Frequently Asked Questions - Clinician and Researchers

FAQs - Clinician and Researchers

Advanced ECG (A-ECG) comprises an extensive suite of software-based analytical techniques that can be performed on pre-existing resting 12-lead ECG data, including on stored standard (10-sec) and longer (5-minute) resting 12-lead ECG data files. The underlying technologies were developed by several researchers, engineers, cardiologists and statisticians throughout the world, but brought together in one place—NASA’s Johnson Space Center—over the past decade. A-ECG analyses and Reports simultaneously consider and statistically integrate results not only from the conventional 12-lead ECG, but also (most importantly) from advanced ECG analyses that are not directly available on conventional ECG machines. The advanced ECG parameters that can be measured and statistically integrated into A-ECG Reports include those from nearly every resting advanced ECG technique historically proven, within the scientific literature, to have diagnostic or prognostic utility, for example studies of T-Wave and QRS-Wave Complexity (TWC and QRSWC) via singular value decomposition (SVD); beat-to-beat QT interval Variability (QTV) and Heart Rate Variability (HRV); 3-Dimensional (3D) ECG, including spatial and spatiotemporal ECG; and various aspects of Signal Averaged ECG (SAECG). For a general scientific introduction to A-ECG, see this publication (PDF available here) [65] and/or this video.

A-ECG results are integrated and reported in the form of A-ECG "scores", originally constructed by applying population statistical techniques such as multivariate logistic regression and pattern recognition (e.g., multidimensional discriminant analysis) as well as feature selection, bootstrapping and jackknifing, to results from all available advanced and conventional ECG parameters stored within large underlying (pre-existing) ECG databases. These same databases contain, in addition to their ECG and A-ECG information, large amounts of clinical and imaging information both from diseased patients and healthy subjects whose cardiac conditions have been defined by non-ECG-based gold-standard imaging tests. Thus any new patient’s statistically integrated A-ECG results are compared against those in these large pre-existing databases, and the new patient's A-ECG Report (see example A-ECG Reports here) serves to explain and depict his/her results not only according to simple “disease versus no disease” scores (probabilities), but also according to the probability of the presence of any given type of heart disease already characterized ("fingerprinted") by means of earlier patients' results within the pre-existing databases. In addition, for adult patients whose overall probabilities put them closest to or within the "healthy" zone (i.e., whose results are most similar to those of patients already in the database(s) who have known non-diseased hearts), A-ECG can also estimate, from full-disclosure (5-min) 12-lead ECG recordings, the A-ECG “Heart Age” score, contrasting that to the patient's true chronological age. 

For a review of the logistics of how a clinician can use the website (and/or a dedicated securely shared folder) to upload his/her patient's raw ECG data file, and then ultimately receive a detailed A-ECG Report for his/her patient, refer to this graphic.

No specialized equipment is required. A-ECG Reports can be generated after use of almost any manufacturer's conventional ECG machine (or ECG-containing Electronic Health Record system) that is capable of exporting its 12-lead ECGs in a known digital data format. The data that are necessary for the generation of A-ECG Reports are thus collected and stored during one's usual conventional 12-lead ECG data collection procedure. Thus exportation and uploading of the ECG data file(s) to our secure, HIPAA compliant site (or to a shared-folder equivalent, see below) are the only additional steps a clinician or researcher must take to request and obtain an A-ECG Report. Nearly all of the exportable formats of the major ECG machine manufacturers (for example .xml formats, .scp formats, etc.) are supported. For further details on the specific formats that are currently accepted (the list of which is also continually growing), see the lower half of the PRODUCTS AND SERVICES section of the site.

While most ECG machines in doctors' offices and hospitals today are still only capable of performing and storing 12-lead ECGs that are 10 seconds in length, these "snapshot" 12-lead ECGs are nonetheless still sufficient for conducting the most important aspects of A-ECG-related scoring for heart diseases, as long as their digital data format is known. Certain additional analyses that go beyond A-ECG scoring for diseases, for example A-ECG-based Heart Age scoring in "healthy" individuals, on the other hand require higher fidelity 12-lead ECG recordings of longer duration, typically at least 5 minutes in length (aka "full disclosure" ECGs) for accurate performance. But for the majority of clinicians or researchers who request A-ECG Reports, access to a snapshot-only capable 12-lead ECG system will usually suffice. 

For clinicians and researchers who do not currently own, yet desire to own, a hardware platform for both snapshot and full-disclosure conventional 12-lead ECGs that can also enable A-ECG-based Heart Age scoring, we do secondarily offer a relatively inexpensive solution that centers around a state-of-the-art, WiFi (plus USB) enabled computerized 12-lead ECG recorder. This recorder and its accompanying conventional ECG software have been optimized for collecting, displaying and auto-interpreting (in several possible languages) high-fidelity, full-disclosure, conventional 12-lead ECG recordings. Its price is roughly 1/5th of that of the larger manufacturers' machines that typically can only collect and store lower-fidelity snapshot (10-sec) 12-lead ECGs. For pricing information, please inquire by utilizing the CONTACT icon. For further details on the hardware/software system itself, refer to the upper half of our PRODUCTS AND SERVICES section (if not logged in), or, if you are already registered and logged in, refer to your PRICING section.   

When utilizing the above hardware platform, it's also very straightforward to install, if desired, the platform's 12-lead ECG software into a securely shared folder, e.g., into a folder within Dropbox, or, if HIPAA compliance is also required, e.g., in the USA, then into a "Sookasa for Dropbox" folder or equivalent. Such installation can therefore also offer instantaneous secure sharing of newly-collected files with our analytical programs here in Switzerland, leading to reduced A-ECG Report turnaround times. Highly experienced and/or advanced clinical users of A-ECG often tend to prefer this "securely shared folder" method of file sharing, as it leads to optimum efficiency, with simple drag-and-drop procedures on a site like Dropbox (+/- Sookasa) ultimately bypassing any need to use our website for file and Report transfers. 

Quite literally, "Signal Averaging" simply means lining up sequential ECG waveforms (P, QRS and/or T) and averaging them into a single waveform to obtain a result with a better signal-to-noise ratio than that from any single beat or lesser number of beats. Over the years, the term “Signal Averaged ECG" (SAECG) has often unfortunately become synonymous with just one particular older application of signal averaging that applied it to analysis of so-called “late potentials”, which are signals greater than 30 to 40 Hz that may occur toward the end of the QRS wave and the beginning of the ST segment.[13]

Although elucidation of late potentials, when present, still has some potential usefulness (and the full-disclosure A-ECG test can include a variation of late potentials analysis upon request), in general “late potentials analysis” represents a less powerful, older method that in the scientific literature has poorer diagnostic and/or predictive value than many of the newer techniques such as TWC, QRSWC, QTV, HRV, 3D ECG, etc., as described below. A number of these latter techniques also utilize "signal averaging" in the more generic sense of that term.

HFQRS ECG is a technique that takes advantage of high-fidelity, full-disclosure 12-lead ECG recordings to measure high frequency (150-250 Hz) signals within the QRS waves (i.e., during ventricular depolarization), specifically through signal averaging and digital filtering. These signals are not quantified by conventional 12-lead ECG, which typically assesses only low frequencies (< 150 Hz). In the scientific literature, HFQRS has sometimes been shown to be more useful than standard ECG in helping to identify coronary artery disease and cardiomyopathies (see this Mayo Clinic Proceedings review publication [1] for further details). However, in the context of resting 12-lead ECG recordings, the diagnostic utility of parameters of HFQRS is known to be inferior to those of parameters from other advanced ECG techniques such as T-wave complexity, 3D ECG, and beat-to-beat QT and RR interval variability—see Supplemental Table 1 of this publication for further details. Thus at the present time, HFQRS parameters do not play any diagnostic role in A-ECG. 

The morphology, or shape, of the T wave during electrical recovery (repolarization) can be an important indicator of normal versus abnormal heart function, yet standard ECG does not quantify morphology of T waves in any notable detail. Changes in T Wave Morphology (also known as T-wave Complexity, TWC) can be more precisely quantified by applying advanced mathematical techniques such as principal component analysis (PCA) or singular value decomposition (SVD) to the 12-lead ECG. Abnormal PCA- or SVD-derived TWC can be found in many types of heart diseases, for example in hypertrophic cardiomyopathy[2] (the leading cause of sudden death in young athletes in most countries), as well as in other hereditary cardiomyopathies and ion channelopathies such as long QT syndromes.[3] The presence of such abnormalities can also aid in the identification of coronary artery disease and left ventricular systolic dysfunction (LVSD or left-sided systolic heart failure) and in helping to predict the propensity for cardiac events.[4-8] Similar analyses of QRS Wave Complexity (QRSWC) have also been shown to be helpful for identifying LVSD and in predicting adverse cardiac events.[9-11] Methodologically, it's also very important that TWC and QRSWC be assessed by using signal averaging,[12], as occurs within A-ECG, so that a sufficient signal-to-noise ratio is obtained. 

A 3-Dimensional ECG can be constructed from the 12-lead ECG by using a method known as the Frank lead reconstruction.[14,15] During A-ECG analyses, such reconstruction is used along with signal averaging to derive the so-called “spatial QRS-T angle”, which has been shown to have a stronger predictive value for future cardiac events than any conventional cardiovascular “risk factor”, including diabetes and hypertension.[16] The spatial QRS-T angle has also been shown to have a relatively high value for predicting heart disease events and mortality both in the general older population and in women.[9-11],[16-18]  And it's also been shown useful for assessing which patients with heart failure would actually most benefit from receiving (versus not receiving) implantable cardioverter-defibrillator (ICD) devices.[69] ICD devices, although often life saving, commonly lead to substantial decrements in the quality of life for those heart failure patients who receive them, and many such patients suffer from ICD-related complications (infections, breakdowns, false shocks, etc) yet never actually benefit from their device. Based on the scientific literature, when a patient with heart failure due to ischemic heart disease has a spatial QRS-T angle less than approximately 100 degrees, he/she may actually be very unlikely to receive "appropriate shocks" from an ICD, and thus also unlikely to benefit from an ICD.[69]

Finally, the spatial QRS-T angle has also been shown to be very helpful for detecting hypertrophic cardiomyopathy,[66] and in fact for detecting any type of enlargement or hypertrophy of the ventricles, commonly when conventional ECG is simultaneously falsely negative.[65]  From the 3D ECG, one can also obtain parameters such as the spatial ventricular gradient and its variability, potentially helpful for aiding detection of pulmonary hypertension/right ventricular overload[19] and of ischemic heart disease syndromes,[20,21] respectively, plus also dozens of other parameters of potential interest that were historically developed from the conventional vectorcardiogram (VCG).[22]  From full-disclosure 3D ECG, one can also obtain results from some more recently developed and potentially useful “spatiotemporal” 3D ECG parameters.[23,24]

In summary, for each snapshot or full-disclosure 12-lead ECG, A-ECG quantifies several 3D ECG parameters for immediate inclusion within multiple A-ECG scores, as well as hundreds more such parameters for posterity, meaning for potential inclusion in future A-ECG scores that will draw upon the results of further iterative population statistical analyses as the underlying clinical and A-ECG databases continue to grow.

On the conventional ECG, the QT interval is simply the amount of time from the beginning of the QRS wave to the end of the T wave. It thus encompasses the entire duration of the “cardiac action potential”, or the time for both the depolarization and repolarization phases of ventricular electrical activity. Although lengthening of the corrected QT (QTc) interval itself often reinforces the presence of certain types of heart disease (e.g., “long QT syndromes”, cardiomyopathies, coronary artery disease, left ventricular hypertrophy, acute coronary syndromes, etc.), the variability of the QT interval from beat-to-beat is typically even more sensitive than just the QTc interval length itself for detecting these very same conditions.[25-32]

An increase in QTV, especially in relation to HRV (see below), has also been shown to be useful for predicting any propensity for life-threatening ventricular arrhythmias in individuals with known pre-existing heart disease.[33-36] In relation to A-ECG, the results for QTV are only analyzed and incorporated into A-ECG scores and Reports when full-disclosure ECGs have been collected, as at least a few minutes worth of data are required for adequate accuracy and reproducibility of QTV results. The template time-shifting algorithms used for quantifying beat-to-beat QTV within A-ECG [37-39] are arguably the world's most robust, as third parties have determined that methodologically these algorithms are the “best available", i.e., the least affected by noise and other artifacts.[67] These algorithms have been iterated and perfected over decades of work, and specifically take advantage of the multichannel nature of the 12-lead ECG as well as advanced mathematics.   

Simply put, the healthy heart does not beat like a monotonous metronome, but rather more like a well-organized jazz band that is also allowed some improvisational leeway. Thus, during analysis of Heart Rate Variability (HRV), also known as R-wave-to-R-wave interval variability (RRV, i.e., when the exact time-distances in milliseconds between adjacent R-wave peaks are measured rather than less exact changes in heart rate in bpm from beat to beat), more variability is generally a sign of greater health, at least when the heart is in a normal rhythm without premature beats. Note that the opposite is the case for QT Variability, wherein more variability is generally a “bad” sign (unless "driven by" high HRV), and wherein the variability that is present should be mostly accounted for by (or "commensurate with") the underlying HRV. Thus, one good reason to measure HRV (RRV) is that it allows one to properly contextualize QTV, with the combination of RRV and QTV offering more diagnostic and prognostic power in the scientific literature than either of the techniques alone. By itself, HRV (RRV), which like QTV is accurately quantifiable only on full-disclosure (5-min+) ECGs, has also been shown to have some value in predicting events in patients with heart failure [40] and (along with QTV) in A-ECG Heart Age scoring.[68] Full-disclosure A-ECG analyses quantify RRV in multiple different ways, e.g., using both traditional linear techniques (time and frequency domains), and also more recent “non-linear” techniques such as detrended fluctuation analysis that may provide additional diagnostic and/or prognostic utility.[41,42]

Detection of meaningful "microvolt-level T-wave alternans" (TWA) critically depends upon increasing the heart rate above normal (to over 100 beats/min), at least for several minutes, traditionally during exercise stress testing or cardiac pacing. The A-ECG test has been specifically designed for performance at rest, so it does not attempt to measure TWA.

Yes. Almost everyone has premature (ectopic) beats on occasion, including premature atrial, junctional or ventricular complexes. About 95% of the time, isolated ectopic beats do not pose any problem for the generation of A-ECG Reports. Generally, there are no issues if the ectopic beats occurred only occasionally during the ECG data collection because algorithms used within A-ECG automatically detect and eliminate their effect. During A-ECG analyses, the number of premature complexes present in the recording, if any, is also automatically counted. Because during full-disclosure (5-min) 12-lead ECG recordings, a certain number of “normal" QRS-T complexes must have been collected, the QTV and RRV part of such recordings may occasionally be rejected for A-ECG reporting if premature ventricular complexes occurred with some regularity (e.g., >6-7 ventricular ectopic beats/minute). Similarly, if two or more ventricular ectopic complexes occurred during any given short (10-sec "snapshot") 12-lead ECG recording, then those recordings may also occasionally be rejected for A-ECG reporting if an insufficient number of "normal" QRS-T complexes are present for A-ECG-related signal averaging to produce an adequate signal-to-noise ratio.

In general, when ventricular ectopic beats occur with extreme frequency, such as every other beat ("bigeminy"), every third beat (trigeminy) or every fourth beat (quadrigeminy), or, for full disclosure recordings, >6-7 times/minute, we strongly recommend that the patient's 12-lead ECG recording be postponed until a time when fewer ectopic beats are present. This will substantially decrease the risk that we will be forced to reject part or all of the given uploaded ECG file due to an insufficient number or sequence of normal beats. 

For now, no, except by prior special arrangement. (Until further notice, whenever we receive files from patients with such blocks without prior arrangement, a report will not be produced or forwarded, nor will there be any charge to the customer, unless prior special arrangements have been made for the analysis of such files).

Complete left and right bundle branch blocks (LBBBs and RBBBs, respectively) are electrical conduction delays that may invalidate the results of several types of A-ECG analyses (e.g., aspects of QRSWC, 3D ECG and SAECG). However results of other A-ECG analyses, especially from the full-disclosure A-ECG (e.g., QTV, HRV, TWC, some aspects of 3D ECG) may still remain valid for such patients and, within certain limitations, be useful for helping to address certain circumscribed questions only.  

For example, by prior arrangement, we now produce specialized A-ECG reports that can help clinicians subjectively quantify the probability that any given patient whose ECG shows "LBBB-type morphology" will have a "good" versus "bad" response to future cardiac resynchronization therapy (CRT), through quantification of parameters such as "QRS area" and "T area".  In addition, such reports can also subjectively quantify the relative risk of future ventricular arrhythmic events based on results from certain 3D ECG, QTV, RRV and other A-ECG techniques.

Although we are currently building additional LBBB- and RBBB-related A-ECG reference databases, until that process is completed, we do not recommend that "nominal" (non-specialized) types of A-ECG Reports be produced for the 12-lead recordings of patients with bundle branch blocks, nor for patients with other types of intraventicular conduction delays (QRS interval >120 ms).  Only the specialized types of reports should be requested for such patients. 

12-lead ECG data from patients who were acutely "tachycardic" (i.e., had heart rates >100 beats/min) at the time of data collection should not be uploaded to our site. We will usually reject such files because tachycardia can have artifactual effects on the results of a number of A-ECG parameters.

12-lead ECG data from patients who were in other abnormal (non-tachycardic) atrial rhythms (e.g., chronic or paroxysmal atrial fibrillation or flutter or other supraventricular arrhythmia) are acceptable, and will be processed for A-ECG reporting if uploaded and sent, as long as those patients' ventricular response rates were less than 100 beats/minute at the time of the recording. (A general rule is that regardless of the atrial rhythm, the heart rate or ventricular response rate should have been <100 beats per minute at the time of recording for an A-ECG Report to be considered methodologically valid). 

A-ECG Reports will not be generated for patients who had an active artificial pacemaker maintaining their heart's rhythm during their 12-lead ECG recording(s). This is because nearly all A-ECG analyses are invalidated by fully artificially paced rhythms or electrical spikes. For similar reasons, A-ECG Reports will also not be generated for patients who were experiencing a sustained ventricular arrhythmia at the time of their 12-lead ECG recording. Thus these types of files should not be uploaded nor sent.

12-lead ECG data from patients who have a pacemaker device, but who were not experiencing any active artificial pacing at the time of their recording, and who had a normal sinus rhythm (or other allowable atrial rhythm per the above), are acceptable, and will be processed for A-ECG reporting if uploaded/sent.  

Yes, although for any individual who legally is a minor, we'll only produce an A-ECG Report when it is clear that appropriate steps have first been taken with respect to informed consent, parental permission, and assent, as generally outlined here: http://www.cirp.org/library/ethics/AAP/

Note too that our underlying clinical and A-ECG database for pediatric patients is currently much smaller than it is for adult patients (i.e., several hundreds of pediatric patients as compared to several thousands of adult patients). Thus 12-lead ECG recordings from children should only be uploaded by clinical professionals who are legally as well as parentally approved to study, rule out, or serially follow certain pediatric heart conditions, and who are also fully cognizant of the currently greater limitations and potential pitfalls of A-ECG results when applied to pediatric-aged individuals. With respect to the "screening" by A-ECG of more general populations of children or young adults, for example for potentially life-threatening heritable heart conditions like hypertrophic cardiomyopathy or long QT syndromes, we would suggest that general population A-ECG screening generally not be requested for pre-pubescent children. This relates not only to our relatively limited current underlying database for pediatric A-ECGs, but also to the fast heart rates often occurring in infants, toddlers and younger children (if >100 beats/min, the files are unacceptable for A-ECG anyway) as well as the rapid electrical changes that occur in a normal child's cardiac development that tend to make estimates of "normal" more difficult, absent very large amounts of "normal" data from pediatric control subjects for each given year of childhood. 

Currently (2017), the scientific literature suggests that A-ECG analyses might potentially improve the standard ECG-based detection of occult coronary artery disease, left ventricular hypertrophy or enlargement (better referred to as "left ventricular electrical remodeling" when detected by A-ECG or conventional ECG), ischemic, non-ischemic and hypertrophic cardiomyopathies, and ion channelopathies. (For further details, see the Publications section under ABOUT, the REFERENCES section below, and some of the EXAMPLE A-ECG REPORTS, for example for patients "Aida Maines", "Tavis Reddy" and "Kent C. Long").

 Heart Age Scoring[70] by full-disclosure A-ECG may also potentially facilitate patient motivation to better follow through on important modifications to lifestyle, when indicated (see for example the A-ECG Report for patient "Will B. Young" in the EXAMPLE A-ECG REPORTS section).

Recent literature also suggests that A-ECG analyses, including on snapshot 12-lead ECGs, might also be employed to serially follow patients with heart failure (i.e., to potentially less expensively or more conveniently help gauge the effectiveness of medical therapy) [71]. For an example of the utility of serial A-ECG results in helping to monitor the success of heart failure therapy, see the example "Serial A-ECG Results Report" in the EXAMPLE A-ECG REPORTS section.  

A-ECG analyses may also add information (via the results of the spatial QRS-T angle, QTV, RRV and other parameters) on the relative risk of future ventricular arrhythmic events in patients with ischemic (and possibly other) cardiomyopathies, thereby potentially providing ancillary information that may be useful to clinicians who are in the midst of making difficult ICD-related placement decisions. It may also assist clinicians in making CRT-related placement decisions in patients who have LBBB-type morphologies on their conventional ECG. 

Except by prior specific arrangement, "nominal" A-ECG Reports should not be requested for patients with complete bundle branch blocks (QRS>>120 ms), known pre-excitation, active pacing, active ventricular arrhythmias (>6-7 PVCs/min) or tachycardias (heart rate or ventricular response rate >>100 beats/min). A-ECG is also not presently designed to estimate the likelihood of future atrial arrhythmic events, e.g., of future atrial fibrillation, although along with our bundle branch block-related research and ongoing research to better detect right (in addition to left) ventricular electrical remodeling by A-ECG compared to strictly conventional ECG, this too is an active area of exploration, so consider checking back for updates. 

Currently no. However in the future we will try to make A-ECG Reports available in other languages as our time and resources allow, especially as driven by our customer base. 

Our strong preference is in fact to first briefly converse with each health care provider, researcher or other professional who is considering requesting A-ECG Reports. This can be done by telephone, Skype (if you're located in a country other than Switzerland) or equivalent, or less ideally by email. There is no charge for this initial interaction, as long as it's kept reasonably brief (<10-15 min). To schedule it, you can directly email Dr. Schlegel at:  TTSchlegel@gmail.com.  Alternatively, first create an account, then within your new account, in the "MY PROFILE" section, check the box for "Request initial (one-time) informational briefing" while also specifying your professional position, location, email address, telephone number and/or Skype address (if outside of Switzerland) where you'd like to be contacted, as well as the best days of the week and best times to reach you. The company or Dr. Schlegel will then contact you, most likely by email first, within the next few working days. When suggesting possible times, please also keep in mind that we ourselves are located in Switzerland and thus on Central European Time.  

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70. Ball, R.L., Feiveson, A.H., Schlegel, T.T., Starc, V. and Dabney A.R.  Predicting “Heart Age” using Electrocardiography. J. Pers. Med. 2014, 4(1), 65-78.   Full text: http://www.mdpi.com/2075-4426/4/1/65  (doi:10.3390/jpm4010065 )

71. Gladding PA,  Cave A,  Zareian M,  Smith K,  Hussan J, Hunter P, Erogbogbo F, Aguilar Z, Martin DS, Chan E,  Homer ML,  Shevade AV,  Kassemi M,  Thomas JD, Schlegel TT. Open Access Integrated Therapeutic and Diagnostic Platforms for Personalized Cardiovascular Medicine. Journal of Personalized Medicine 2013; 3:203-237. Full Text: http://www.mdpi.com/2075-4426/3/3/203  (see sections on Advanced Electrocardiography, pages 209-212, with Figure 4, and also pages 223-226, with Figures 10-11).