Journal of electrocardiology
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Over the past few years, reducing the number of false positive cardiac monitor alarms (FA) in the intensive care unit (ICU) has become an issue of the utmost importance. In our work, we developed a robust methodology that, without the need for additional non-ECG waveforms, suppresses false positive ventricular tachycardia (VT) alarms without resulting in false negative alarms. Our approach is based on features extracted from the ECG signal 20 seconds prior to a triggered alarm. ⋯ These representations are presented to a L1-regularized logistic regression classifier. Results are shown in two datasets of physiological waveforms with manually assessed cardiac monitor alarms: the MIMIC II dataset, where we achieved a false alarm (FA) suppression of 21% with zero true alarm (TA) suppression; and a dataset compiled by UCSF and General Electric, where a 36% FA suppression was achieved with a zero TA suppression. The methodology described in this work could be implemented to reduce the number of false monitor alarms in other arrhythmias.
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Analyzing cardiac rhythm in the presence of chest compression artifact for automated shock advisory.
Defibrillation is often required to terminate a ventricular fibrillation or fast ventricular tachycardia rhythm and resume a perfusing rhythm in sudden cardiac arrest patients. Automated external defibrillators rely on automatic ECG analysis algorithms to detect the presence of shockable rhythms before advising the rescuer to deliver a shock. For a reliable rhythm analysis, chest compression must be interrupted to prevent corruption of the ECG waveform due to the artifact induced by the mechanical activity of compressions. ⋯ Using this method only a small percentage of cases need compressions interruption, hence a significant reduction in hands-off time is achieved. Our algorithm comprises a novel filtering technique for the ECG and thoracic impedance waveforms, and an innovative method to combine analysis from both filtered and unfiltered data. Requiring compression interruption for only 14% of cases, our algorithm achieved a sensitivity of 92% and specificity of 99%.
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Left ventricular hypertrophy (LVH) induces changes in the depolarization and repolarization of the heart that alter the resting electrocardiogram (ECG). These changes include widening of the QRS duration, an increase in the QRS amplitude and secondary changes in the ST segment and T waves. Typically, there is ST segment depression and T wave inversion (or biphasic T waves) in the lateral leads and ST segment elevation (STE) in the precordial leads V1-V3. ⋯ These changes may vary over time and may not necessarily reflect acute ischemia. The ST-T changes secondary to LVH interfere with ECG interpretation and may affect our accuracy in diagnosing STEMI and other forms of active ischemia. The current guidelines specify thresholds for STE in patients without LVH for whom acute reperfusion therapy is indicated; however, there are no such thresholds for patients with LVH.
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Takotsubo cardiomyopathy (TC) is a recently recognized novel cardiac syndrome characterized by transient left ventricular dysfunction without obstructive coronary disease, electrocardiographic (ECG) changes (ST-segment elevation and/or negative T wave) or elevated cardiac enzymes. Because the clinical features and ECG findings of TC mimic those of anterior acute myocardial infarction (AMI) with occlusion of the left anterior descending coronary artery, differential diagnosis has an important role in selecting the most appropriate treatment strategy. ⋯ Although it has been suggested that ECG does not allow reliable differentiation between TC and anterior AMI, several ECG criteria distinguishing TC from anterior AMI have been proposed. In this review, we discuss ECG findings of TC, especially in the acute phase, compare them with those of anterior AMI, and identify ECG features that may facilitate early recognition of this disease.
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Cornell product criteria, Sokolow-Lyon voltage criteria and electrocardiographic (ECG) strain (secondary ST-T abnormalities) are markers for left ventricular hypertrophy (LVH) and adverse prognosis in population studies. However, the relationship of regression of ECG LVH and strain during antihypertensive therapy to cardiovascular (CV) risk was unclear before the Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) study. We reviewed findings on ECG LVH regression and strain over time in 9193 hypertensive patients with ECG LVH at baseline enrolled in the LIFE study. ⋯ After controlling for treatment with losartan or atenolol, for baseline Framingham risk score, Cornell product, and Sokolow-Lyon voltage, and for baseline and in-treatment systolic and diastolic blood pressure, 1 standard deviation (SD) lower in-treatment Cornell product was associated with a 14.5% decrease in the composite endpoint (HR. 0.86, 95% CI [0.82-0.90]). In a parallel analysis, 1 SD lower in-treatment Sokolow-Lyon voltage was associated with a 16.6% decrease in the composite endpoint (HR. 0.83, 95% CI [0.78-0.88]). The LIFE study shows that evaluation of both baseline and in-study ECG LVH defined by Cornell product criteria, Sokolow-Lyon voltage criteria or ECG strain improves prediction of CV events and that regression of ECG LVH during antihypertensive treatment is associated with better outcome, independent of blood pressure reduction.