scheme is introduced to ensure that the compressed ECG segments fit into the available limited payload packets, while maintaining a fixed CR to preserve the diagnostic information. The scheme automatically divides the ECG block into segments, while maintaining other compression parameters fixed. This scheme adopts discrete wavelet transform (DWT) method to decompose the ECG data, bit-field preserving (BFP) method to preserve the quality of the DWT coefficients, and a modified running-length encoding (RLE) scheme to encode the coefficients. The proposed dynamic compression scheme showed promising results with a percentage packet reduction (PR) of about 85.39% at low percentage root-mean square difference (PRD) values, less than 1%. ECG records from MIT-BIH Arrhythmia Database were used to test the proposed method. The simulation results showed promising performance that satisfies the needs of portable telecardiology systems, like the limited payload size and low power consumption.

Matched MeSH terms: Electrocardiography*
Machine learning-based coronary artery disease diagnosis: A comprehensive review

Alizadehsani R, Abdar M, Roshanzamir M, Khosravi A, Kebria PM, Khozeimeh F, et al.

Comput Biol Med, 2019 08;111:103346.
PMID: 31288140 DOI: 10.1016/j.compbiomed.2019.103346

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often leads to a heart attack. It annually causes millions of deaths and billions of dollars in financial losses worldwide. Angiography, which is invasive and risky, is the standard procedure for diagnosing CAD. Alternatively, machine learning (ML) techniques have been widely used in the literature as fast, affordable, and noninvasive approaches for CAD detection. The results that have been published on ML-based CAD diagnosis differ substantially in terms of the analyzed datasets, sample sizes, features, location of data collection, performance metrics, and applied ML techniques. Due to these fundamental differences, achievements in the literature cannot be generalized. This paper conducts a comprehensive and multifaceted review of all relevant studies that were published between 1992 and 2019 for ML-based CAD diagnosis. The impacts of various factors, such as dataset characteristics (geographical location, sample size, features, and the stenosis of each coronary artery) and applied ML techniques (feature selection, performance metrics, and method) are investigated in detail. Finally, the important challenges and shortcomings of ML-based CAD diagnosis are discussed.

Matched MeSH terms: Electrocardiography
Fulltext QTc Interval Prolongation and Hemorrhagic Stroke: Any Difference Between Acute Spontaneous Intracerebral Hemorrhage and Acute Non-traumatic Subarachnoid Hemorrhage?

Amin OSM, Al-Bajalan SJ, Mubarak A

Med Arch, 2017 Jun;71(3):193-197.
PMID: 28974832 DOI: 10.5455/medarh.2017.71.193-197

BACKGROUND: A variety of ECG changes occur as an aftermath of stroke. Prolongation of the QTc interval is a well-documented change. We analyzed QTc interval prolongation among patients with acute hemorrhagic strokes.
METHODS: This observational study was conducted at the Emergency Department of Sulaymaniyah General Teaching Hospital and Shar Hospital from September 1st, 2014 to August 31st, 2015. Fifty patients who developed acute spontaneous hypertensive intracerebral hemorrhage (ICH) and 50 patients who developed acute non-traumatic subarachnoid hemorrhage (SAH) were included in the study. All patients underwent resting 12-lead ECG within half an hour of admission. The QTc interval was calculated and analyzed in those 100 patients.
RESULTS: Females (62%) outnumbered males (38%) with a female to male ratio of 1.6:1. Forty percent of the patients were between 60-69 years of age. Hypertension was seen in 82% of patients while left ventricular hypertrophy was documented in 40% of patients. The QTc was prolonged in 38 patients (17 patients in the ICH group and 21 patients in the SAH group). In both groups, males demonstrated QTc prolongation more than females. However, there were no statistically significant gender difference between both groups and within the same group. There was a statistically significant association between SAH and QTc prolongation (p-value<0.001); the ICH group did not demonstrate any significant relationship with QTc prolongation.
CONCLUSION: Prolongation in the QTc interval was "statistically" associated with acute SAH only. No gender difference was noted; whether this observation is clinically significant or not, it needs further analytic studies.

Matched MeSH terms: Electrocardiography
Smartphone electrocardiogram for QT interval monitoring in Coronavirus Disease 2019 (COVID-19) patients treated with Hydroxychloroquine

Andy Ko TY, Chen LS, Pang IX, Ling HS, Wong TC, Sia Tonnii LL, et al.

Med J Malaysia, 2021 03;76(2):125-130.
PMID: 33742617

INTRODUCTION: The global pandemic of Corona Virus Disease 2019 (COVID-19) has led to the re-purposing of medications, such as hydroxychloroquine and lopinavir-ritonavir in the treatment of the earlier phase of COVID-19 before the recognized benefit of steroids and antiviral. We aim to explore the corrected QT (QTc) interval and 'torsadogenic' potential of hydroxychloroquine and lopinavir-ritonavir utilising a combination of smartphone electrocardiogram and 12-lead electrocardiogram monitoring.
MATERIALS AND METHODS: Between 16-April-2020 to 30-April- 2020, patients with suspected or confirmed for COVID-19 indicated for in-patient treatment with hydroxychloroquine with or without lopinavir-ritonavir to the Sarawak General Hospital were monitored with KardiaMobile smartphone electrocardiogram (AliveCor®, Mountain View, CA) or standard 12-lead electrocardiogram. The baseline and serial QTc intervals were monitored till the last dose of medications or until the normalization of the QTc interval.
RESULTS: Thirty patients were treated with hydroxychloroquine, and 20 (66.7%) patients received a combination of hydroxychloroquine and lopinavir-ritonavir therapy. The maximum QTc interval was significantly prolonged compared to baseline (434.6±28.2msec vs. 458.6±47.1msec, p=0.001). The maximum QTc interval (456.1±45.7msec vs. 464.6±45.2msec, p=0.635) and the delta QTc (32.6±38.5msec vs. 26.3±35.8msec, p=0.658) were not significantly different between patients on hydroxychloroquine or a combination of hydroxychloroquine and lopinavir-ritonavir. Five (16.7%) patients had QTc of 500msec or more. Four (13.3%) patients required discontinuation of hydroxychloroquine and 3 (10.0%) patients required discontinuation of lopinavirritonavir due to QTc prolongation. However, no torsade de pointes was observed.
CONCLUSIONS: QTc monitoring using smartphone electrocardiogram was feasible in COVID-19 patients treated with hydroxychloroquine with or without lopinavir-ritonavir. The usage of hydroxychloroquine and lopinavir-ritonavir resulted in QTc prolongation, but no torsade de pointes or arrhythmogenic death was observed.

Matched MeSH terms: Electrocardiography*
Diagnostic value of electrocardiogram in cardiac tamponade

Ang KP, Nordin RB, Lee SCY, Lee CY, Lu HT

Med J Malaysia, 2019 02;74(1):51-56.
PMID: 30846663

INTRODUCTION: We aim to study the diagnostic value of electrocardiogram (ECG) in cardiac tamponade.
METHODS: This study was a single centre, retrospective casecontrol study. We recruited 42 patients diagnosed with cardiac tamponade of various aetiologies confirmed by transthoracic echocardiography and 100 controls between January 2011 and December 2015. The ECG criteria of cardiac tamponade we adopted was as follows: 1) Low QRS voltage in a) the limb leads alone, b) in the precordial leads alone or, c) in all leads, 2) PR segment depression, 3) Electrical alternans, and 4) Sinus tachycardia.
RESULTS: Malignancy was the most common causes of cardiac tamponade, the two groups were of similar proportion of gender and ethnicity. We calculated the sensitivity (SN), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) of each ECG criteria. Among the ECG abnormalities, we noted the SN of 'low voltage in all chest leads' (69%), 'low voltage in all limb leads' (67%) and 'sinus tachycardia' (69%) were higher as compared to 'PR depression' (12%) and 'electrical alternan' (5%). On the other hand, 'low voltage in all chest leads' (98%), 'low voltage in all leads' (99%), 'PR depression' (100%) and 'electrical alternans' (100%) has highest SP.
CONCLUSION: Our study reaffirmed the findings of previous studies that electrocardiography cannot be used as a screening tool for diagnosing cardiac tamponade due to its low sensitivity. However, with clinical correlation, electrocardiography is a valuable adjuvant test to 'rule in' cardiac tamponade because of its high specificity.

Matched MeSH terms: Electrocardiography*
Acute myocarditis mimicking ST-elevation myocardial infarction: A diagnostic challenge for frontline clinicians

Ang KP, Quek ZQ, Lee CY, Lu HT

Med J Malaysia, 2019 12;74(6):561-563.
PMID: 31929492

The clinical presentation of acute myocarditis is highly variable ranging from no symptoms to cardiogenic shock. Despite considerable progress, it remains a challenge for frontline physicians to discriminate between acute myocarditis and myocardial infarction, especially in the early phase. Our case serves as a reminder that acute presentation of myocarditis could resemble ST elevation myocardial infarction potentially misdirecting the therapeutic decision. The clinical presentation, electrocardiographic and laboratory findings of the patient are not specific enough to distinguish acute myocarditis from myocardial infarction. The gold standard tests such coronary angiography and cardiovascular magnetic resonance (CMR) can reliably differentiate the two entities.

Matched MeSH terms: Electrocardiography
Ebstein's anomaly of the tricuspid valve: a report of 10 cases

Anuar M, Singham KT

Med J Malaysia, 1979 Dec;34(2):140-4.
PMID: 548715
Matched MeSH terms: Electrocardiography
Diastolic dysfunction grading, echocardiographic and electrocardiogram findings in 50 patients with apical hypertrophic cardiomyopathy

Aslannif R, Suraya K, Koh HB, Tey YS, Tan KL, Tham CH, et al.

Med J Malaysia, 2019 12;74(6):521-526.
PMID: 31929479

INTRODUCTION: Apical Hypertrophic Cardiomyopathy (Apical HCM) is an uncommon variant of hypertrophic cardiomyopathy, but it is relatively more common in Asian countries. This is a retrospective, non-randomised, single centre study of patients with Apical HCM focusing on their diastolic dysfunction grading, echocardiographic parameters and electrocardiograms (ECG).
METHODS: All Apical HCM patients coming for clinic visits at the Institut Jantung Negara from September 2017 to September 2018 were included. We assessed their echocardiography images, grade their diastolic function and reviewed their ECG on presentation.
RESULTS: Fifty patient were included, 82% (n=41) were males and 18% (n=9) females. The diastolic function grading of 37 (74%) patients were able to be determined using the updated 2016 American Society of Echocardiography (ASE) diastolic guidelines. Fifty percent (n=25) had the typical ace-ofspades shape left ventricle (LV) appearance in diastole and 12% (n=6) had apical pouch. All patients had T inversion in the anterior leads of their ECG, and only 52% (n=26) fulfilled the ECG left ventricular hypertrophy (LVH) criteria. Majority of our patients presented with symptoms of chest pain (52%, n=26) and dyspnoea (42%, n=21).
CONCLUSION: The updated 2016 ASE guideline makes it easier to evaluate LV diastolic function in most patients with Apical HCM. It also helps in elucidating the aetiology of dyspnoea, based on left atrial pressure. Clinicians should have a high index of suspicion for Apical HCM when faced with deep T inversion on ECG, in addition to a thick LV apex with an aceof- spades appearance during diastole.

Matched MeSH terms: Electrocardiography/methods*

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