The study ECGs were recorded with MAC PC ECG machines (Marquette Electronics, Milwaukee, Wis) in all clinical centers. ECGs were initially processed in a central laboratory at the EPI-CORE Center (University of Alberta, Edmonton, Alberta, Canada) and during later phases of the study at the EPICARE Center (Wake Forest University, Winston-Salem, NC). All ECGs were visually inspected for technical errors and inadequate quality. Initial ECG processing was done by the Dalhousie ECG program, and processing was later repeated with the 2001 version of the GE Marquette 12-SL program (GE Marquette, Milwaukee, Wis). ARIC participants were scheduled to have 4 ECG recordings that were performed during the baseline and the every-3-year study examination. The baseline ECG recordings were used to create the AF predictors, whereas the follow-up ECG recordings were used to measure AF incidence. The ECG variables that we used as AF predictors included P-wave terminal force, P-wave duration, P-wave area, and PR duration, all measured automatically. Because of the automatic measurement, the repeatability of all ECG measures was 100%. P-wave terminal force was defined as the duration in seconds of the terminal part (negative) of the P wave in lead V1 multiplied by its depth in microvolts. P-wave duration (maximum, mean, and in lead II) was measured in milliseconds as the first “onset” and last “offset” deflection from the baseline. P-wave area (maximum and mean) was measured in microvolt · milliseconds2 as the area under the P wave in the 12 leads of the ECG. PR duration was measured in milliseconds as the mean P-wave duration plus the mean PR-segment duration in the 12-lead ECG. The ECG recordings that were automatically coded as AF were visually rechecked by a trained cardiologist to confirm diagnosis. The visually confirmed AF cases in any of the 3 follow-up visits were the ones used in our analysis.
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Electrocardiograph
Electrocardiograph
Electrocardiograph: An instrument that records the electrical activity of the heart.
It is commonly used to help diagnose heart conditions and monitor cardiac health.
The electrocardiograph measures the electrical impulses generated by the polarization and depolarization of the heart muscle, producing a characteristic waveform.
This device has become an essential tool in modern cardiology, providing clinicians with valuable insights into the functioning of the cardiovascular system.
With its ability to detect abnormalities, the electrocardiograph plays a crucial role in the early identification and management of various heart disorders, empowering healthcare professionals to make informed decisions and deliver effective treatments.
Reserchers can leveraege the power of this technology to advance the field of cardiology and improve patient outcomes.
It is commonly used to help diagnose heart conditions and monitor cardiac health.
The electrocardiograph measures the electrical impulses generated by the polarization and depolarization of the heart muscle, producing a characteristic waveform.
This device has become an essential tool in modern cardiology, providing clinicians with valuable insights into the functioning of the cardiovascular system.
With its ability to detect abnormalities, the electrocardiograph plays a crucial role in the early identification and management of various heart disorders, empowering healthcare professionals to make informed decisions and deliver effective treatments.
Reserchers can leveraege the power of this technology to advance the field of cardiology and improve patient outcomes.
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Most recents protocols related to «Electrocardiograph»
The standard body surface 12-lead electrocardiogram of the selected patients was collected at admission. Three models of twelve-lead electrocardiograph were used for ECG acquisition: Fukuda FX7402, Fukuda FX8322 (Fukuda Corporation, Tokyo, Japan), and GE MAC1200ST (GE Medical Systems Information Technologies, the United States). The participant was required to rest quietly for 5 min in a supine position. Then a standard 12-lead ECG was collected for 10 s at a paper speed of 25 mm/s and a voltage of 1 mV for every 10 mm amplitude. Among the ECG parameters, heart rate, PR interval, P wave duration, QRS complex duration, QT interval, and corrected QT interval were automatically measured by the electrocardiographs. For those who did not report the above data due to the acquisition mode, we used the distance tool of Foxit PDF Reader software to manually measure the required data on lead II in the pdf format of the ECG image.
Taking into account the thickness of the ECG waveform line, the distance of segments was measured from the left edge of the starting point to the left edge of the endpoint. The measurement of each segment was performed independently by two qualified cardiologists (YY and XZ) who were blinded to the patients' clinical status and prognosis. If the interpretation result was uncertain, it would be decided after a discussion with senior cardiologists. The manually measured QT interval was corrected by heart rate according to the Bazett’s formula [22 ]. Interobserver agreement was assessed by comparing the P wave duration measurements of the two observers (YY and XZ) in 50 randomly selected patients. Intraobserver agreement was calculated by repeated measurements in 50 patients by the two observers 1 month after the initial measurement.
Among the research variables, the PR interval was defined as the duration from the time the P wave leaves the baseline to the time the next QRS complex leaves the baseline. The duration of the P wave was defined as the time from the start to the end of the P wave. The PR segment was defined as the time from the end of the P wave to the time the first QRS complex leaves the baseline, which can be calculated from the time difference between the PR interval and the P wave duration.
Taking into account the thickness of the ECG waveform line, the distance of segments was measured from the left edge of the starting point to the left edge of the endpoint. The measurement of each segment was performed independently by two qualified cardiologists (YY and XZ) who were blinded to the patients' clinical status and prognosis. If the interpretation result was uncertain, it would be decided after a discussion with senior cardiologists. The manually measured QT interval was corrected by heart rate according to the Bazett’s formula [22 ]. Interobserver agreement was assessed by comparing the P wave duration measurements of the two observers (YY and XZ) in 50 randomly selected patients. Intraobserver agreement was calculated by repeated measurements in 50 patients by the two observers 1 month after the initial measurement.
Among the research variables, the PR interval was defined as the duration from the time the P wave leaves the baseline to the time the next QRS complex leaves the baseline. The duration of the P wave was defined as the time from the start to the end of the P wave. The PR segment was defined as the time from the end of the P wave to the time the first QRS complex leaves the baseline, which can be calculated from the time difference between the PR interval and the P wave duration.
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The procedures and methods of this study will be made available for replication upon reasonable request directed to the corresponding author. The Institutional Review Board of Universidade Federal de Minas Gerais approved the study under CAAE number 37228120.9.0000.5149.
This is a comparative observational study with prospective data collection. The sample consisted of two arms and one parallel registry, and clinical and electrocardiographic outcomes were assessed remotely. The project was funded by the Brazilian Ministry of Health and conducted by the Telehealth Center of Hospital das Clínicas, Universidade Federal de Minas Gerais (Belo Horizonte, MG, Brazil). Remote data collection occurred in health units connected to the Teleassistance Network of Minas Gerais (Rede de Teleassistência de Minas Gerais–RTMG), and the tele-electrocardiography (ECG) system for COVID-19, in all Brazilian regions.
During the COVID-19 pandemic, RTMG adapted its mobile ECG application to provide clinical decision support for COVID-19 cases in health units, especially in primary care, with demographic and clinical data collection, and ECGs for remote interpretation. It was recommended by health authorities that an ECG be obtained before and following the initiation of drugs for COVID-19. ECGs were captured by commercial equipment linked to specific proprietary software, which allows for getting the ECG signal and clinical data, and transmitted by internet to a central server at the Telehealth Center. The requesting healthcare provider collected baseline history, demographic and clinical data. ECGs were centrally analyzed by a team of experienced cardiologists, utilizing specific semi-automated software with measurement and magnification tools, with visual inspection and subsequent classification by the Minnesota code. Minnesota is the most widely used ECG classification system in the world, developed in the 1950s by Dr. Henry Blackburn, which utilizes a defined set of measurement rules to assign specific numerical codes according to the severity of findings (16 (link), 17 (link)). In the presence of a discrepancy between automated reports and the cardiologist’s interpretation, exams were audited by the study team, composed of three previously trained investigators. All ECGs of patients with suspected COVID-19 in the study period were eligible for this analysis and stored in a specific database.
This is a comparative observational study with prospective data collection. The sample consisted of two arms and one parallel registry, and clinical and electrocardiographic outcomes were assessed remotely. The project was funded by the Brazilian Ministry of Health and conducted by the Telehealth Center of Hospital das Clínicas, Universidade Federal de Minas Gerais (Belo Horizonte, MG, Brazil). Remote data collection occurred in health units connected to the Teleassistance Network of Minas Gerais (Rede de Teleassistência de Minas Gerais–RTMG), and the tele-electrocardiography (ECG) system for COVID-19, in all Brazilian regions.
During the COVID-19 pandemic, RTMG adapted its mobile ECG application to provide clinical decision support for COVID-19 cases in health units, especially in primary care, with demographic and clinical data collection, and ECGs for remote interpretation. It was recommended by health authorities that an ECG be obtained before and following the initiation of drugs for COVID-19. ECGs were captured by commercial equipment linked to specific proprietary software, which allows for getting the ECG signal and clinical data, and transmitted by internet to a central server at the Telehealth Center. The requesting healthcare provider collected baseline history, demographic and clinical data. ECGs were centrally analyzed by a team of experienced cardiologists, utilizing specific semi-automated software with measurement and magnification tools, with visual inspection and subsequent classification by the Minnesota code. Minnesota is the most widely used ECG classification system in the world, developed in the 1950s by Dr. Henry Blackburn, which utilizes a defined set of measurement rules to assign specific numerical codes according to the severity of findings (16 (link), 17 (link)). In the presence of a discrepancy between automated reports and the cardiologist’s interpretation, exams were audited by the study team, composed of three previously trained investigators. All ECGs of patients with suspected COVID-19 in the study period were eligible for this analysis and stored in a specific database.
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Twelve-lead standard ECGs were recorded on admission with a CARDIOLINE® HD+ ECG machine. The ECGs were retrieved by our dedicated institutional ECG storage server and independently analyzed by two cardiologists (FS, FM). The ECGs were analyzed before proceeding with an assessment of clinical outcome, which was therefore unknown to the ECG readers.
Cardiologists
Electrocardiogram
Electrocardiograph
Top products related to «Electrocardiograph»
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The MAC 1200 electrocardiograph is a diagnostic device designed to record and display the electrical activity of the heart. It is capable of capturing standard 12-lead electrocardiograms (ECGs) and providing accurate measurements of various cardiac parameters.
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The MAC 5500 is a 12-lead electrocardiograph (ECG) device manufactured by GE Healthcare. It is designed to acquire, display, and store high-quality electrocardiograms. The device features an intuitive user interface and advanced signal processing capabilities to provide reliable cardiac data for clinical evaluation.
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MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
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The GE Marquette 12-SL program is a diagnostic tool used for electrocardiogram (ECG) analysis. It provides automated interpretation and measurements of the electrical activity of the heart, which can be used to assess heart health and identify potential issues.
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LabChart Pro is a data acquisition and analysis software designed for scientific research and experimentation. It allows users to record, view, and analyze a wide range of physiological and experimental data from various instruments and sensors. LabChart Pro provides a user-friendly interface and a range of tools for data management, processing, and visualization.
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PowerLab is a data acquisition system designed for recording and analyzing physiological signals. It provides a platform for connecting various sensors and transducers to a computer, allowing researchers and clinicians to capture and analyze biological data.
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Fastrak is a motion tracking system developed by Polhemus. It is designed to precisely measure the position and orientation of multiple objects in 3D space. The Fastrak system utilizes magnetic tracking technology to capture real-time data on the movement and position of its sensors.
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LabChart 7 is a data acquisition and analysis software designed for recording, visualizing, and analyzing physiological signals. It provides a user-friendly interface for capturing data from various types of laboratory equipment and sensors. LabChart 7 offers tools for real-time display, analysis, and offline processing of the acquired data.
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GE CardioSoft V6.71 is a comprehensive software solution for cardiac diagnostic testing. It provides tools for electrocardiogram (ECG) data acquisition, analysis, and reporting. The software supports various cardiac diagnostic modalities, including resting ECG, stress testing, and Holter monitoring.
More about "Electrocardiograph"
Electrocardiogram (ECG/EKG), heart monitor, cardiac monitor, cardiac tracing, cardiac activity recording, heart health assessment, cardiovascular diagnostics, cardiac electrophysiology, heart rhythm analysis, myocardial activity, depolarization and repolarization, MAC 1200 electrocardiograph, MAC 5500, MATLAB, LabChart 8, GE Marquette 12-SL program, LabChart Pro, PowerLab, Fastrak, LabChart 7, GE CardioSoft V6.71.
Electrocardiographs are essential medical devices used to measure and record the electrical impulses generated by the heart's muscle activity.
These instruments provide clinicians with valuable insights into the function of the cardiovascular system, enabling the early detection and management of various heart conditions.
By analyzing the characteristic waveforms produced by the electrocardiograph, healthcare professionals can identify arrhythmias, myocardial infarctions, and other cardiac abnormalities, empowering them to make informed decisions and deliver effective treatments.
Researchers leveraging the power of electrocardiograph technology can advance the field of cardiology and improve patient outcomes through enhanced reproducibility and accuracy in their studies.
Electrocardiographs have become an indespensible tool in modern medicine, playing a crucial role in the diagnosis and monitoring of heart health.
Electrocardiographs are essential medical devices used to measure and record the electrical impulses generated by the heart's muscle activity.
These instruments provide clinicians with valuable insights into the function of the cardiovascular system, enabling the early detection and management of various heart conditions.
By analyzing the characteristic waveforms produced by the electrocardiograph, healthcare professionals can identify arrhythmias, myocardial infarctions, and other cardiac abnormalities, empowering them to make informed decisions and deliver effective treatments.
Researchers leveraging the power of electrocardiograph technology can advance the field of cardiology and improve patient outcomes through enhanced reproducibility and accuracy in their studies.
Electrocardiographs have become an indespensible tool in modern medicine, playing a crucial role in the diagnosis and monitoring of heart health.