Patient Driven EKG Device Performance in Adults with Fontan Palliation

Patient Driven EKG Device Performance in Adults with Fontan Palliation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Patient Driven EKG Device Performance in Adults with Fontan Palliation Matthew Laubham, Anudeep K Dodeja, Rohan Kumthekar, Victoria Shay, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4254187/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Aug, 2024 Read the published version in Pediatric Cardiology → Version 1 posted 8 You are reading this latest preprint version Abstract Objectives The aim of this study was to evaluate the accuracy of the KardiaMobile (KM) device in adults with a Fontan palliation, and to assess the KM function as a screening tool for atrial arrhythmias. Background While patient driven electrocardiogram (EKG) devices are becoming a validated way to evaluate cardiac arrhythmias, their role for patients with congenital heart disease is less clear. Patients with single ventricle Fontan palliation have a high prevalence of atrial arrhythmias and represent a unique cohort that could benefit from early detection of atrial arrhythmias. Methods This single center prospective study enrolled adult patients with Fontan palliation to use the KM heart rhythm monitoring device for both symptomatic episodes and asymptomatic weekly screening over a 1-year period. Accuracy was assessed by comparing the automatic KM to physician overread and traditional EKG. Results Fifty patients were enrolled and 510 follow up transmissions were received. The sensitivity and specificity of enrollment KM-auto compared to EKG was 65% and 100%, respectively. The sensitivity and specificity of enrollment automated KM interpretations (KM-auto) compared to the electrophysiologist interpretation (KM-EP) was 75% and 96%, respectively. Conclusion In the adult Fontan palliation, the accuracy of the KM device to detect a normal rhythm was reliable and best with a physician overread. Abnormal or uninterpretable KM device interpretations, symptomatic transmissions, and any transmissions with a high heart rate compared to a patient’s normal baseline should warrant further review. Fontan Arrhythmia Adult Congenital Heart Disease Artificial Intelligence Diagnostics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Smart devices are becoming a mainstream and validated means to monitor heart rate, sleep hygiene and blood pressure, track lifestyle behavior and fitness, and surveil for cardiac arrhythmias [1–3] . Most direct-to-consumer devices have shown well established accuracy of discriminating between sinus rhythm and atrial fibrillation (AF) and have been used for AF screening, symptomatic paroxysmal or intermittent AF diagnosis, and post-ablative and post-cardioversion AF management [4–8] . Patient driven electrocardiogram (EKG) devices have also been shown to be a valuable cost-effective tool in evaluating palpitations [9–12] . However, their effectiveness for detecting non-AF arrhythmias, is unclear [13–16] . Beyond AF detection and management of palpitations, there is little data regarding the utility of smart devices within the growing congenital heart disease (CHD) patient population [17] . Patients with Fontan palliation have a higher risk of atrial tachyarrhythmias with an estimated arrhythmia prevalence of 20–44% [18–20] . Importantly, those who develop arrhythmias have a higher morbidity and mortality risk, with atrial arrhythmias being both a cause and consequence of Fontan failure [18, 20, 21] . The adult Fontan population represents a unique CHD cohort that could greatly benefit from early detection of atrial arrhythmias. Current guidelines recommend annual ambulatory monitoring, typically with a traditional Holter monitor [22] . However, standard 24–48 hour monitoring can often miss paroxysmal tachyarrhythmias. Longer term implantable monitoring may increase the chance of detecting infrequent arrhythmias, albeit more invasive and with increased cost. The KardiaMobile® (KM) device (AliveCor, Mountain View, CA), is a commercially available portable heart monitor, consisting of a single bipolar lead with a corresponding smart device application. This device generates a 30-second EKG resembling lead I and can monitor heart rate and rhythm in real time using algorithms generated from EKG data. The KM device received FDA clearance for detecting atrial fibrillation and sinus rhythm. The objective of this prospective study was to examine the accuracy and utility of the KM device’s interpretations in a cohort of adults with Fontan palliation. We hypothesize that the KM device could be used to accurately detect infrequent arrhythmias in symptomatic patients with Fontan palliation and help bridge the gap between more typical routine short-term ambulatory monitoring and more costly long term implantable monitors. Methods This single center prospective study enrolled adult patients with Fontan palliation to use the KM heart rhythm monitoring device for both symptomatic episodes and asymptomatic weekly screening over a 1-year period. This study was approved by institutional IRB. Adult congenital heart disease (ACHD) clinic schedules were reviewed to identify patients who fit inclusion criteria, which consisted of patients ≥ 18 years of age at the time of enrollment with a history of Fontan palliation. Patients were recruited and consented for the study during their outpatient clinic appointment. Enrollment was from 2019 to 2021, with an institutional mandatory enrollment pause during 2020 due to the COVID-19 pandemic. Exclusion criteria consisted of patients with developmental delay or inability to properly use the KM device, patients without a smartphone, and patients without email access to send necessary study transmissions. Study team personnel set up the smartphone application and taught the enrollee how to use the app and KM device. A baseline 12-lead EKG and KM recording were obtained during the enrollment clinic visit. For enrollment analysis, the 12 lead EKG was considered the gold standard rhythm diagnostic modality for comparison. Clinically relevant arrhythmias were defined as any sustained or non-sustained supraventricular tachycardia (SVT) or wide complex tachycardia. Over the outlined 1-year follow up period, patients were instructed to submit weekly asymptomatic recordings that were prompted by weekly email reminders, as well as a KM recording of any symptomatic episodes. Transmitted recordings were submitted to a designated study email, reviewed by the study team and forwarded to the clinical team. Transmitted KM recordings were sent via institutional password protected emails and stored on a password protected network. Demographic information was obtained by review of electronic health record, and included age, clinical information, symptom history, previous Holter monitoring, previous 12 lead EKG results, electrophysiology studies, and cardiac imaging (echocardiography, MRI, CT). Patients were also categorized based on their ACHD anatomic and physiologic classification [22] . Study data was managed using a REDCap electronic database [23, 24] . EKG and KM Interpretations : To determine the accuracy of the automatic KM device readings (KM-auto), the KM-auto reading was compared to both an enrollment 12 lead EKG and interpretation of the KM device recording by two congenital electrophysiologists (KM-EP). The two congenital electrophysiologists were blinded to EKG diagnosis and patient clinical background. Enrollment KM recordings were compared to corresponding enrollment EKG to assess P wave axis, QRS axis, and T wave axis agreement in the lead most closely resembling the KM tracing. To be consistent with real-world clinical interpretation of heart rhythm assessment in adults with Fontan palliation, study physicians (KM-EP) were given the following diagnostic selections: clearly sinus rhythm, normal rate but atrial activity not discernable, wide complex rhythm < 100 bpm, bradycardia 100 bpm, wide complex rhythm > 100 bpm, possible atrial tachyarrhythmia, and uninterpretable. This categorization encompassed the interpretation spectrum, besides normal sinus rhythm, which would be considered normal in patients with Fontan palliation (e.g., bradycardia). The comparison of KM-auto interpretations to the KM-EP interpretation options were analyzed for agreement, as delineated in Table 1 . Any enrollment KM-EP read disagreements between the two congenital electrophysiologists underwent post hoc adjudication. Table 1 Description of how KM-auto interpretations were classified to KM-EP interpretations. bpm = beats per minute. Automated KM KM-EP Normal Clearly sinus rhythm Normal rate but atrial activity not clearly demonstrated Bradycardia 100 bpm Wide complex rhythm > 100 bpm Statistical Analysis Demographic information was summarized using count for categorical and dichotomous variables and median (IQR) for continuous variables. The number of follow-up transmissions per patient were summarized using a histogram and density plot. To determine the accuracy of the KM device, 3 sets of comparisons were made for the enrollment KM tracing: 1) EKG vs KM-EP, 2) EKG vs KM-auto, and 3) KM-EP vs KM-auto. Percent agreement and Cohen’s kappa were used as metrics of inter-rater reliability and concordance between KM interpretations, EKG reads, and KM-EP interpretations. Sensitivity, specificity, negative predictive value, and positive predictive value were calculated at the interpretation-level, but only those for a normal transmission are presented for brevity. Comparisons between those whose enrollment transmission agreed between the KM-auto and the KM-EP interpretations and those whose did not were made using Wilcoxon rank sum test for continuous variables and either Pearson’s chi-squared or Fisher’s exact test for categorical variables. All analyses were performed using R version 4.2.2. Results There were 118 patients with Fontan palliation identified, and a total of fifty patients, with a median age of 27 years (IQR 23,31), 29 (58%) male, were enrolled in this study (Fig. 1 ). By Fontan type, 33 (66%) patients had lateral tunnel Fontan palliation, and 32 (64%) had a single left ventricle (Table 2 ). Most patients were NYHA Class I (17, 34%) or II (26, 52%); 45 (92%) patients were ACHD physiologic stage C. The majority of patients had normal or mildly reduced systemic ventricle function (45, 94%) with normal or mild atrial-ventricular valve (AVV) regurgitation (45, 94%). Over half (28, 56%) of the study population had a history of any arrhythmia, either sustained or non-sustained, and 6% of patients had a previous atrial arrhythmia requiring cardioversion. Most patients had a Holter within one year of enrollment (38, 76%), and 16% of those patients had non-sustained SVT detected on recent Holter. Table 2 Demographics and clinical characteristics. AP = atrio-pulmonary; ICD = implantable cardioverter defibrillator. Characteristic N = 50 Age at Enrollment 27 (23, 31) Gender Male 29 (58%) Female 21 (42%) Underlying cardiac diagnosis Single RV 13 (26%) Single LV 32 (64%) Mixed 5 (10%) Type of Fontan Palliation Lateral Tunnel 33 (66%) Extracardiac 16 (32%) AP 1 (2.0%) Systemic ventricle Echo function : Normal/mildly reduced 45 (94%) Moderate 3 (6.3%) Severely depressed 0 (0%) AVV Regurgitation Normal/Mild 45 (94%) Moderate 3 (6.3%) Severely depressed 0 (0%) Unknown NYHA Function Class Class I Class II Class III Class IV 2 17 (34%) 26 (52%) 7 (14%) 0 (0%) Pulmonary Hypertension 1 (2.0%) Creatinine above cutoff for Sex 5 (11%) Pulse Ox (%) 91.0 (89.0, 93.0) Unknown 3 History of any arrhythmia, sustained or non-sustained 28 (56%) History of Sustained Atrial Flutter 3 (6.0%) Symptoms at the time of enrollment? 11 (22%) Pacemaker or ICD 13 (26%) Holter within 1 year of enrollment 38 (76%) Values are presented as median (IQR) or n (%) Enrollment and Patient Driven KM Tracings During the study period, there were 50 enrollment tracings and 510 follow up transmissions received from 34 (68%) patients, 449 of which were feasible for analysis, including 422 asymptomatic transmissions and 22 symptomatic transmissions. There was a median of 7.5 transmissions sent per patient (Fig. 2 ). Inter-rater reliability of the KM-EP interpretations had a very strong agreement for follow-up tracings (98% agreement, Cohen Κ = 0.89). Enrollment KM-auto compared to enrollment EKG Approximately two-thirds of the enrollment KM tracings 34/50 (68%) were most consistent with lead I of the 12 lead EKG. The QRS and T wave concordance analysis was consistent with the EKG in 96% of enrollment tracings (K 0.891 (0.74,1.0) and 0.9 (0.76,1.0), respectively). Notably, the P wave axis was concordant with the EKG in only 58% of enrollment tracings (Cohen K 0.381 (0.2,0.54)). Seventeen enrollment KM-auto interpretations (34%) were classified as uninterpretable; and the corresponding enrollment EKGs for these uninterpretable KM-auto enrollment transmissions demonstrated sinus rhythm, ectopic atrial rhythm, sinus rhythm with premature atrial contractions, and atrial flutter in one case. A single KM-auto enrollment interpretation as possible AF was determined to be an atrial-ventricular paced rhythm based upon comparison to the 12 lead EKG. There was 64% percent agreement (Cohens K 0.033 (-0.03,0.097)) between KM-auto and the 12 lead EKG. Sensitivity and specificity of the KM-auto interpretation to detect a normal transmission compared to enrollment 12 lead EKG were 65% and 100%, respectively (Table 3 ). Table 3 KM analysis demonstrating the sensitivity, specificity, positive predictive value (PPV), and negative predictive valve (NPV) of KM-auto normal interpretations. KM-Auto = automated KM reads; KM-EP = electrophysiologist KM interpretation. Agreement & Concordance Metrics Diagnostic Metrics for Normal Transmission Follow-up Period Comparison Percent Agreement Cohen’s K and 95% CI Sensitivity Specificity PPV NPV Enrollment EKG vs. KM-EP 0.90 -0.03 (-0.07, 0.02) 0.92 0.00 0.98 0.00 EKG vs. KM-Auto 0.64 0.03 (-0.03, 0.01) 0.65 1.00 1.00 0.06 KM-Auto vs KM-EP 0.68 0.19 (0.02, 0.37) 0.70 1.00 1.00 0.22 Follow-up KM-auto vs. KM-EP All 0.72 0.13 (0.08, 0.17) 0.75 0.96 1.00 0.18 Symptomatic 0.50 0.20 (0.01, 0.38) 0.59 1.00 1.00 0.42 Asymptomatic 0.73 0.11 (0.06, 0.16) 0.76 0.95 1.00 0.16 Enrollment KM-EP compared to enrollment EKG There were 46 enrollment KM-EP interpretations that were categorized as normal. Based on EKG, 18 of these 46 were classified as normal sinus rhythm, 18 as normal sinus rhythm with conduction delay, 4 as sinus bradycardia, 4 as ectopic atrial rhythm, 1 as junctional rhythm, and 1 as atrial flutter. Percent agreement between KM-EP and EKG reads was 90% (Cohen’s K -0.03 (-0.07,0.02)). The four KM-EP interpretations not categorized as normal were classified as possible AT in two of the cases or uninterpretable in the other two cases. The EKG for these 4 demonstrated normal sinus rhythm and ectopic atrial rhythm. Sensitivity of the KM-EP interpretations in detecting a normal rhythm was 92.8% (Table 3 ). Enrollment KM-EP compared to KM-auto The number of normal KM enrollment interpretations were higher in the KM-EP compared to the KM-auto reads 46/50 vs 32/50. There were two KM recordings that were uninterpretable by KM-EP evaluation, compared to 17 KM-auto interpretations. Percent agreement between KM-auto and KM-EP reads was only 68% (Cohen’s K 0.194 (0.018,0.37)). Additionally, enrollment transmissions were evaluated based on those which were concordant and discordant between KM-auto and KM-EP interpretation. History of any sustained or nonsustained arrhythmia was associated with discordant KM-auto and KM-EP interpretations (Table 4 ). No other clinical factors were found to be significantly associated with discordant interpretations. Table 4 Demographics and clinical characteristics comparing initial enrollment transmissions that had KM-auto and KM-EP agreement versus disagreement. Initial Transmission Characteristic Agreement , N = 34 Disagreement , N = 16 p-value Age at Enrollment 28 (23, 30) 26 (22, 37) 0.803 Gender 0.863 Male 20 (59%) 9 (56%) Female 14 (41%) 7 (44%) Underlying cardiac diagnosis 0.653 Single RV 8 (24%) 5 (31%) Single LV 23 (68%) 9 (56%) Mixed 3 (8.8%) 2 (13%) Type of Fontan Palliation 0.303 AP 1 (2.9%) 0 (0%) Extracardiac 13 (38%) 3 (19%) Lateral Tunnel 20 (59%) 13 (81%) NYHA Function Class 0.341 Class I 13 (38%) 4 (25%) Class II 18 (53%) 8 (50%) Class III 3 (8.8%) 4 (25%) Class IV 0 (0%) 0 (0%) ACHD Physiologic Class 0.463 A 1 (2.9%) 0 (0%) B 1 (2.9%) 2 (13%) C 32 (94%) 13 (87%) D 0 (0%) 0 (0%) Unknown 0 1 Systemic ventricle Echo function : 0.227 Normal/mildly reduced 32 (97%) 13 (87%) Moderate 1 (3.0%) 2 (13%) Severely depressed 0 (0%) 0 (0%) Unknown 1 1 AVV Regurgitation > 0.999 Normal/Mild 31 (94%) 14 (93%) Moderate 2 (6.1%) 1 (6.7%) Severely depressed 0 (0%) 0 (0%) Unknown 1 1 Pulse Ox (%) 91.5 (88.8, 93.3) 90.0 (89.5, 91.0) 0.396 Unknown 2 1 History of arrhythmia (at time of enrollment or prior to enrollment) 15 (44%) 13 (81%) 0.014 Symptoms at the time of enrollment? 8 (24%) 3 (19%) > 0.999 Pacemaker or ICD 6 (18%) 7 (44%) 0.082 Match ECG Lead 0.520 I 25 (74%) 9 (56%) P-wave matched? 22 (65%) 7 (44%) 0.161 Values are presented as median (IQR) or n (%) Follow up transmission KM-auto compared to KM-EP KM-auto interpretations of the asymptomatic transmissions included 306/422 normal, 21/422 possible AF, 27/422 tachycardia, and 68/422 uninterpretable. During the study, 22 symptomatic transmissions were submitted by 11 patients, and the KM-auto reads were 10/22 normal, 3/22 possible AF, 2/22 tachycardia, and 7/22 uninterpretable. The sensitivity and specificity for KM-auto to detect a normal transmission compared to KM-EP interpretations of all follow up transmissions was 75% and 96%, respectively (Table 3 ). The highest agreement of the KM-auto to KM-EP interpretation was for asymptomatic transmissions (= 73% (Cohen K = 0.112). Of note, one symptomatic KM submission had a KM-auto interpretation of normal but was noted by a clinical team to be a higher heart rate than their normal baseline, and had atrial flutter confirmed on a follow up 12 lead EKG (Fig. 3 ). There were 16 (34%) enrolled patients who did not submit any follow up transmissions. Medical records were reviewed for these patients and confirmed no known atrial arrhythmias occurred during the study period. Discussion While there is an increasing fund of literature supporting the use of patient driven heart rhythm monitors for patients without CHD, accuracy of these devices in the ever-growing ACHD population has not been extensively studied. Enrollment KM recordings in this adult Fontan population were most similar to lead I in comparison to the standard 12 lead EKG, consistent with manufacturer design. In comparison to enrollment 12 lead EKG, there was a high concordance for the QRS complex and T wave axis, but a poor P wave axis concordance on KM recordings. This is an important consideration given the high prevalence of atrial arrhythmias, specifically intra-atrial reentrant tachycardias (IART), in adults with Fontan palliation. For patient driven rhythm monitoring devices, including the KM device, there is significant evidence validating the algorithmic technology to diagnose and manage atrial fibrillation, largely based on analysis of the R-R interval [8, 25–30] . However, for IART the R-R interval is often regular, so the algorithm for arrhythmia detection may be inaccurate. This is a known barrier for non-AF arrhythmia detection with patient driven EKG devices [31] . The percentage of enrollment KM-auto interpretations that were uninterpretable (34%) in this study was higher compared to other studies with non-CHD patients [5, 8, 13, 26, 27, 29] . When compared to enrollment EKG, the uninterpretable rhythms were found to be sinus rhythm with premature atrial complexes, sinus arrhythmia, intraventricular conduction delay, and ventricular paced rhythm, all rhythms that would give either variability in R-R interval or wide QRS complex. Normal KM interpretations increased to 94% with when overread by a physician (KM-EP), similar to prior studies where physician overreads improved accuracy [8, 29, 32] . Few atrial arrhythmias were identified during the study period, including both enrollment and follow up transmission data. Follow up KM transmissions confirmed to be atrial arrhythmias occurred in symptomatic patients, although detection of atrial arrhythmias required clinician overread and additional contextual patient information. The patient driven aspect of the KM device allowed patients to record symptomatic events that prompted a comparison to their baseline heart rate and EKG, which led to arrhythmia detection requiring cardioversion in one patient. Thus, our proposed use of the KM device in adult Fontan patients includes overread of symptomatic events and events noted to have higher heart rate than patient baseline resting heart rate (Fig. 4 ). Study Limitations This study used the KM device solely, though other patient driven and wearable biosensing monitors exist. A large number of enrolled patients did not send weekly asymptomatic transmissions as per study protocol, even when prompted by a weekly email reminder, suggesting that patient driven EKG monitoring for asymptomatic arrhythmias may not be reliable for the early detection of asymptomatic arrhythmias in patients who are less motivated to send transmissions. Conclusion In this cohort of relatively healthy adults with Fontan palliation, the diagnostic performance of the KM device required physician overread due to high number of uninterpretable KM-auto results. Though patient driven heart rhythm monitoring can accurately detect AF in non-CHD patients, this study suggests that a KM-auto reading of normal may accurately identify a normal rhythm, though may miss atrial arrhythmias. We recommend abnormal or uninterpretable KM device interpretations, symptomatic transmissions, and any transmissions with a high heart rate compared to a patient’s normal baseline be reviewed by the clinical team. Declarations Funding: This work was supported by a grant (A.R.Y.) from The Heart Center intramural program (51108-0005-1219) at Nationwide Children’s Hospital All authors contributed to the study conception, design, and analysis. Competing Interests : There are no financial or non-financial conflicts of interest of any author. Ethics Approval : This research involved human participants, and informed consent was obtained from all individual participants included in the study. Consent to publish : The authors affirm that human research participants provided informed consent for publication of the KardiaMobile recordings. Data availability : Data for this study was stored on password protected file repositories. If further investigation is required, this data can be accessed by contacting the corresponding author. Author Contribution All authors contributed to the study conception and design. Conceptualization and design by A.D., A.K. 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Cite Share Download PDF Status: Published Journal Publication published 16 Aug, 2024 Read the published version in Pediatric Cardiology → Version 1 posted Editorial decision: Revision requested 17 Jul, 2024 Reviews received at journal 22 May, 2024 Reviewers agreed at journal 30 Apr, 2024 Reviewers agreed at journal 28 Apr, 2024 Reviewers invited by journal 25 Apr, 2024 Submission checks completed at journal 12 Apr, 2024 Editor assigned by journal 12 Apr, 2024 First submitted to journal 11 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4254187","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291079750,"identity":"5370a907-8969-465c-b321-7c1b9e0ed440","order_by":0,"name":"Matthew Laubham","email":"data:image/png;base64,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","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Matthew","middleName":"","lastName":"Laubham","suffix":""},{"id":291079751,"identity":"afab468e-93e1-47b5-902f-8f86ad74377b","order_by":1,"name":"Anudeep K Dodeja","email":"","orcid":"","institution":"University of Connecticut School of Medicine and Connecticut Children’s Hospital Hartford","correspondingAuthor":false,"prefix":"","firstName":"Anudeep","middleName":"K","lastName":"Dodeja","suffix":""},{"id":291079752,"identity":"460bed10-34b2-4726-89a7-641b5b432d08","order_by":2,"name":"Rohan Kumthekar","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rohan","middleName":"","lastName":"Kumthekar","suffix":""},{"id":291079753,"identity":"a30a264b-10fe-42f0-a7af-e3899076cf67","order_by":3,"name":"Victoria Shay","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Shay","suffix":""},{"id":291079754,"identity":"2ced66c6-c9d7-4636-97ea-93ca7e1a23a4","order_by":4,"name":"Nathan D’Emilio","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"D’Emilio","suffix":""},{"id":291079755,"identity":"c92247e5-b44b-4606-aacf-6b9ed823cee7","order_by":5,"name":"Sara Conroy","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Conroy","suffix":""},{"id":291079756,"identity":"b7823176-4862-4fce-a7c0-8cfbe80b461c","order_by":6,"name":"May Ling Mah","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"May","middleName":"Ling","lastName":"Mah","suffix":""},{"id":291079757,"identity":"c3c758ce-2885-4c21-9987-6c2705af6745","order_by":7,"name":"Chance Alvarado","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chance","middleName":"","lastName":"Alvarado","suffix":""},{"id":291079758,"identity":"a25b1f4a-babf-4158-979b-32dbc652a658","order_by":8,"name":"Anna Kamp","email":"","orcid":"","institution":"Nationwide Children’s Hospital Heart Center, Nationwide Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Kamp","suffix":""}],"badges":[],"createdAt":"2024-04-11 19:44:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4254187/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4254187/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00246-024-03614-6","type":"published","date":"2024-08-16T15:57:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55001952,"identity":"7b308bc8-7fe8-4d07-bc77-b02d88a0c979","added_by":"auto","created_at":"2024-04-19 18:38:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35820,"visible":true,"origin":"","legend":"\u003cp\u003ePatient Enrollment Process\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4254187/v1/36469942af22a3f596c74819.png"},{"id":55001956,"identity":"4ee7ebab-c463-4210-aa35-3d5b5295fb4b","added_by":"auto","created_at":"2024-04-19 18:38:56","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":346851,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the number of follow-up transmissions sent, demonstrating a median\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4254187/v1/8cd891c1a61900cf80396fd7.jpeg"},{"id":55001946,"identity":"5f45ff9e-cbc4-4a34-a4f5-228f776ebaba","added_by":"auto","created_at":"2024-04-19 18:38:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1724619,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) A symptomatic KM transmission with an automatic read of normal sinus rhythm. Because of a noticeable rate change from the clinical team, an EKG was obtained (\u003cstrong\u003eB\u003c/strong\u003e) showing atrial flutter. This was compared to the patient’s baseline EKG (\u003cstrong\u003eC\u003c/strong\u003e) that demonstrates a resting heart rate of 45 beats per minute (bpm).\u003c/p\u003e","description":"","filename":"floatimage35.png","url":"https://assets-eu.researchsquare.com/files/rs-4254187/v1/679eebcf220fcaefb3f56dd7.png"},{"id":55001948,"identity":"bb79f184-95c1-4c0c-b60e-333c5243ad42","added_by":"auto","created_at":"2024-04-19 18:38:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":41478,"visible":true,"origin":"","legend":"\u003cp\u003eA proposed workflow for use of patient driven KardiaMobile EKG device in adults with Fontan palliation.\u003c/p\u003e","description":"","filename":"floatimage61.png","url":"https://assets-eu.researchsquare.com/files/rs-4254187/v1/d476660608bd959c21fdaf84.png"},{"id":63070905,"identity":"d8691620-4f5e-4450-8b95-50df398a5de8","added_by":"auto","created_at":"2024-08-22 19:56:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2810966,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4254187/v1/135d89e3-49c8-4b2e-ae6e-26f4f96644b9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Patient Driven EKG Device Performance in Adults with Fontan Palliation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSmart devices are becoming a mainstream and validated means to monitor heart rate, sleep hygiene and blood pressure, track lifestyle behavior and fitness, and surveil for cardiac arrhythmias \u003csup\u003e[1\u0026ndash;3]\u003c/sup\u003e. Most direct-to-consumer devices have shown well established accuracy of discriminating between sinus rhythm and atrial fibrillation (AF) and have been used for AF screening, symptomatic paroxysmal or intermittent AF diagnosis, and post-ablative and post-cardioversion AF management \u003csup\u003e[4\u0026ndash;8]\u003c/sup\u003e. Patient driven electrocardiogram (EKG) devices have also been shown to be a valuable cost-effective tool in evaluating palpitations \u003csup\u003e[9\u0026ndash;12]\u003c/sup\u003e. However, their effectiveness for detecting non-AF arrhythmias, is unclear \u003csup\u003e[13\u0026ndash;16]\u003c/sup\u003e. Beyond AF detection and management of palpitations, there is little data regarding the utility of smart devices within the growing congenital heart disease (CHD) patient population \u003csup\u003e[17]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePatients with Fontan palliation have a higher risk of atrial tachyarrhythmias with an estimated arrhythmia prevalence of 20\u0026ndash;44% \u003csup\u003e[18\u0026ndash;20]\u003c/sup\u003e. Importantly, those who develop arrhythmias have a higher morbidity and mortality risk, with atrial arrhythmias being both a cause and consequence of Fontan failure \u003csup\u003e[18, 20, 21]\u003c/sup\u003e. The adult Fontan population represents a unique CHD cohort that could greatly benefit from early detection of atrial arrhythmias. Current guidelines recommend annual ambulatory monitoring, typically with a traditional Holter monitor \u003csup\u003e[22]\u003c/sup\u003e. However, standard 24\u0026ndash;48 hour monitoring can often miss paroxysmal tachyarrhythmias. Longer term implantable monitoring may increase the chance of detecting infrequent arrhythmias, albeit more invasive and with increased cost.\u003c/p\u003e \u003cp\u003eThe KardiaMobile\u0026reg; (KM) device (AliveCor, Mountain View, CA), is a commercially available portable heart monitor, consisting of a single bipolar lead with a corresponding smart device application. This device generates a 30-second EKG resembling lead I and can monitor heart rate and rhythm in real time using algorithms generated from EKG data. The KM device received FDA clearance for detecting atrial fibrillation and sinus rhythm.\u003c/p\u003e \u003cp\u003eThe objective of this prospective study was to examine the accuracy and utility of the KM device\u0026rsquo;s interpretations in a cohort of adults with Fontan palliation. We hypothesize that the KM device could be used to accurately detect infrequent arrhythmias in symptomatic patients with Fontan palliation and help bridge the gap between more typical routine short-term ambulatory monitoring and more costly long term implantable monitors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis single center prospective study enrolled adult patients with Fontan palliation to use the KM heart rhythm monitoring device for both symptomatic episodes and asymptomatic weekly screening over a 1-year period. This study was approved by institutional IRB. Adult congenital heart disease (ACHD) clinic schedules were reviewed to identify patients who fit inclusion criteria, which consisted of patients\u0026thinsp;\u0026ge;\u0026thinsp;18 years of age at the time of enrollment with a history of Fontan palliation. Patients were recruited and consented for the study during their outpatient clinic appointment. Enrollment was from 2019 to 2021, with an institutional mandatory enrollment pause during 2020 due to the COVID-19 pandemic. Exclusion criteria consisted of patients with developmental delay or inability to properly use the KM device, patients without a smartphone, and patients without email access to send necessary study transmissions.\u003c/p\u003e \u003cp\u003eStudy team personnel set up the smartphone application and taught the enrollee how to use the app and KM device. A baseline 12-lead EKG and KM recording were obtained during the enrollment clinic visit. For enrollment analysis, the 12 lead EKG was considered the gold standard rhythm diagnostic modality for comparison. Clinically relevant arrhythmias were defined as any sustained or non-sustained supraventricular tachycardia (SVT) or wide complex tachycardia. Over the outlined 1-year follow up period, patients were instructed to submit weekly asymptomatic recordings that were prompted by weekly email reminders, as well as a KM recording of any symptomatic episodes. Transmitted recordings were submitted to a designated study email, reviewed by the study team and forwarded to the clinical team. Transmitted KM recordings were sent via institutional password protected emails and stored on a password protected network. Demographic information was obtained by review of electronic health record, and included age, clinical information, symptom history, previous Holter monitoring, previous 12 lead EKG results, electrophysiology studies, and cardiac imaging (echocardiography, MRI, CT). Patients were also categorized based on their ACHD anatomic and physiologic classification \u003csup\u003e[22]\u003c/sup\u003e. Study data was managed using a REDCap electronic database \u003csup\u003e[23, 24]\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eEKG and KM Interpretations\u003c/span\u003e:\u003c/h2\u003e \u003cp\u003eTo determine the accuracy of the automatic KM device readings (KM-auto), the KM-auto reading was compared to both an enrollment 12 lead EKG and interpretation of the KM device recording by two congenital electrophysiologists (KM-EP). The two congenital electrophysiologists were blinded to EKG diagnosis and patient clinical background. Enrollment KM recordings were compared to corresponding enrollment EKG to assess P wave axis, QRS axis, and T wave axis agreement in the lead most closely resembling the KM tracing.\u003c/p\u003e \u003cp\u003eTo be consistent with real-world clinical interpretation of heart rhythm assessment in adults with Fontan palliation, study physicians (KM-EP) were given the following diagnostic selections: clearly sinus rhythm, normal rate but atrial activity not discernable, wide complex rhythm\u0026thinsp;\u0026lt;\u0026thinsp;100 bpm, bradycardia\u0026thinsp;\u0026lt;\u0026thinsp;60 bpm, tachycardia\u0026thinsp;\u0026gt;\u0026thinsp;100 bpm, wide complex rhythm\u0026thinsp;\u0026gt;\u0026thinsp;100 bpm, possible atrial tachyarrhythmia, and uninterpretable. This categorization encompassed the interpretation spectrum, besides normal sinus rhythm, which would be considered normal in patients with Fontan palliation (e.g., bradycardia). The comparison of KM-auto interpretations to the KM-EP interpretation options were analyzed for agreement, as delineated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Any enrollment KM-EP read disagreements between the two congenital electrophysiologists underwent post hoc adjudication.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of how KM-auto interpretations were classified to KM-EP interpretations. bpm\u0026thinsp;=\u0026thinsp;beats per minute.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e Automated KM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKM-EP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClearly sinus rhythm\u003c/p\u003e \u003cp\u003eNormal rate but atrial activity not clearly demonstrated\u003c/p\u003e \u003cp\u003eBradycardia\u0026thinsp;\u0026lt;\u0026thinsp;60 bpm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUninterpretable/Unreadable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUninterpretable / Artifact\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePossible Atrial Fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePossible atrial tachyarrhythmia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTachycardia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSinus tachycardia\u0026thinsp;\u0026gt;\u0026thinsp;100 bpm\u003c/p\u003e \u003cp\u003eWide complex rhythm\u0026thinsp;\u0026gt;\u0026thinsp;100 bpm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDemographic information was summarized using count for categorical and dichotomous variables and median (IQR) for continuous variables. The number of follow-up transmissions per patient were summarized using a histogram and density plot. To determine the accuracy of the KM device, 3 sets of comparisons were made for the enrollment KM tracing: 1) EKG vs KM-EP, 2) EKG vs KM-auto, and 3) KM-EP vs KM-auto. Percent agreement and Cohen\u0026rsquo;s kappa were used as metrics of inter-rater reliability and concordance between KM interpretations, EKG reads, and KM-EP interpretations.\u003c/p\u003e \u003cp\u003eSensitivity, specificity, negative predictive value, and positive predictive value were calculated at the interpretation-level, but only those for a normal transmission are presented for brevity. Comparisons between those whose enrollment transmission agreed between the KM-auto and the KM-EP interpretations and those whose did not were made using Wilcoxon rank sum test for continuous variables and either Pearson\u0026rsquo;s chi-squared or Fisher\u0026rsquo;s exact test for categorical variables. All analyses were performed using R version 4.2.2.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 118 patients with Fontan palliation identified, and a total of fifty patients, with a median age of 27 years (IQR 23,31), 29 (58%) male, were enrolled in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). By Fontan type, 33 (66%) patients had lateral tunnel Fontan palliation, and 32 (64%) had a single left ventricle (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most patients were NYHA Class I (17, 34%) or II (26, 52%); 45 (92%) patients were ACHD physiologic stage C. The majority of patients had normal or mildly reduced systemic ventricle function (45, 94%) with normal or mild atrial-ventricular valve (AVV) regurgitation (45, 94%). Over half (28, 56%) of the study population had a history of any arrhythmia, either sustained or non-sustained, and 6% of patients had a previous atrial arrhythmia requiring cardioversion. Most patients had a Holter within one year of enrollment (38, 76%), and 16% of those patients had non-sustained SVT detected on recent Holter.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and clinical characteristics. AP\u0026thinsp;=\u0026thinsp;atrio-pulmonary; ICD\u0026thinsp;=\u0026thinsp;implantable cardioverter defibrillator.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;50\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at Enrollment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (23, 31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (58%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (42%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnderlying cardiac diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle LV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Fontan Palliation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLateral Tunnel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtracardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (32%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSystemic ventricle Echo function\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal/mildly reduced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely depressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAVV Regurgitation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal/Mild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely depressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003cp\u003e\u003cb\u003eNYHA Function Class\u003c/b\u003e\u003c/p\u003e \u003cp\u003eClass I\u003c/p\u003e \u003cp\u003eClass II\u003c/p\u003e \u003cp\u003eClass III\u003c/p\u003e \u003cp\u003eClass IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e17 (34%)\u003c/p\u003e \u003cp\u003e26 (52%)\u003c/p\u003e \u003cp\u003e7 (14%)\u003c/p\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary Hypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine above cutoff for Sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulse Ox (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.0 (89.0, 93.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of any arrhythmia, sustained or non-sustained\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (56%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of Sustained Atrial Flutter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptoms at the time of enrollment?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePacemaker or ICD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHolter within 1 year of enrollment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eValues are presented as median (IQR) or n (%)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEnrollment and Patient Driven KM Tracings\u003c/h2\u003e \u003cp\u003eDuring the study period, there were 50 enrollment tracings and 510 follow up transmissions received from 34 (68%) patients, 449 of which were feasible for analysis, including 422 asymptomatic transmissions and 22 symptomatic transmissions. There was a median of 7.5 transmissions sent per patient (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Inter-rater reliability of the KM-EP interpretations had a very strong agreement for follow-up tracings (98% agreement, Cohen Κ\u0026thinsp;=\u0026thinsp;0.89).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEnrollment KM-auto compared to enrollment EKG\u003c/h2\u003e \u003cp\u003eApproximately two-thirds of the enrollment KM tracings 34/50 (68%) were most consistent with lead I of the 12 lead EKG. The QRS and T wave concordance analysis was consistent with the EKG in 96% of enrollment tracings (K 0.891 (0.74,1.0) and 0.9 (0.76,1.0), respectively). Notably, the P wave axis was concordant with the EKG in only 58% of enrollment tracings (Cohen K 0.381 (0.2,0.54)).\u003c/p\u003e \u003cp\u003eSeventeen enrollment KM-auto interpretations (34%) were classified as uninterpretable; and the corresponding enrollment EKGs for these uninterpretable KM-auto enrollment transmissions demonstrated sinus rhythm, ectopic atrial rhythm, sinus rhythm with premature atrial contractions, and atrial flutter in one case. A single KM-auto enrollment interpretation as possible AF was determined to be an atrial-ventricular paced rhythm based upon comparison to the 12 lead EKG. There was 64% percent agreement (Cohens K 0.033 (-0.03,0.097)) between KM-auto and the 12 lead EKG. Sensitivity and specificity of the KM-auto interpretation to detect a normal transmission compared to enrollment 12 lead EKG were 65% and 100%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKM analysis demonstrating the sensitivity, specificity, positive predictive value (PPV), and negative predictive valve (NPV) of KM-auto normal interpretations. KM-Auto\u0026thinsp;=\u0026thinsp;automated KM reads; KM-EP\u0026thinsp;=\u0026thinsp;electrophysiologist KM interpretation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAgreement \u0026amp; Concordance Metrics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eDiagnostic Metrics for Normal Transmission\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up Period\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent Agreement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCohen\u0026rsquo;s K and 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEnrollment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEKG vs. KM-EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003cp\u003e(-0.07, 0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEKG vs. KM-Auto\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003cp\u003e(-0.03, 0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eKM-Auto vs KM-EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003cp\u003e(0.02, 0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eFollow-up\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eKM-auto vs. KM-EP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAll\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003cp\u003e(0.08, 0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSymptomatic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003cp\u003e(0.01, 0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAsymptomatic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003cp\u003e(0.06, 0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEnrollment KM-EP compared to enrollment EKG\u003c/h2\u003e \u003cp\u003eThere were 46 enrollment KM-EP interpretations that were categorized as normal. Based on EKG, 18 of these 46 were classified as normal sinus rhythm, 18 as normal sinus rhythm with conduction delay, 4 as sinus bradycardia, 4 as ectopic atrial rhythm, 1 as junctional rhythm, and 1 as atrial flutter. Percent agreement between KM-EP and EKG reads was 90% (Cohen\u0026rsquo;s K -0.03 (-0.07,0.02)). The four KM-EP interpretations not categorized as normal were classified as possible AT in two of the cases or uninterpretable in the other two cases. The EKG for these 4 demonstrated normal sinus rhythm and ectopic atrial rhythm. Sensitivity of the KM-EP interpretations in detecting a normal rhythm was 92.8% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEnrollment KM-EP compared to KM-auto\u003c/h2\u003e \u003cp\u003eThe number of normal KM enrollment interpretations were higher in the KM-EP compared to the KM-auto reads 46/50 vs 32/50. There were two KM recordings that were uninterpretable by KM-EP evaluation, compared to 17 KM-auto interpretations. Percent agreement between KM-auto and KM-EP reads was only 68% (Cohen\u0026rsquo;s K 0.194 (0.018,0.37)).\u003c/p\u003e \u003cp\u003eAdditionally, enrollment transmissions were evaluated based on those which were concordant and discordant between KM-auto and KM-EP interpretation. History of any sustained or nonsustained arrhythmia was associated with discordant KM-auto and KM-EP interpretations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). No other clinical factors were found to be significantly associated with discordant interpretations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and clinical characteristics comparing initial enrollment transmissions that had KM-auto and KM-EP agreement versus disagreement.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eInitial Transmission\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharacteristic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAgreement\u003c/b\u003e, N\u0026thinsp;=\u0026thinsp;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eDisagreement\u003c/b\u003e, N\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at Enrollment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (23, 30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (22, 37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnderlying cardiac diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle LV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Fontan Palliation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtracardiac\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLateral Tunnel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNYHA Function Class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eACHD Physiologic Class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e1\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSystemic ventricle Echo function\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal/mildly reduced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely depressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAVV Regurgitation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal/Mild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely depressed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulse Ox (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.5 (88.8, 93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.0 (89.5, 91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of arrhythmia (at time of enrollment or prior to enrollment)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptoms at the time of enrollment?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePacemaker or ICD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMatch ECG Lead\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP-wave matched?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are presented as median (IQR) or n (%)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFollow up transmission KM-auto compared to KM-EP\u003c/h2\u003e \u003cp\u003eKM-auto interpretations of the asymptomatic transmissions included 306/422 normal, 21/422 possible AF, 27/422 tachycardia, and 68/422 uninterpretable. During the study, 22 symptomatic transmissions were submitted by 11 patients, and the KM-auto reads were 10/22 normal, 3/22 possible AF, 2/22 tachycardia, and 7/22 uninterpretable. The sensitivity and specificity for KM-auto to detect a normal transmission compared to KM-EP interpretations of all follow up transmissions was 75% and 96%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The highest agreement of the KM-auto to KM-EP interpretation was for asymptomatic transmissions (=\u0026thinsp;73% (Cohen K\u0026thinsp;=\u0026thinsp;0.112). Of note, one symptomatic KM submission had a KM-auto interpretation of normal but was noted by a clinical team to be a higher heart rate than their normal baseline, and had atrial flutter confirmed on a follow up 12 lead EKG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere were 16 (34%) enrolled patients who did not submit any follow up transmissions. Medical records were reviewed for these patients and confirmed no known atrial arrhythmias occurred during the study period.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhile there is an increasing fund of literature supporting the use of patient driven heart rhythm monitors for patients without CHD, accuracy of these devices in the ever-growing ACHD population has not been extensively studied.\u003c/p\u003e \u003cp\u003eEnrollment KM recordings in this adult Fontan population were most similar to lead I in comparison to the standard 12 lead EKG, consistent with manufacturer design. In comparison to enrollment 12 lead EKG, there was a high concordance for the QRS complex and T wave axis, but a poor P wave axis concordance on KM recordings. This is an important consideration given the high prevalence of atrial arrhythmias, specifically intra-atrial reentrant tachycardias (IART), in adults with Fontan palliation. For patient driven rhythm monitoring devices, including the KM device, there is significant evidence validating the algorithmic technology to diagnose and manage atrial fibrillation, largely based on analysis of the R-R interval \u003csup\u003e[8, 25\u0026ndash;30]\u003c/sup\u003e. However, for IART the R-R interval is often regular, so the algorithm for arrhythmia detection may be inaccurate. This is a known barrier for non-AF arrhythmia detection with patient driven EKG devices\u003csup\u003e[31]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe percentage of enrollment KM-auto interpretations that were uninterpretable (34%) in this study was higher compared to other studies with non-CHD patients \u003csup\u003e[5, 8, 13, 26, 27, 29]\u003c/sup\u003e. When compared to enrollment EKG, the uninterpretable rhythms were found to be sinus rhythm with premature atrial complexes, sinus arrhythmia, intraventricular conduction delay, and ventricular paced rhythm, all rhythms that would give either variability in R-R interval or wide QRS complex. Normal KM interpretations increased to 94% with when overread by a physician (KM-EP), similar to prior studies where physician overreads improved accuracy \u003csup\u003e[8, 29, 32]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFew atrial arrhythmias were identified during the study period, including both enrollment and follow up transmission data. Follow up KM transmissions confirmed to be atrial arrhythmias occurred in symptomatic patients, although detection of atrial arrhythmias required clinician overread and additional contextual patient information. The patient driven aspect of the KM device allowed patients to record symptomatic events that prompted a comparison to their baseline heart rate and EKG, which led to arrhythmia detection requiring cardioversion in one patient. Thus, our proposed use of the KM device in adult Fontan patients includes overread of symptomatic events and events noted to have higher heart rate than patient baseline resting heart rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitations\u003c/h2\u003e \u003cp\u003eThis study used the KM device solely, though other patient driven and wearable biosensing monitors exist. A large number of enrolled patients did not send weekly asymptomatic transmissions as per study protocol, even when prompted by a weekly email reminder, suggesting that patient driven EKG monitoring for asymptomatic arrhythmias may not be reliable for the early detection of asymptomatic arrhythmias in patients who are less motivated to send transmissions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this cohort of relatively healthy adults with Fontan palliation, the diagnostic performance of the KM device required physician overread due to high number of uninterpretable KM-auto results. Though patient driven heart rhythm monitoring can accurately detect AF in non-CHD patients, this study suggests that a KM-auto reading of normal may accurately identify a normal rhythm, though may miss atrial arrhythmias. We recommend abnormal or uninterpretable KM device interpretations, symptomatic transmissions, and any transmissions with a high heart rate compared to a patient\u0026rsquo;s normal baseline be reviewed by the clinical team.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by a grant (A.R.Y.) from The Heart Center intramural program (51108-0005-1219) at Nationwide Children\u0026rsquo;s Hospital\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception, design, and analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e: There are no financial or non-financial conflicts of interest of any author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e: This research involved human participants, and informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e: The authors affirm that human research participants provided informed consent for publication of the KardiaMobile recordings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e: Data for this study was stored on password protected file repositories. If further investigation is required, this data can be accessed by contacting the corresponding author.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Conceptualization and design by A.D., A.K. Material preparation, data collection and analysis were performed by M.L., R.K., N.D., V.K, C.A., and S.C. The first draft of the manuscript was written by M.L., and all authors commented on previous versions of the manuscript including M.M. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eImtiaz SA. A Systematic Review of Sensing Technologies for Wearable Sleep Staging. \u003cem\u003eSensors (Basel)\u003c/em\u003e. 2021;21.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKristoffersson A and Linden M. 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Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation. \u003cem\u003eHeart\u003c/em\u003e. 2020;106:665\u0026ndash;670.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-cardiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pedc","sideBox":"Learn more about [Pediatric Cardiology](http://link.springer.com/journal/246)","snPcode":"246","submissionUrl":"https://submission.nature.com/new-submission/246/3","title":"Pediatric Cardiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Fontan, Arrhythmia, Adult Congenital Heart Disease, Artificial Intelligence, Diagnostics","lastPublishedDoi":"10.21203/rs.3.rs-4254187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4254187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe aim of this study was to evaluate the accuracy of the KardiaMobile (KM) device in adults with a Fontan palliation, and to assess the KM function as a screening tool for atrial arrhythmias.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhile patient driven electrocardiogram (EKG) devices are becoming a validated way to evaluate cardiac arrhythmias, their role for patients with congenital heart disease is less clear. Patients with single ventricle Fontan palliation have a high prevalence of atrial arrhythmias and represent a unique cohort that could benefit from early detection of atrial arrhythmias.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis single center prospective study enrolled adult patients with Fontan palliation to use the KM heart rhythm monitoring device for both symptomatic episodes and asymptomatic weekly screening over a 1-year period. Accuracy was assessed by comparing the automatic KM to physician overread and traditional EKG.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFifty patients were enrolled and 510 follow up transmissions were received. The sensitivity and specificity of enrollment KM-auto compared to EKG was 65% and 100%, respectively. The sensitivity and specificity of enrollment automated KM interpretations (KM-auto) compared to the electrophysiologist interpretation (KM-EP) was 75% and 96%, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn the adult Fontan palliation, the accuracy of the KM device to detect a normal rhythm was reliable and best with a physician overread. Abnormal or uninterpretable KM device interpretations, symptomatic transmissions, and any transmissions with a high heart rate compared to a patient\u0026rsquo;s normal baseline should warrant further review.\u003c/p\u003e","manuscriptTitle":"Patient Driven EKG Device Performance in Adults with Fontan Palliation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-19 18:38:50","doi":"10.21203/rs.3.rs-4254187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-17T15:27:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-23T02:28:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274332939597533525811628529107038092880","date":"2024-05-01T01:50:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"558920936926969113392126231877978203","date":"2024-04-28T17:06:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-25T17:09:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-12T05:51:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-12T05:51:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Cardiology","date":"2024-04-11T19:42:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-cardiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pedc","sideBox":"Learn more about [Pediatric Cardiology](http://link.springer.com/journal/246)","snPcode":"246","submissionUrl":"https://submission.nature.com/new-submission/246/3","title":"Pediatric Cardiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1ffd103a-08e0-4059-bcac-bed74a4eb1db","owner":[],"postedDate":"April 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-22T19:29:35+00:00","versionOfRecord":{"articleIdentity":"rs-4254187","link":"https://doi.org/10.1007/s00246-024-03614-6","journal":{"identity":"pediatric-cardiology","isVorOnly":false,"title":"Pediatric Cardiology"},"publishedOn":"2024-08-16 15:57:40","publishedOnDateReadable":"August 16th, 2024"},"versionCreatedAt":"2024-04-19 18:38:50","video":"","vorDoi":"10.1007/s00246-024-03614-6","vorDoiUrl":"https://doi.org/10.1007/s00246-024-03614-6","workflowStages":[]},"version":"v1","identity":"rs-4254187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4254187","identity":"rs-4254187","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}