Considerations for clinical studies for electrocardiographs
2
Conclusion: The automated Selvester scoring system we implemented has high accuracy and comparable to expert manual scoring. We observed that the largest score differences between manual and automated resulted from the classification of rS and Q patterns. The computer algorithm is designed not to detect small initial deflections (∼20 μV), which human readers code as R waves when using a ×4 high-gain display. doi:10.1016/j.jelectrocard.2009.08.017 Detection of periodic variations including T-wave Alternans Eric D. Helfenbein, A. Dean Forbes, James M. Lindauer, Saeed Babaeizadeh, Sophia H. Zhou, (Advanced Algorithm Research Center, Philips Healthcare, Thousand Oaks, CA, USA) Introduction: Metabolically compromised tissue may respond to stimuli in a patterned matter. T-wave alternans (TWA) is one form of a patterned behavior in ECG that may be predictive of SCD. We introduce Microvolt Electrocardiogram (ECG) Amplitude Periodicity (MEAP) to detect TWA by analyzing body-surface ECG. Methods: Microvolt ECG Amplitude Periodicity is a time-domain approach to detect TWA buried in additive noise and modulating interferences. It filters the ECG to remove the noise and baseline wander and then estimates and suppresses the components due to respiration and exercise motion. To determine the presence or absence of TWA, a set of basis functions is generated, which represent the repeating patterns that are to be detected (including alternans). A model then is fit into the observed data by finding a linear combination of the basis functions. The coefficients corresponding to each period are used to compute the pattern power and amplitude for that period. Then, MEAP uses a generalized likelihood ratio test to calculate a measure of signal-to-noise ratio defined as the power in the observations “explained” and power “not explained” by the model. Generalized likelihood ratios computed for the TWA period represent the likelihood that TWA of that period is present. Results: Electrocardiograms were recorded from 50 patients with implantable cardiac defibrillator (ICD) while pedaling a stationary bike following a specific protocol. Each recording was 16 channels, 2000 sps, 140 nV LSB in ±5.5-mV offset-adjustable window, and frequency response of 0 to 500 Hz. Low-current respiratory impedance, electro- magnetic interference (EMI), and bicycle pedal revolutions were also acquired. The study subjects were stable patients and were mostly on β- blockers and amiodarone (which probably suppressed alternans in most patients). Microvolt ECG Amplitude Periodicity detected positive TWA with the peak amplitude of 4 μV on 1 patient. It was also tested on the PhysioNet CinC Challenge 2008 database (n = 100) and achieved sensitivity of 77%, specificity of 99%, PPV of 96%, and NPV of 91%, with only 1 false positive. Conclusion: Microvolt ECG Amplitude Periodicity is a highly specific and noise-tolerant algorithm to detect patterned beat-to-beat variability including TWA. More research is necessary to characterize its sensitivity and to determine if any periodic variation in QRS-T complex other than TWA may be used as a predictor of SCD. doi:10.1016/j.jelectrocard.2009.08.018 Displaying computerized electrocardiogram recordings on smartphones T. Hilbel, a S. Klug, a R.L. Lux, b H.A. Katus, c ( a University of Applied Sciences, Gelsenkirchen, Germany; b University of Utah, Salt Lake City, UT, USA; c University of Heidelberg, Heidelberg, Germany) Introduction: Smartphones combine functions of mobile phones, personal digital assistants, and pocket PCs, and their use for business, communica- tion, and entertainment is growing exponentially. Interestingly, biomedical software applications can be developed easily for smartphone devices that support Windows Mobile or Java. Because smartphones are popular in all age groups, one could posit that they might be useful as a portable health monitor for physiologic parameters and as an electrocardiogram (ECG) imaging device. Advantages of these portable minicomputers are that they are light and compact and support wireless communication and even eye-to- eye video communication. In addition, sensors for vital parameters can easily be connected to such devices, and physiologically monitored parameters could be sent wireless from anywhere in the world to telemedicine health care centers or personalized fitness portals. Methods: To test and judge the suitability of smartphones as an ECG imaging device, an ECG viewer for a smartphone was developed. The program was written for Windows Mobile 6.1 using Microsoft C-Sharp. The graphical user interface was designed to display continuous, digitally recorded 12-lead ECG data and also discrete values of blood pressure and oxygen saturation. All data for display and analysis were stored and retrieved from the smartphone's memory card. The smartphone had a 300-MHz CPU, 64-MB RAM, and a 2.4- inch touch screen with a resolution of 240 ⁎ 320 pixels. Results: With minimal programming effort, a program was developed that displayed ECG tracings and discrete physiologic values (heart rate, blood pressure, or pulse oximetry values) on the smartphone screen. The small smartphone display size limited viewing and monitoring of continuous ECG tracings. Especially for older people, a 2.40-inch touch screen with a resolution of 240 ⁎ 320 pixels may be difficult to see and operate. A 2.4- inch' smartphone display is suitable for 2 ECG channels and a recording time of 1 to 3 seconds. It is not feasible to display a reasonable 12-lead ECG. The scrolling speed is also limited due to limited computation power of its CPU and its graphic chips. Nevertheless, due to their multiple wireless communication capabilities (GSM, Bluetooth, WiFi), the smartphone software is useful for the mobile transmission of physiologic data. Conclusions: Visualization of multichannel ECG recordings requires a high-resolution display and considerable memory, both of which are limited on small, low-power consumption mobile phones, thus limiting their usefulness as 12-lead ECG viewers. They would be suitable for display of 2- channel ECGs and discrete vital parameters and very helpful for the wireless transmission of a variety of physiologic data. We have demonstrated that biomedical programs for smartphones can easily be developed using standardized Windows Mobile programming tools. doi:10.1016/j.jelectrocard.2009.08.019 Considerations for clinical studies for electrocardiographs Charles Ho, Lynn Braddock, Benjamin Eloff, Brian Lewis, Nina Nwaba, Linda Ricci, Estelle Russek-Cohen, Elias Mallis, (U.S. Food and Drug Administration, Rockville, Maryland, USA) Food and Drug Administration (FDA)/center for device and radiological health (CDRH) is charged with the responsibility to evaluate new electrocardiogram (ECG) devices for market clearance. As ECG technology expands into new diagnostic areas, FDA is challenged with evaluating the results of clinical studies that aim to support these new diagnostic claims. Because of the investment of time, effort, and other resources, FDA strongly encourages early collaboration with ECG developers before the initiation of a clinical study. In this article, we aim to describe some key considerations for an ECG developer to consider before planning and conducting clinical testing. These considerations may hopefully provide an efficient, least burdensome path toward market clearance. First and foremost is the context for use of the device and capturing the right patients and the right users of the device. Both the types of cases and the type of user (ie, level of training and experience) will depend on the setting of the study. This will drive expectations concerning performance. In planning a study, there is a need for stating the null and alternative hypotheses, and this is partially driven by contextual description of the hypotheses. We believe that a rigorous mathematical description of the null and alternative hypothesis will completely define the aim that the investigator wants to achieve. Furthermore, these hypotheses will directly impact the sample size and subsequently the length of study. The statistical analysis plan should also consider which statistical methods will be used to assess the hypotheses. Another issue to take into consideration is the prevalence of the disease in the population to be studied. In addition to impacting the availability of patients with the particular disease, the disease prevalence can impact the usefulness of commonly used statistical metrics such as sensitivity and specificity. For diseases with low prevalence in a prospective study, we 611 Poster Session 1 / Journal of Electrocardiology 42 (2009) 607–613
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Transcript of Considerations for clinical studies for electrocardiographs
611Poster Session 1 / Journal of Electrocardiology 42 (2009) 607–613
Conclusion: The automated Selvester scoring system we implemented hashigh accuracy and comparable to expert manual scoring. We observed thatthe largest score differences between manual and automated resulted fromthe classification of rS and Q patterns. The computer algorithm is designednot to detect small initial deflections (∼20 μV), which human readers codeas R waves when using a ×4 high-gain display.
doi:10.1016/j.jelectrocard.2009.08.017
Detection of periodic variations including T-wave AlternansEric D. Helfenbein, A. Dean Forbes, James M. Lindauer, SaeedBabaeizadeh, Sophia H. Zhou, (Advanced Algorithm Research Center,Philips Healthcare, Thousand Oaks, CA, USA)
Introduction: Metabolically compromised tissue may respond to stimuli ina patterned matter. T-wave alternans (TWA) is one form of a patternedbehavior in ECG that may be predictive of SCD. We introduce MicrovoltElectrocardiogram (ECG) Amplitude Periodicity (MEAP) to detect TWA byanalyzing body-surface ECG.Methods: Microvolt ECG Amplitude Periodicity is a time-domain approachto detect TWA buried in additive noise and modulating interferences. Itfilters the ECG to remove the noise and baseline wander and then estimatesand suppresses the components due to respiration and exercise motion. Todetermine the presence or absence of TWA, a set of basis functions isgenerated, which represent the repeating patterns that are to be detected(including alternans). A model then is fit into the observed data by finding alinear combination of the basis functions. The coefficients corresponding toeach period are used to compute the pattern power and amplitude for thatperiod. Then, MEAP uses a generalized likelihood ratio test to calculate ameasure of signal-to-noise ratio defined as the power in the observations“explained” and power “not explained” by the model. Generalizedlikelihood ratios computed for the TWA period represent the likelihoodthat TWA of that period is present.Results: Electrocardiograms were recorded from 50 patients withimplantable cardiac defibrillator (ICD) while pedaling a stationary bikefollowing a specific protocol. Each recording was 16 channels, 2000 sps,140 nV LSB in ±5.5-mV offset-adjustable window, and frequencyresponse of 0 to 500 Hz. Low-current respiratory impedance, electro-magnetic interference (EMI), and bicycle pedal revolutions were alsoacquired. The study subjects were stable patients and were mostly on β-blockers and amiodarone (which probably suppressed alternans in mostpatients). Microvolt ECG Amplitude Periodicity detected positive TWAwith the peak amplitude of 4 μV on 1 patient. It was also tested on thePhysioNet CinC Challenge 2008 database (n = 100) and achievedsensitivity of 77%, specificity of 99%, PPV of 96%, and NPV of 91%,with only 1 false positive.Conclusion: Microvolt ECG Amplitude Periodicity is a highly specific andnoise-tolerant algorithm to detect patterned beat-to-beat variability includingTWA. More research is necessary to characterize its sensitivity and todetermine if any periodic variation in QRS-T complex other than TWA maybe used as a predictor of SCD.
doi:10.1016/j.jelectrocard.2009.08.018
Displaying computerized electrocardiogram recordings on smartphonesT. Hilbel,a S. Klug,a R.L. Lux,b H.A. Katus,c ( aUniversity of AppliedSciences, Gelsenkirchen, Germany; bUniversity of Utah, Salt Lake City,UT, USA; cUniversity of Heidelberg, Heidelberg, Germany)
Introduction: Smartphones combine functions of mobile phones, personaldigital assistants, and pocket PCs, and their use for business, communica-tion, and entertainment is growing exponentially. Interestingly, biomedicalsoftware applications can be developed easily for smartphone devices thatsupport Windows Mobile or Java. Because smartphones are popular in allage groups, one could posit that they might be useful as a portable healthmonitor for physiologic parameters and as an electrocardiogram (ECG)imaging device. Advantages of these portable minicomputers are that they
are light and compact and support wireless communication and even eye-to-eye video communication. In addition, sensors for vital parameters caneasily be connected to such devices, and physiologically monitoredparameters could be sent wireless from anywhere in the world totelemedicine health care centers or personalized fitness portals.
Methods: To test and judge the suitability of smartphones as an ECG imagingdevice, an ECG viewer for a smartphone was developed. The program waswritten forWindowsMobile 6.1 using Microsoft C-Sharp. The graphical userinterface was designed to display continuous, digitally recorded 12-lead ECGdata and also discrete values of blood pressure and oxygen saturation. All datafor display and analysis were stored and retrieved from the smartphone'smemory card. The smartphone had a 300-MHzCPU, 64-MBRAM, and a 2.4-inch touch screen with a resolution of 240 ⁎ 320 pixels.
Results: With minimal programming effort, a program was developed thatdisplayed ECG tracings and discrete physiologic values (heart rate, bloodpressure, or pulse oximetry values) on the smartphone screen. The smallsmartphone display size limited viewing and monitoring of continuous ECGtracings. Especially for older people, a 2.40-inch touch screen with aresolution of 240 ⁎ 320 pixels may be difficult to see and operate. A 2.4-inch' smartphone display is suitable for 2 ECG channels and a recordingtime of 1 to 3 seconds. It is not feasible to display a reasonable 12-lead ECG.The scrolling speed is also limited due to limited computation power of itsCPU and its graphic chips. Nevertheless, due to their multiple wirelesscommunication capabilities (GSM, Bluetooth, WiFi), the smartphonesoftware is useful for the mobile transmission of physiologic data.
Conclusions: Visualization of multichannel ECG recordings requires ahigh-resolution display and considerable memory, both of which are limitedon small, low-power consumption mobile phones, thus limiting theirusefulness as 12-lead ECG viewers. They would be suitable for display of 2-channel ECGs and discrete vital parameters and very helpful for the wirelesstransmission of a variety of physiologic data. We have demonstrated thatbiomedical programs for smartphones can easily be developed usingstandardized Windows Mobile programming tools.
doi:10.1016/j.jelectrocard.2009.08.019
Considerations for clinical studies for electrocardiographsCharles Ho, Lynn Braddock, Benjamin Eloff, Brian Lewis, Nina Nwaba,Linda Ricci, Estelle Russek-Cohen, Elias Mallis, (U.S. Food and DrugAdministration, Rockville, Maryland, USA)
Food and Drug Administration (FDA)/center for device and radiologicalhealth (CDRH) is charged with the responsibility to evaluate newelectrocardiogram (ECG) devices for market clearance. As ECG technologyexpands into new diagnostic areas, FDA is challenged with evaluating theresults of clinical studies that aim to support these new diagnostic claims.Because of the investment of time, effort, and other resources, FDA stronglyencourages early collaboration with ECG developers before the initiation of aclinical study. In this article, we aim to describe some key considerations foran ECG developer to consider before planning and conducting clinicaltesting. These considerations may hopefully provide an efficient, leastburdensome path toward market clearance.First and foremost is the context for use of the device and capturing the rightpatients and the right users of the device. Both the types of cases and the typeof user (ie, level of training and experience) will depend on the setting of thestudy. This will drive expectations concerning performance.In planning a study, there is a need for stating the null and alternativehypotheses, and this is partially driven by contextual description of thehypotheses. We believe that a rigorous mathematical description of the null andalternative hypothesis will completely define the aim that the investigator wantsto achieve. Furthermore, these hypotheses will directly impact the sample sizeand subsequently the length of study. The statistical analysis plan should alsoconsider which statistical methods will be used to assess the hypotheses.Another issue to take into consideration is the prevalence of the disease inthe population to be studied. In addition to impacting the availability ofpatients with the particular disease, the disease prevalence can impact theusefulness of commonly used statistical metrics such as sensitivity andspecificity. For diseases with low prevalence in a prospective study, we
612 Poster Session 1 / Journal of Electrocardiology 42 (2009) 607–613
suggest calculating the positive predictive value and negative predictivevalue, in addition to other useful statistical metrics.We will provide examples to highlight the important differences betweenthe requirements to support a screening claim versus those for adiagnostic claim.
doi:10.1016/j.jelectrocard.2009.08.020
A mobilized 12-lead electrocardiogram information system for clinicalemergency telemedicineJui-chien Hsieh, (Department of Information Management, Yuan ZeUniversity, Taiwan)
Despite the progress of manufacture- and machine-dependent 12-leadelectrocardiogram (ECG) information systems, such as HP SCP-ECG andPhilips XML-ECG, the development of mobilized 12-lead ECG inhospitals is impeded by the heterogeneous ECG file formats andencrypted 12-lead ECG waveform data. Until now, there is no mobilized12-lead ECG information system that can exchange information withclinically used 12-lead ECG for the need of emergency telemedicine. Themajor goals of this study are to develop a mobilized 12-lead ECGsystem, which can provide clinicians with ubiquitously 12-lead ECGdiagnoses in clinical practices and hence to improve the services ofemergency telemedicine. As a first step, an interpreter decodingwaveform data of SCP-ECG and XML-ECG was developed. Second, awaveform-based DICOM-ECG converter converting clinically used SCP-ECG and XML-ECG to DICOM was implemented in PACS for image-and waveform-based DICOM manipulation. Third, to realize remote 12-lead ECG diagnoses, a mobile SQL database communicating with theimage server of PACS by wireless access was used in physicians' PDAphones. The developed mobile 12-lead ECG information system has beenevaluated by technology and operational management in clinicalemergency telemedicine. The results include the following. First, themobile system enabled the integration of image- and waveform-basedmedical data and facilitated 12-lead ECG record interoperability. Second,the use of mobile12-lead ECG information system significantly reducedtreatment time of acute coronary diseases by approximately 20 minutes in20-second clinical case studies of emergency telemedicine. Third,according to 7 senior physicians of emergency and cardiovasculardepartments, the use of this mobile 12-lead ECG system effectivelydecreased medical disputes and strengthened physicians' timely respon-siveness and their sense of responsibility while being away from theirhospitals. In conclusion, this mobile 12-lead ECG information system notonly is time efficient but can also effectively improve the medicaltreatment quality in emergency medicine.
doi:10.1016/j.jelectrocard.2009.08.021
ST-segment depression in aVr as a predictor of culprit artery andinfarct size in acute inferior wall ST-segment elevation myocardialinfarctionYumiko Kanei, Jyoti Sharma, Ravi Diwan, Ron Sklash, Lori L. Vales,John T. Fox, Paul Schweitzer, (Beth Israel Medical Center, New York,NY, USA)
Background: Acute ST-segment elevation myocardial infarction (STEMI)of the inferior wall can be caused by an occlusion of either the right coronaryartery (RCA) or left circumflex (LCx) artery. ST-segment depression in aVrhas recently been suggested as a predictor of left circumflex arteryinvolvement. It was also shown to be associated with impaired myocardialperfusion. The purpose of this study is to evaluate the clinical significanceand anatomic correlation of aVr depression during inferior wall STEMI.
Methods: This study included 121 consecutive patients who presented toour institution with inferior wall STEMI and underwent a subsequentcoronary angiogram. After excluding 6 patients with bundle branch block,115 electrocardiograms were reviewed by 2 readers for ST-segmentdeviation measured at 60 milliseconds after the J point. Patients were
divided into 2 groups based on the presence or absence of aVr depressionmore than 0.1 mV. Clinical and angiographic findings were comparedbetween the 2 groups.Results: The culprit artery was found to be the RCA in 93 patients, LCx in21 patients, and the left anterior descending in 1 patient. ST-segmentdepression in aVr was seen in 28 patients. Clinical characteristics weresimilar in both groups, except that the LCx was a more common culpritartery in the aVr depression group. The sensitivity and specificity of aVrdepression as a predictor of LCx infarction were 62% and 84%, respectively.Cardiac enzymes were significantly higher in the aVr depression group(creatinase kinase (CK)-MB 208 ± 178 ng/mL versus 121 ± 105 ng/mL, P =.0026). This finding was consistent in the RCA culprit artery group (CK-MB233 ± 234 ng/mL versus 115 ± 94 ng/mL, P = .0022), however, not in theLCx culprit artery group (CK-MB 180 ± 111 ng/mL versus 186 ± 172 ng/mL, P = .9232). Furthermore, among patients with RCA as the culprit artery,75% of patients with aVr depression had a large posterolateral branch,whereas 42% of the patients without aVr depression had a small RCA withcodominant or LCx-dominant system.Conclusion: In patients with inferior-wall STEMI, ST-segment depressionin aVr is a useful predictor of LCx as the culprit artery. The finding of aVrdepression with the RCA as the culprit artery is associated with larger infarctsize. This can potentially be explained by the larger size of the RCA branch.ST-segment depression in aVr should be looked upon as a significantelectrocardiographic finding in patients with acute inferior wall STEMI.
doi:10.1016/j.jelectrocard.2009.08.022
Efficacy of low level laser therapy around the stellate ganglion in thetreatment of sick sinus syndromeYuji Kasamaki,a Masakatsu Ohta,a Toshiko Nakai,a Ichiro Watanabe,a
Atsushi Hirayama,a Yukio Ozawa,a Kenichi Yoshida,b Masamai Ichiba,b
Kouji Kagami,c ( aDivision of Cardiology, Department of Medicine, NihonUniversity School of Medicine, Tokyo, Japan; bMochida Siemens MedicalSystem, Tokyo, Japan; cFukuda Denshi, Tokyo, Japan)
Background: Low-level laser therapy (LLLT) has been used to treat variouspathophysiologic disorders. It has recently been reported that a case of sinusarrest caused by mechanical stimulation to the autonomic nervous systemwas improved by LLLT to the stellate ganglion. The aim of the present studywas to evaluate the efficacy of LLLT on the heart rate in patients with sicksinus syndrome (SSS).Methods: The study included 10 patients with SSS. Low-level laser therapyat a wave length of 830 nm and an output of 10W directed to the both stellateganglion were applied. Holter electrocardiogram and signal-averaged P-wave electrocardiograms were recorded before and after LLLT. The rootmean square amplitude for the initial 20milliseconds (EP20) and the durationof initial low-amplitude signals less than 4 μV (ED4) of the filtered P wavewere measured. Filtered P-wave duration was also measured.Results: Low-level laser therapy significantly increased the mean (SD) heartrate from 48 (±5) to 57 (±7) beats/min (P b .01) and shortened maximum RR(SD) interval from 2.8 (±0.6) to 2.2 (±0.4) seconds (P b .01). EP20 wastended to be larger and ED4 was tended to be shorter after LLLT. The heartrate has been maintained after the cessation of the LLLT.Conclusion: Our results suggest that LLLT could be effective at increasingthe heart rate in patients with SSS.
doi:10.1016/j.jelectrocard.2009.08.023
Detection of ST-T abnormalities by portable electrocardiogram monitor-ing devices—comparison with standard 12-lead electrocardiogramYuji Kasamaki,a Masakatsu Ohta,a Toshiko Nakai,a Ichiro Watanabe,a
Atsushi Hirayama,a Yukio Ozawa,a Midori Masuno,b ( aDivision ofCardiology, Department of Medicine, Nihon University School of Medicine,Tokyo, Japan; bOmron Healthcare, Kyoto, Japan)
Background: Compact portable electrocardiogram (ECG) monitors havebeen recently introduced to the public and have been widely used.
