Wireless Smartphone ECG Enables Large-Scale Screening in Diverse Populations

Use of portable single-lead electrocardiogram device as an alternative for QTc monitoring in critically ill patients

PURPOSE

Acquired QT prolongation is frequent and leads to a higher mortality rate in critically ill patients. KardiaMobile 1L® (KM1L) is a portable, user-friendly single lead, mobile alternative to conventional 12-lead electrocardiogram (12-L ECG) that could be more readily available, potentially facilitating more frequent QTc assessments in intensive care units (ICU); however, there is currently no evidence to validate this potential use.

METHODS

We conducted a prospective diagnostic test study comparing QT interval measurement using KM1L with conventional 12-L ECG ordered for any reason in patients admitted to an ICU. We compared the mean difference using a paired t-test, agreement using Bland-Altman analysis, and Lin's concordance coefficient, numerical precision (proportion of QT measurements with <10 ms difference between KM1L and conventional 12-L ECG), and clinical precision (concordance for adequate discrimination of prolonged QTc).

RESULTS

We included 114 patients (61.4% men, 60% cardiovascular etiology of hospitalization) with 131 12-L ECG traces. We found no statistical difference between corrected QT measurements (427 ms vs. 428 ms, p = .308). Lin's concordance coefficient was 0.848 (95% CI 0.801-0.894, p = .001). Clinical precision was excellent in males and substantial in females (Kappa 0.837 and 0.781, respectively). Numerical precision was lower in patients with vasoactive drugs (-13.99 ms), QT-prolonging drugs (13.84 ms), antiarrhythmic drugs (-12.87 ms), and a heart rate (HR) difference of ≥5 beats per minute (bpm) between devices (-11.26 ms).

CONCLUSION

Our study validates the clinical viability of KM1L, a single-lead mobile ECG device, for identifying prolonged QT intervals in ICU patients. Caution is warranted in patients with certain medical conditions that may affect numerical precision.

A Scoping Review of Varying Mobile Electrocardiographic Devices

The electrocardiogram (ECG) can now be measured using mobile devices. Mobile ECG devices, which are defined as devices capable of recording and transmitting non-standard ECGs, offer numerous advantages such as cost-effectiveness and being user-friendly. Mobile ECG can also extend recording lengths (e.g., 2 days, 14 days), which is necessary to capture important intermittent events (e.g., cardiac arrhythmias) and evaluate prognostic risk markers (e.g., prolonged corrected QT (QTc) interval). Some mobile ECG devices can even connect to broadband networks allowing patients to remotely transmit their ECG to a clinician. This article systematically examines different mobile ECG devices used in prior studies and provides a detailed assessment of five diverse yet commonly used mobile ECG devices: AliveCor KardiaMobile; AliveCor KardiaMobile 6L; iRhythm ZioPatch; Apple Smartwatch ECG; and CardioSecur System. These mobile ECG devices are diverse in the number of leads measured and the duration of monitoring. Similar to their diversity, there has been a wide range of clinical applications of mobile ECG devices. Despite significant progress, questions regarding data quality, and clinican and patient acceptance and compliance persist.

Evaluation of a smartphone electrocardiograph in healthy foals and comparison to standard base-apex electrocardiography

Smartphone-based technology for ECG recording has recently spread as a complementary tool for electrocardiographic screening and monitoring in adult horses and in other animal species. The present study aimed to assess the feasibility and accuracy of a smartphone-based ECG in healthy foals. This was a prospective observational study (authorization n. 45,865/2016) including 22 foals aged less than 21 days. A reference standard base-apex ECG (rECG) was acquired, and a smartphone ECG (sECG) was recorded immediately after by using a smartphone-based single lead electrocardiograph. All ECG tracings were evaluated in a blind fashion by a single board-certified cardiologist, who judged whether the tracings were acceptable for interpretation and performed ECG measurements and diagnosis. The Spearman correlation coefficient, the Cohen's k test and the Bland-Altman test were used to assess the agreement between sECG and rECG. All sECG tracings were acceptable for interpretation. All foals showed sinus rhythm on both rRCG and sECG tracings, with perfect agreement in heart rate classification (κ = 0.87; p < 0.001). No clinically relevant differences were found in the assessment of waves and intervals duration. Concerning P wave and QRS complex polarity, the percentage of agreement between rECG and sECG was 78% and 83%, respectively. About ECG tracing quality, rECG and sECG showed a substantial agreement (κ = 0.624; p < 0.001). In conclusion, the smartphone-based ECG device tested in the present study recorded good quality single-lead ECG tracings in foals, reliable for heart rate and ECG measurements, but different polarity of P waves and QRS complexes was found in some foals in comparison to rECG.

Detection of atrial fibrillation in persons aged 65 years and above using a mobile electrocardiogram device

BACKGROUND

Untreated atrial fibrillation (AF) often results in increased morbidity and mortality. Opportunistic AF screening in persons aged ≥ 65 years is recommended to identify patients with AF in order to prevent AF-related complications.

OBJECTIVE

The aim of this study was to assess the feasibility of screening persons for AF with the Kardia mobile electrocardiogram device (MED) and to determine the percentage of newly detected AF cases by selective population screening in the Netherlands.

METHODS

Persons aged ≥ 65 years, without a medical history of AF, in nursing homes, at public events or visiting the general practitioner (GP) were approached to participate. A Kardia MED smartphone ECG (sECG) was recorded and the CHA2DS2-VASc score was calculated. An automated AF algorithm classified the sECGs as 'sinus rhythm', 'AF' or 'unclassified'. In the case of AF, participants were referred to their GP. All sECGs were assessed by blinded experts.

RESULTS

A total of 2168 participants were screened for AF. According to the expert's interpretation, 2.5% had newly detected AF, of whom 76.4% never experienced palpitations and 89.1% had a CHA2DS2-VASc score ≥ 2. The algorithm result was unclassified in 12.2% of cases, of which 95.5% were interpretable by experts. With expert opinion as the gold standard and excluding unclassified sECGs, the Kardia MED's negative and positive predictive value for detecting AF was 99.8% and 60.0%, respectively.

CONCLUSION

Screening for AF using the Kardia MED is feasible and results in 2.5% newly detected AF cases. Expert interpretation of algorithm outcomes AF and unclassified is recommended.

AttentionCovidNet: Efficient ECG-based diagnosis of COVID-19

The novel coronavirus caused a worldwide pandemic. Rapid detection of COVID-19 can help reduce the spread of the novel coronavirus as well as the burden on healthcare systems worldwide. The current method of detecting COVID-19 suffers from low sensitivity, with estimates of 50%-70% in clinical settings. Therefore, in this study, we propose AttentionCovidNet, an efficient model for the detection of COVID-19 based on a channel attention convolutional neural network for electrocardiograms. The electrocardiogram is a non-invasive test, and so can be more easily obtained from a patient. We show that the proposed model achieves state-of-the-art results compared to recent models in the field, achieving metrics of 0.993, 0.997, 0.993, and 0.995 for accuracy, precision, recall, and F1 score, respectively. These results indicate both the promise of the proposed model as an alternative test for COVID-19, as well as the potential of ECG data as a diagnostic tool for COVID-19.

Serial electrocardiogram recordings revealed a high prevalence of QT interval prolongation in patients with tuberculosis receiving fluoroquinolones

BACKGROUND

Fluoroquinolones, crucial components of treatment regimens for drug-resistant tuberculosis (TB), are associated with QT interval prolongation and risks of fatal cardiac arrhythmias. However, few studies have explored dynamic changes in the QT interval in patients receiving QT-prolonging agents.

METHODS

This prospective cohort study recruited hospitalized patients with TB who received fluoroquinolones. The study investigated the variability of the QT interval by using serial electrocardiograms (ECGs) recorded four times daily. This study analyzed the accuracy of intermittent and single-lead ECG monitoring in detecting QT interval prolongation.

RESULTS

This study included 32 patients. The mean age was 68.6 ± 13.2 years. The results revealed mild-to-moderate and severe QT interval prolongation in 13 (41%) and 5 (16%) patients, respectively. The incremental yields in sensitivity of one to four daily ECG recordings were 61.0%, 26.1%, 5.6%, and 7.3% in detecting mild-to-moderate QT interval prolongation, and 66.7%, 20.0%, 6.7%, and 6.7% in detecting severe QT interval prolongation. The sensitivity levels of lead II and V5 ECGs in detecting mild-to-moderate and severe QT interval prolongation exceeded 80%, and their specificity levels exceeded 95%.

CONCLUSION

This study revealed a high prevalence of QT interval prolongation in older patients with TB who receive fluoroquinolones, particularly those with multiple cardiovascular risk factors. Sparsely intermittent ECG monitoring, the prevailing strategy in active drug safety monitoring programs, is inadequate owing to multifactorial and circadian QT interval variability. Additional studies performing serial ECG monitoring are warranted to enhance the understanding of dynamic QT interval changes in patients receiving QT-prolonging anti-TB agents.

Accuracy of mobile 6-lead electrocardiogram device for assessment of QT interval: a prospective validation study

INTRODUCTION

Ambulatory assessment of the heart rate-corrected QT interval (QTc) can be of diagnostic value, for example in patients on QTc-prolonging medication. Repeating sequential 12-lead electrocardiograms (ECGs) to monitor the QTc is cumbersome, but mobile ECG (mECG) devices can potentially solve this problem. As the accuracy of single-lead mECG devices is reportedly variable, a multilead mECG device may be more accurate.

METHODS

This prospective dual-centre study included outpatients visiting our cardiology clinics for any indication. Participants underwent an mECG recording using a smartphone-enabled 6‑lead mECG device immediately before or immediately after a conventional 12-lead ECG recording. Multiple QTc values in both recordings were manually measured in leads I and II using the tangent method and subsequently compared.

RESULTS

In total, 234 subjects were included (mean ± standard deviation (SD) age: 57 ± 17 years; 58% males), of whom 133 (57%) had cardiac disease. QTc measurement in any lead was impossible due to artefacts in 16 mECGs (7%) and no 12-lead ECGs. Mean (± SD) QTc in lead II on the mECG and 12-lead ECG was 401 ± 30 and 406 ± 31 ms, respectively. Mean (± SD) absolute difference in QTc values between both modalities was 12 ± 9 ms (r = 0.856; p < 0.001). In 55% of the subjects, the absolute difference between QTc values was < 10 ms.

CONCLUSION

A 6-lead mECG allows for QTc assessment with good accuracy and can be used safely in ambulatory QTc monitoring. This may improve patient satisfaction and reduce healthcare costs.

Telemedicine in the Era of a Pandemic: Usefulness of a Novel Three-Lead ECG

The 12-lead electrocardiogram (ECG) is a first-line diagnostic tool for patients with cardiac symptoms. As observed during the COVID-19 pandemic, the ECG is essential to the initial patient evaluation. The novel KardioPal three-lead-based ECG reconstructive technology provides a potential alternative to a standard ECG, reducing the response time and cost of treatment and improving patient comfort. Our study aimed to evaluate the diagnostic accuracy of a reconstructed 12-lead ECG obtained by the KardioPal technology, comparing it with the standard 12-lead ECG, and to assess the feasibility and time required to obtain a reconstructed ECG in a real-life scenario. A prospective, nonrandomized, single-center, adjudicator-blinded trial was conducted on 102 patients during the COVID-19 pandemic at the Dedinje Cardiovascular Institute in Belgrade. The KardioPal system demonstrated a high feasibility rate (99%), with high specificity (96.3%), sensitivity (95.8%), and diagnostic accuracy (96.1%) for obtaining clinically relevant matching of reconstructed 12-lead compared to the standard 12-lead ECG recording. This novel technology provided a significant reduction in ECG acquisition time and the need for personnel and space for obtaining ECG recordings, thereby reducing the risk of viral transmission and the burden on an already overwhelmed healthcare system such as the one experienced during the COVID-19 pandemic.

Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review

BACKGROUND

Electrocardiograms (ECGs) are used by physicians to record, monitor, and diagnose the electrical activity of the heart. Recent technological advances have allowed ECG devices to move out of the clinic and into the home environment. There is a great variety of mobile ECG devices with the capabilities to be used in home environments.

OBJECTIVE

This scoping review aimed to provide a comprehensive overview of the current landscape of mobile ECG devices, including the technology used, intended clinical use, and available clinical evidence.

METHODS

We conducted a scoping review to identify studies concerning mobile ECG devices in the electronic database PubMed. Secondarily, an internet search was performed to identify other ECG devices available in the market. We summarized the devices' technical information and usability characteristics based on manufacturer data such as datasheets and user manuals. For each device, we searched for clinical evidence on the capabilities to record heart disorders by performing individual searches in PubMed and ClinicalTrials.gov, as well as the Food and Drug Administration (FDA) 510(k) Premarket Notification and De Novo databases.

RESULTS

From the PubMed database and internet search, we identified 58 ECG devices with available manufacturer information. Technical characteristics such as shape, number of electrodes, and signal processing influence the capabilities of the devices to record cardiac disorders. Of the 58 devices, only 26 (45%) had clinical evidence available regarding their ability to detect heart disorders such as rhythm disorders, more specifically atrial fibrillation.

CONCLUSIONS

ECG devices available in the market are mainly intended to be used for the detection of arrhythmias. No devices are intended to be used for the detection of other cardiac disorders. Technical and design characteristics influence the intended use of the devices and use environments. For mobile ECG devices to be intended to detect other cardiac disorders, challenges regarding signal processing and sensor characteristics should be solved to increase their detection capabilities. Devices recently released include the use of other sensors on ECG devices to increase their detection capabilities.

Feasibility of using KardiaMobile-L6 for QT interval monitoring during the early phase of the COVID-19 pandemic in critical care patients

The electrocardiogram (ECG) represents an essential tool to determine cardiac electrical abnormalities in COVID-19 patients, the effects of anti-SARS-CoV-2 drugs, and potential drug interactions. Smartphone-based heart monitors have increased the spectrum of ECG monitoring however, we are not aware of its reliability in critically ill COVID-19 patients. We aim to evaluate the feasibility and reliability of nurse-performed smartphone electrocardiography for QT interval monitoring in critically ill COVID-19 patients using KardiaMobile-6L compared with the standard 12-lead ECG. An observational comparative study was conducted comparing consecutive KardiaMobile-6L and 12-lead ECG recordings obtained from 20 patients admitted to the intensive care unit with SARS-CoV-2 infection and on invasive mechanical ventilation. The heart rate-corrected QT (QTc) intervals measured by KardiaMobile-6L and 12-lead ECG were compared. In 60 percent of the recordings, QTc intervals measured by KardiaMobile-6L matched those by 12-lead ECG. The QTc intervals measured by KardiaMobile-6 and 12-lead ECG were 428 ± 45 ms and 425 ± 35 ms (p = 0.82), respectively. The former demonstrated good agreement (bias = 2.9 ms; standard deviation of bias = 29.6 ms) with the latter, using the Bland-Altman method of measurement agreement. In all but one recording, KardiaMobile-6L demonstrated QTc prolongation. QTc interval monitoring with KardiaMobile-6L in critically ill COVID-19 patients was feasible and demonstrated reliability comparable to the standard 12-lead ECG.

Evaluation of a new smartphone-based digital stethoscope featuring phonocardiography and electrocardiography in dogs and cats

This study assessed a new smartphone-based digital stethoscope (DS) featuring simultaneous phonocardiographic and one-lead electrocardiogram (ECG) recording in dogs and cats. The audio files and ECG traces obtained by the device were compared with conventional auscultation and standard ECG. A total of 99 dogs and nine cats were prospectively included. All cases underwent conventional auscultation using an acoustic stethoscope, standard six-lead ECG, standard echocardiography and recordings with the DS. All the audio recordings, phonocardiographic files and ECG traces were then blind reviewed by an expert operator. The agreement between methods was assessed using Cohen's kappa and the Bland-Altman test. Audio recordings were considered interpretable in 90% animals. Substantial agreement was found in the diagnosis of heart murmur (κ = 0.691) and gallop sound (k = 0.740). In nine animals with an echocardiographic diagnosis of heart disease, only the DS detected a heart murmur or gallop sound. ECG traces recorded with the new device were deemed interpretable in 88 % animals. Diagnosis of heart rhythm showed moderate agreement in the identification of atrial fibrillation (k = 0.596). The detection of ventricular premature complexes and bundle branch blocks revealed an almost perfect agreement (k = 1). Overall, the DS showed a good diagnostic accuracy in detecting heart murmurs, gallop sounds, ventricular premature complexes and bundle branch blocks. A clinically relevant overdiagnosis of atrial fibrillation was found but without evidence of false negatives. The DS could represent a useful screening tool for heart sound abnormalities and cardiac arrhythmias..

Layman electrocardiographic screening using smartphone-based multiple‑lead ECG device in school children

BACKGROUND

Pre-partecipation ECG screening of large populations has a significant socioeconomic impact. Technological progress now allows for high-tech-low-cost ECG screening using validated smartphone-based devices capable of guiding to the correct performance of a 12‑lead ECG by layman with no medical background.

METHODS

We enrolled 728 (364, 52% males) individuals, aged 12-13 years who underwent ECG screening with a smartphone 12‑lead ECG during school hours by layman volunteers. Correct electrodes placement was provided by a validated image-processing algorithm by the smartphone camera in the App. ECG interpretation was via a telecardiology platform and alterations classified following current standards.

RESULTS

A total of 741 ECGs were recorded, of which 13(2%) were technically not interpretable. Mean PR, QRS and QTc were: 145 ± 22, 85 ± 19 and 387 ± 57 msec. No QTc prolongation was observed. Mean QRS axis was 15°; 26 (4%) patients presented an iRBB. T-wave inversion from V1-V3 was present in 145 (21%) subjects. Twenty-one(3%) patients were referred to second level examination: deep Q-waves in inferior leads in 12(1.6%), ventricular ectopics in 5(0.7%), anterior T-waves inversions V1-V4 in 3(0.4%); extreme right axis deviation in 1(0.3%). Second line investigations did not provide any definitive diagnosis. Total project costs (material equipment and human cost) was 14.460€, 19.51€ per individual. The potential net saving with respect to current pre-participation screening cost was 19%.

CONCLUSIONS

Layman 12‑lead Smartphone-ECG population screening proved feasible and effective, with a rate of non-interpretable ECG of <5%. Potential cost-saving in ECG screening and recording was 19%, providing an appealing opportunity when large campaigns should be addressed also in developing countries.

Wrist-worn device combining PPG and ECG can be reliably used for atrial fibrillation detection in an outpatient setting

Aims

The aim was to validate the performance of a monitoring system consisting of a wrist-worn device and a data management cloud service intended to be used by medical professionals in detecting atrial fibrillation (AF).

Methods

Thirty adult patients diagnosed with AF alone or AF with concomitant flutter were recruited. Continuous photoplethysmogram (PPG) and intermittent 30 s Lead I electrocardiogram (ECG) recordings were collected over 48 h. The ECG was measured four times a day at prescheduled times, when notified due to irregular rhythm detected by PPG, and when self-initiated based on symptoms. Three-channel Holter ECG was used as the reference.

Results

The subjects recorded a total of 1,415 h of continuous PPG data and 3.8 h of intermittent ECG data over the study period. The PPG data were analyzed by the system's algorithm in 5-min segments. The segments containing adequate amounts, at least ~30 s, of adequate quality PPG data for rhythm assessment algorithm, were included. After rejecting 46% of the 5-min segments, the remaining data were compared with annotated Holter ECG yielding AF detection sensitivity and specificity of 95.6 and 99.2%, respectively. The ECG analysis algorithm labeled 10% of the 30-s ECG records as inadequate quality and these were excluded from the analysis. The ECG AF detection sensitivity and specificity were 97.7 and 89.8%, respectively. The usability of the system was found to be good by both the study subjects and the participating cardiologists.

Conclusion

The system comprising of a wrist device and a data management service was validated to be suitable for use in patient monitoring and in the detection of AF in an ambulatory setting.Clinical Trial Registration: ClinicalTrials.gov/, NCT05008601.

A prospective study on the association between atrial fibrillation and blood pressure in an elderly Chinese population

BACKGROUND

Intensive blood pressure (BP) lowering in patients with hypertension has been associated with a lowered risk of atrial fibrillation (AF). It is still uncertain what is the optimal BP levels to prevent AF in the general elderly population. In the present prospective study, we investigated the association between incident AF and BP in an elderly Chinese population.

METHODS AND FINDINGS

Elderly (≥65 years) residents were recruited from 6 communities in Shanghai. 9019 participants who did not have AF at baseline and had at least one ECG recording during follow-up were included in the present analysis. During a median of 3.5 years follow-up, the overall incidence rate of AF was 5.6 per 1000 person-years (n = 178). Systolic BP was associated with increased AF risk (age- and sex-adjusted hazard ratio [HR] per 20-mmHg increase for systolic BP 1.21, 95% CI 1.04-1.39, P = 0.01), but risk estimate was attenuated after adjustment for common AF risk factors. In categorical analyses, statistical significance was achieved for HR relative to optimal BP only in stage 2 or 3 systolic and diastolic hypertension (multivariate-adjusted HR 1.76, 95% CI 1.00-3.08, P = 0.05). The association between AF incidence and BP status tended to be stronger in the absence than presence of a history of cardiovascular disease at baseline (P for interaction = 0.06).

CONCLUSION

In this Chinese population of 65 years and older, linear increases in systolic and diastolic BP were not independently associated with increased risk of AF, and only exposure to stage 2 or 3 hypertension carries a higher risk of AF.

Association of lifestyle with deep learning predicted electrocardiographic age

Background

People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear.

Methods

This study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Δage. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Δage, and the models were adjusted for sex and chronological age.

Results

This study included 44,094 individuals (mean age 64 ± 8, 51.4% females). A significant correlation was observed between predicted biological age and chronological age (correlation coefficient = 0.54, P < 0.001) and the mean Δage (absolute error of biological age and chronological age) was 9.8 ± 7.4 years. Δage was significantly associated with all of the four lifestyle factors, with the effect size ranging from 0.41 ± 0.11 for the healthy diet to 2.37 ± 0.30 for non-smoking. Compared with an ideal lifestyle, an unfavorable lifestyle was associated with an average of 2.50 ± 0.29 years of older predicted ECG-age.

Conclusion

In this large contemporary population, a strong association was observed between all four studied healthy lifestyle factors and deaccelerated aging. Our study underscores the importance of a healthy lifestyle to reduce the burden of aging-related diseases.

Clinical Validation of a Smartphone-based Handheld ECG Device: A Validation Study

BACKGROUND

Remote cardiac monitoring and screening have already become an integral telemedicine component. The wide usage of several different wireless electrocardiography (ECG) devices warrants a validation study on their accuracy and reliability.

METHODS

Totally, 300 inpatients with the Nabz Hooshmand-1 handheld ECG device and the GE MAC 1200 ECG system (as the reference) were studied to check the accuracy of the devices in 1 and 6-limb lead performance. Simultaneous 10-second resting ECGs were assessed for the most common ECG parameters in lead I. Afterward, 6-lead ECGs (limb leads), were performed immediately and studied for their morphologies.

RESULTS

Of the 300 patients, 297 had acceptable ECG quality in both devices for simultaneous lead I ECGs. The ECGs were inspected on-screen by a cardiologist for their rhythms, rates, axes, numbers, morphologies of premature atrial and ventricular beats, morphologies and amplitudes of PQRST waves, P-wave durations, QRS-wave durations, P-R intervals, and QT intervals. No significant differences were detected between the devices, and no major abnormalities were missed. Six-limb lead ECGs were obtained in 284 patients, of whom 281 had acceptable quality in ECGs by both devices. The morphology matching evaluation of the ECGs demonstrated an overall 98% compatibility rate, with the highest compatibility in lead I and the lowest in lead augmented vector foot.

CONCLUSIONS

The diagnosis of critical pathological rhythms, including atrial fibrillation and high-grade atrioventricular node block, was not missed by the Nabz Hooshmand-1 and GE MAC 1200 ECG devices. Accordingly, rhythm detection as the primary purpose of handheld ECG devices was highly accurate. Both devices had acceptable sensitivity to diagnose long P-R and long and short QT intervals. Although the modern technology of smartphones and the physical inability for the 6-limb mode might cause old patients difficulty in utilizing such devices, their use for screening and follow-up is safe.

Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG

OBJECTIVES

Sleep apnea is the most common sleep disorder that leads to serious health complications if not treated early. Forecasting apnea occurrence ahead in time provides the opportunity to take appropriate actions to control and manage it.

METHODS

A novel framework for forecasting the occurrence of apnea from single-lead electrocardiogram (ECG) based on deep recurrent neural networks is proposed. ECG R-peak amplitudes and R-R intervals are extracted and aligned using power spectral analysis, and recurrent deep learning models are developed to extract the most predictive ECG features and forecast the occurrence of apnea.

RESULTS

The performance of the proposed approach was validated in forecasting apnea events up to five minutes in future on a dataset of 70 sleep recordings. A forecasting accuracy of up to 94.95% was achieved which was higher than the performance of conventional multilayer perceptron (p < 0.05) and other state-of-the-art techniques.

CONCLUSIONS

The proposed deep learning approach was successful in forecasting the occurrence of sleep apnea from single-lead ECG. It can therefore be adopted in wearable sleep monitors for the management of sleep apnea. Our developed algorithms are publicly available on GitHub.

Premature Beats Rejection Strategy on Paroxysmal Atrial Fibrillation Detection

Paroxysmal atrial fibrillation (PAF) may related to the risk of thromboembolism and is the most common cardiac risk factor of cryptogenic stroke (CS). Due to its paroxysmal characteristics, it is usually diagnosed by continuous long-term ECG. Patients with paroxysmal atrial fibrillation usually have premature beats at the same time which is easy to be confused with the rhythm of atrial fibrillation. Therefore, in this article, we designed a screening algorithm for single premature beat, multi premature beats, bigeminy and trigeminy premature beats, according to their rhythm characteristics to reduce false detection caused by premature beats during the PAF detection process. The proposed elimination method was verified on ECG segments with different types of premature beats, and tested on long-term ECG data of PAF patients. ECG segments of different kinds of premature beats were selected from MIT Atrial Fibrillation database (MIT-AFDB), MIT-BIH Arrhythmia database (MIT-AR) and wearable ECG data from the China Physiological Signal Challenge 2021 (CPSC 2021). The proposed method can effectively eliminate single premature beat segments with 99.5% accuracy, and it also can eliminate more than 95% of ECG segments with other types of premature beats. We designed PAF-score as a new index to evaluate the accuracy of detection, and we also calculate the misjudged and missed segments to comprehensively evaluate the PAF detection algorithm. The proposed method get a PAF-score of 0.912 on MIT-AFDB. The proposed method also has the potential to implant low computing power wearable devices for real-time analysis.

Machine learning in the detection and management of atrial fibrillation

Machine learning has immense novel but also disruptive potential for medicine. Numerous applications have already been suggested and evaluated concerning cardiovascular diseases. One important aspect is the detection and management of potentially thrombogenic arrhythmias such as atrial fibrillation. While atrial fibrillation is the most common arrhythmia with a lifetime risk of one in three persons and an increased risk of thromboembolic complications such as stroke, many atrial fibrillation episodes are asymptomatic and a first diagnosis is oftentimes only reached after an embolic event. Therefore, screening for atrial fibrillation represents an important part of clinical practice. Novel technologies such as machine learning have the potential to substantially improve patient care and clinical outcomes. Additionally, machine learning applications may aid cardiologists in the management of patients with already diagnosed atrial fibrillation, for example, by identifying patients at a high risk of recurrence after catheter ablation. We summarize the current state of evidence concerning machine learning and, in particular, artificial neural networks in the detection and management of atrial fibrillation and describe possible future areas of development as well as pitfalls.

NICE atrial fibrillation guideline snubs wearable technology: a missed opportunity?

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a growing public health epidemic. In the UK, over 1.3 million people have a diagnosis of AF and an estimated 400,000 remain undiagnosed. AF-related strokes account for a quarter of all strokes and, as AF episodes are often asymptomatic, are still often the first manifestation of AF. Early diagnosis and initiation of oral anticoagulation, where appropriate, may prevent some of these thromboembolic strokes. Public Health England is committed to decrease the incidence of AF-related strokes and has sponsored initiatives aimed at improving AF detection by promoting the uptake of wearable technologies. However, the National Institute for Health and Care Excellence (NICE) has not recommended wearable technology in their recent AF diagnosis and management guidelines (NG196). Diagnostic accuracy of single-lead electrocardiography (ECG) generated by the latest iteration of wearable devices is excellent and, in many cases, superior to general practitioner interpretation of the 12-lead ECG. High-quality ECG from wearable devices that unequivocally shows AF can expedite AF detection. Otherwise, there is a real risk of delaying AF diagnosis with the potential of devastating consequences for patients and their families.

Lessons from a multicenter clinical trial with an approved wearable electrocardiogram: issues and practical considerations

Although wearable electrocardiograms (ECGs) are being increasingly applied in clinical settings, validation methods have not been standardized. As an exploratory evaluation, we performed a multicenter clinical trial implementing an approved wearable patch ECG. Healthy male adults were enrolled in 2 study centers. The approved ECGs were deployed for 6 hours, and pulse rates were measured independently with conventional pulse oximetry at selected time points for correlation analyses. The transmission status of the data was evaluated by heart rates and classified into valid, invalid, and missing. A total of 55 subjects (40 in center 1 and 15 in center 2) completed the study. Overall, 77.40% of heart rates were within the valid range. Invalid and missing data accounted for 1.42% and 21.23%, respectively. There were significant differences in valid and missing data between centers. The proportion of missing data in center 1 (24.77%) was more than twice center 2 (11.77%). Heart rates measured by the wearable ECG and conventional pulse oximetry showed a poor correlation (intraclass correlation coefficient = 0.0454). In conclusion, we evaluated the multicenter feasibility of implementing wearable ECGs. The results suggest that systems to mitigate multicenter discrepancies and remove artifacts should be implemented prior to performing a clinical trial.

Rate control strategies for atrial fibrillation

Atrial fibrillation (AF) is one of the main cardiac arrhythmias associated with higher risk of cardiovascular morbidity and mortality. AF can cause adverse symptoms and reduced quality of life. One of the strategies for the management of AF is rate control, which can modulate ventricle rate, alleviate adverse associated symptoms and improve the quality of life. As primary management of AF through rate control or rhythm is a topic under debate, the purpose of this review is to explore the rationale for the rate control approach in managing AF by considering the guidelines, recommendations and determinants for the choice of rate control drugs, including beta blockers, digoxin and non- dihydropyridine calcium channel blockers for patients with AF and other comorbidities and atrioventricular nodal ablation and pacing. Despite the limitations of rate control treatment, which may not be effective in preventing disease progression or in reducing symptoms in highly symptomatic patients, it is widely used for almost all patients with atrial fibrillation. Although rate control is one of the first line management of all patient with atrial fibrillation, several issues remain debateable.

Manual QT interval measurement with a smartphone-operated single-lead ECG versus 12-lead ECG: a within-patient diagnostic validation study in primary care

OBJECTIVE

To determine the accuracy of QT measurement in a smartphone-operated, single-lead ECG (1L-ECG) device (AliveCor KardiaMobile 1L).

DESIGN

Cross-sectional, within-patient diagnostic validation study.

SETTING/PARTICIPANTS

Patients underwent a 12-lead ECG (12L-ECG) for any non-acute indication in primary care, April 2017-July 2018.

INTERVENTION

Simultaneous recording of 1L-ECGs and 12L-ECGs with blinded manual QT assessment. OUTCOMES OF INTEREST: (1) Difference in QT interval in milliseconds (ms) between the devices; (2) measurement agreement between the devices (excellent agreement <20 ms and clinically acceptable agreement <40 ms absolute difference); (3) sensitivity and specificity for detection of extreme QTc (short (≤340 ms) or long (≥480 ms)), on 1L-ECGs versus 12L-ECGs as reference standard. In case of significant discrepancy between lead I/II of 12L-ECGs and 1L-ECGs, we developed a correction tool by adding the difference between QT measurements of 12L-ECG and 1L-ECGs.

RESULTS

250 ECGs of 125 patients were included. The mean QTc interval, using Bazett's formula (QTcB), was 393±25 ms (mean±SD) in 1L-ECGs and 392±27 ms in lead I of 12L-ECGs, a mean difference of 1±21 ms, which was not statistically different (paired t-test (p=0.51) and Bland Altman method (p=0.23)). In terms of agreement between 1L-ECGs and lead I, QTcB had excellent agreement in 66.9% and clinically acceptable agreement in 93.4% of observations. The sensitivity and specificity of detecting extreme QTc were 0% and 99.2%, respectively. The comparison of 1L-ECG QTcB with lead II of 12L-ECGs showed a significant difference (p=<0.01), but when using a correction factor (+9 ms) this difference was cancelled (paired t-test (p=0.43) or Bland Altman test (p=0.57)). Moreover, it led to improved rates of excellent (71.3%) and clinically acceptable (94.3%) agreement.

CONCLUSION

Smartphone-operated 1L-ECGs can be used to accurately measure the QTc interval compared with simultaneously obtained 12L-ECGs in a primary care population. This may provide an opportunity for monitoring the effects of potential QTc-prolonging medications.

Predictive performance and impact of algorithms in remote monitoring of chronic conditions: A systematic review and meta-analysis

BACKGROUND

The use of telehealth interventions, such as the remote monitoring of patient clinical data (e.g. blood pressure, blood glucose, heart rate, medication use), has been proposed as a strategy to better manage chronic conditions and to reduce the impact on patients and healthcare systems. The use of algorithms for data acquisition, analysis, transmission, communication and visualisation are now common in remote patient monitoring. However, their use and impact on chronic disease management has not been systematically investigated.

OBJECTIVES

To investigate the use, impact, and performance of remote monitoring algorithms across various types of chronic conditions.

METHODS

A literature search of MEDLINE complete, CINHAL complete, and EMBASE was performed using search terms relating to the concepts of remote monitoring, chronic conditions, and data processing algorithms. Comparable outcomes from studies describing the impact on process measures and clinical and patient-reported outcomes were pooled for a summary effect and meta-analyses. A comparison of studies reporting the predictive performance of algorithms was also conducted using the Youden Index.

RESULTS

A total of 89 articles were included in the review. There was no evidence of a positive impact on healthcare utilisation [OR 1.09 (0.90 to 1.31); P = .35] and mortality [OR 0.83 (0.63 to 1.10); P = .208], but there was a positive effect on generic health status [SDM 0.2912 (0.06 to 0.51); P = .010] and diabetes control [SDM -0.53 (-0.74 to -0.33); P < .001; I² = 15.71] (with two of the three diabetes studies being identified as having a high risk of bias). While the majority of impact studies made use of heuristic threshold-based algorithms (n = 27,87%), most performance studies (n = 36, 62%) analysed non-sequential machine learning methods. There was considerable variance in the quality, sample size and performance amongst these studies. Overall, algorithms involved in diagnosis (n = 22, 47%) had superior performance to those involved in predicting a future event (n = 25, 53%). Detection of arrythmia and ischaemia utilising ECG data showed particularly promising results.

CONCLUSION

The performance of data processing algorithms for the diagnosis of a current condition, particularly those related to the detection of arrythmia and ischaemia, is promising. However, there appears to exist minimal testing in experimental studies, with only two included impact studies citing a performance study as support for the intervention algorithm used. Because of the disconnect between performance and impact studies, there is currently limited evidence of the effect of integrating advanced inference algorithms in remote monitoring interventions. If the field of remote patient monitoring is to progress, future impact studies should address this disconnect by evaluating high performance validated algorithms in robust clinical trials.

A multi-point heart rate monitoring using a soft wearable system based on fiber optic technology

Early diagnosis can be crucial to limit both the mortality and economic burden of cardiovascular diseases. Recent developments have focused on the continuous monitoring of cardiac activity for a prompt diagnosis. Nowadays, wearable devices are gaining broad interest for a continuous monitoring of the heart rate (HR). One of the most promising methods to estimate HR is the seismocardiography (SCG) which allows to record the thoracic vibrations with high non-invasiveness in out-of-laboratory settings. Despite significant progress on SCG, the current state-of-the-art lacks both information on standardized sensor positioning and optimization of wearables design. Here, we introduce a soft wearable system (SWS), whose novel design, based on a soft polymer matrix embedding an array of fiber Bragg gratings, provides a good adhesion to the body and enables the simultaneous recording of SCG signals from multiple measuring sites. The feasibility assessment on healthy volunteers revealed that the SWS is a suitable wearable solution for HR monitoring and its performance in HR estimation is strongly influenced by sensor positioning and improved by a multi-sensor configuration. These promising characteristics open the possibility of using the SWS in monitoring patients with cardiac pathologies in clinical (e.g., during cardiac magnetic resonance procedures) and everyday life settings.

Mobile Electrocardiogram Monitoring and Health-Related Quality of Life in Patients With Atrial Fibrillation: Findings From the iPhone Helping Evaluate Atrial Fibrillation Rhythm Through Technology (iHEART) Study

BACKGROUND

Atrial fibrillation (AF) is associated with high recurrence rates and poor health-related quality of life (HRQOL) but few effective interventions to improve HRQOL exist.

OBJECTIVE

The aim of this study was to examine the impact of the "iPhone Helping Evaluate Atrial Fibrillation Rhythm through Technology" (iHEART) intervention on HRQOL in patients with AF.

METHODS

We randomized English- and Spanish-speaking adult patients with AF to receive either the iHEART intervention or usual care for 6 months. The iHEART intervention used smartphone-based electrocardiogram monitoring and motivational text messages. Three instruments were used to measure HRQOL: the Atrial Fibrillation Effect on Quality of Life (AFEQT), the 36-item Short-Form Health survey, and the EuroQol-5D. We used linear mixed models to compare the effect of the iHEART intervention on HRQOL, quality-adjusted life-years, and AF symptom severity.

RESULTS

A total of 238 participants were randomized to the iHEART intervention (n = 115) or usual care (n = 123). Of the participants, 77% were men and 76% were white. More than half (55%) had an AF recurrence. Both arms had improved scores from baseline to follow-up for AFEQT and AF symptom severity scores. The global AFEQT score improved 18.5 and 11.2 points in the intervention and control arms, respectively (P < .05). There were no statistically significant differences in HRQOL, quality-adjusted life-years, or AF symptom severity between groups.

CONCLUSIONS

We found clinically meaningful improvements in AF-specific HRQOL and AF symptom severity for both groups. Additional research with longer follow-up should examine the influence of smartphone-based interventions for AF management on HRQOL and address the unique needs of patients diagnosed with different subtypes of AF.

Evaluation of a new portable 1-lead digital cardiac monitor (eKuore) compared with standard base-apex electrocardiography in healthy horses

Recently, the use of smartphone ECG devices has been reported in humans and animals. Nevertheless, as the electrodes of these devices are inseparable, they can create only a precordial reading in veterinary species. Thus, although the smartphone ECG devices are considered valuable as a screening tool for the detection of some common arrhythmias, they are not always a reliable method for the measurement of the duration of the electrical deflections. The objectives of this study were to evaluate the feasibility of a novel smartphone ECG device, to report the readings obtained recorded simultaneously with a reference ECG system, and to compare the heart rate and duration of cardiac deflections obtained with the two methods. A total of 28 healthy mares of different breeds and age were included in this study and ECG recordings were obtained simultaneously with a reference ECG telemetry system with surface electrodes attached to the skin with alligator clips using a standard base-apex system and a smartphone ECG device with electrodes positioned alternatively with a standard and a modified base apex derivation. All the recordings obtained were considered acceptable for interpretation. An excellent agreement was found between the two methods for the evaluation of heart rate and polarity of cardiac deflections. No differences regarding number, duration and percentage of artifacts were found. This technology could become a valid diagnostic tool in the cardiological assessment of horses, in particular on the field.

Mobile health applications for the detection of atrial fibrillation: a systematic review

AIMS

Atrial fibrillation (AF) is the most common sustained arrhythmia and an important risk factor for stroke and heart failure. We aimed to conduct a systematic review of the literature and summarize the performance of mobile health (mHealth) devices in diagnosing and screening for AF.

METHODS AND RESULTS

We conducted a systematic search of MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Forty-three studies met the inclusion criteria and were divided into two groups: 28 studies aimed at validating smart devices for AF diagnosis, and 15 studies used smart devices to screen for AF. Evaluated technologies included smartphones, with photoplethysmographic (PPG) pulse waveform measurement or accelerometer sensors, smartbands, external electrodes that can provide a smartphone single-lead electrocardiogram (iECG), such as AliveCor, Zenicor and MyDiagnostick, and earlobe monitor. The accuracy of these devices depended on the technology and the population, AliveCor and smartphone PPG sensors being the most frequent systems analysed. The iECG provided by AliveCor demonstrated a sensitivity and specificity between 66.7% and 98.5% and 99.4% and 99.0%, respectively. The PPG sensors detected AF with a sensitivity of 85.0-100% and a specificity of 93.5-99.0%. The incidence of newly diagnosed arrhythmia ranged from 0.12% in a healthy population to 8% among hospitalized patients.

CONCLUSION

Although the evidence for clinical effectiveness is limited, these devices may be useful in detecting AF. While mHealth is growing in popularity, its clinical, economic, and policy implications merit further investigation. More head-to-head comparisons between mHealth and medical devices are needed to establish their comparative effectiveness.

Development and use of mobile messaging for individuals with musculoskeletal pain conditions: a scoping review protocol

INTRODUCTION

Previous reviews of mobile messaging for individuals with musculoskeletal pain have shown positive effects on pain and disability. However, the configuration of digital content, method of presentation and interaction, dose and frequency needed for optimal results remain unclear. Patient preferences concerning such systems are also unclear. Addressing these knowledge gaps, incorporating evidence from both experimental and observational studies, may be useful to understand the extent of the relevant literature, and to influence the design and outcomes of future messaging systems. We aim to map information that could be influential in the design of future mobile messaging systems for individuals with musculoskeletal pain conditions, and to summarise the findings of efficacy, effectiveness, and economics derived from both experimental and observational studies.

METHODS AND ANALYSIS

We will include studies describing the development and/or use of mobile messaging to support adults (≥18 years) with acute or chronic musculoskeletal pain. We will exclude digital health studies that lack a mobile messaging component, or those targeted at other health conditions unrelated to the bones, muscles and connective tissues, or involving surgical or patients with cancer, or studies involving solely healthy individuals. Our sources of information will be online databases and reference lists of relevant papers. We will include papers published in English in the last 10 years. Two pairs of independent reviewers will screen, select and extract the data, with any disagreements mediated by a third reviewer. We will report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews checklist. We will synthesise the findings in a tabular format and provide a descriptive summary.

ETHICS AND DISSEMINATION

Formal ethical approval is not required. We will disseminate the findings through publication in a peer-reviewed journal, relevant conferences, and relevant consumer forums.

TRIAL REGISTRATION

Open Science Framework https://osf.io/8mzya; DOI: 10.17605/OSF.IO/8MZYA.

Remote Monitoring of the QT Interval and Emerging Indications for Arrhythmia Prevention

QT interval prolongation is a marker of increased risk for life-threatening arrhythmias, and needs to be promptly recognized. Many effective drugs, however, prolong QTc (QT interval corrected for heart rate) in genetically predisposed subjects. The possibility of remote monitoring and QTc measurement for up to 2 weeks, continuously providing physicians with real time data, allows life-saving interventions or changes in drug therapy. This applies especially to patients with the long QT syndrome and to those taking drugs blocking the IKr current and prolonging the QT interval. Patch monitors recording ECG traces continuously are available and contribute to effective arrhythmic prevention.

Returning Cardiac Rhythm Data to Patients: Opportunities and Challenges

Spurred by federal legislation, professional organizations, and patients themselves, patient access to data from electronic cardiac devices is increasingly transparent. Patients can collect data through consumer devices and access data traditionally shared only with health care providers. These data may improve screening, self-management, and shared decision-making for cardiac arrhythmias, but challenges remain, including patient comprehension, communication with providers, and sustained engagement. Ways to address these challenges include leveraging visualizations that support comprehension, involving patients in designing and developing patient-facing digital tools, and establishing clear practices and goals for data exchange with health care providers.

Portable single-lead electrocardiogram device is accurate for QTc evaluation in hospitalized patients

Background

Many commonly used drugs can prolong the QTc interval (QTc), which can lead to potentially life-threatening arrhythmias. In the current era of the COVID-19 pandemic, it is worth mentioning that the disease itself and several drugs used for its treatment have been associated with QTc prolongation.

Objective

To evaluate the agreement and clinical precision of a portable single-lead electrocardiogram (ECG) device to measure the QTc interval compared to the standard 12-lead ECG.

Methods

In sequential tests, QTc of ECG recordings obtained with the KardiaMobile (KM-1L) device (AliveCor, San Francisco, CA) were compared to QTc obtained with conventional 12-lead ECG. Agreement was evaluated using Bland-Altman plots and Lin’s concordance coefficient. Consistency between the 2 devices in determining QTc prolongation (QTc ≥470 ms in males or ≥480 ms in females) was evaluated with kappa statistics.

Results

A total of 128 patients with a presumed or confirmed diagnosis of COVID-19 admitted to a university hospital were included. QTc intervals measured with KM-1L were similar to QTc measured with conventional ECG (442.45 ± 40.5 vs 441.65 ± 40.3 ms, P = .15). Bland–Altman analysis showed no significant difference in QTc values (average difference of -0.797, 95% limits of agreement:-13.179; 11.585). Lin’s concordance coefficient showed an excellent agreement (0.988, P < .001). Concordance between the 2 devices for determining QTc prolongation was excellent (kappa >0.90).

Conclusion

ECG recordings obtained with KM-1L allow an accurate QTc interval assessment. Considering its simplicity of use, this approach has advantages over conventional ECG and can provide an alternative for the evaluation of QTc in hospitalized patients, during the current time of the COVID-19 pandemic and beyond.

Ambulatory monitoring promises equitable personalized healthcare delivery in underrepresented patients

The pandemic has brought to everybody's attention the apparent need of remote monitoring, highlighting hitherto unseen challenges in healthcare. Today, mobile monitoring and real-time data collection, processing and decision-making, can drastically improve the cardiorespiratory-haemodynamic health diagnosis and care, not only in the rural communities, but urban ones with limited healthcare access as well. Disparities in socioeconomic status and geographic variances resulting in regional inequity in access to healthcare delivery, and significant differences in mortality rates between rural and urban communities have been a growing concern. Evolution of wireless devices and smartphones has initiated a new era in medicine. Mobile health technologies have a promising role in equitable delivery of personalized medicine and are becoming essential components in the delivery of healthcare to patients with limited access to in-hospital services. Yet, the utility of portable health monitoring devices has been suboptimal due to the lack of user-friendly and computationally efficient physiological data collection and analysis platforms. We present a comprehensive review of the current cardiac, pulmonary, and haemodynamic telemonitoring technologies. We also propose a novel low-cost smartphone-based system capable of providing complete cardiorespiratory assessment using a single platform for arrhythmia prediction along with detection of underlying ischaemia and sleep apnoea; we believe this system holds significant potential in aiding the diagnosis and treatment of cardiorespiratory diseases, particularly in underserved populations.

Kardia Mobile and ISTEL HR applicability in clinical practice: a comparison of Kardia Mobile, ISTEL HR, and standard 12-lead electrocardiogram records in 98 consecutive patients of a tertiary cardiovascular care centre

Aims

Mobile, portable ECG-recorders allow the assessment of heart rhythm in out-of-hospital conditions and may prove useful for monitoring patients with cardiovascular diseases. However, the effectiveness of these portable devices has not been tested in everyday practice.

Methods and results

A group of 98 consecutive cardiology patients [62 males (63%), mean age 69 ± 12.9 years] were included in an academic care centre. For each patient, a standard 12-lead electrocardiogram (SE), as well as a Kardia Mobile 6L (KM) and Istel (IS) HR-2000 ECG were performed. Two groups of experienced physicians analysed obtained recordings. After analysing ECG tracings from SE, KM, and IS, quality was marked as good in 82%, 80%, and 72% of patients, respectively (P < 0.001). There were no significant differences between devices in terms of detecting sinus rhythm [SE (60%, n = 59), KM (58%, n = 56), and IS (61%, n = 60); SE vs. KM P = 0.53; SE vs. IS P = 0.76) and atrial fibrillation [SE (22%, n = 22), KM (22%, n = 21), and IS (18%, n = 18); (SE vs. KM P = 0.65; SE vs. IS = 0.1)]. KM had a sensitivity of 88.1% and a specificity of 89.7% for diagnosing sinus rhythm. IS showed 91.5% and 84.6% sensitivity and specificity, respectively. The sensitivity of KM in detecting atrial fibrillation was higher than IS (86.4% vs. 77.3%), but their specificity was comparable (97.4% vs. 98.7%).

Conclusion

Novel, portable devices are useful in showing sinus rhythm and detecting atrial fibrillation in clinical practice. However, ECG measurements concerning conduction and repolarization should be clarified with a standard 12-lead electrocardiogram.

Arrhythmia in an athlete diagnosed by smartphone electrocardiogram: a case report

Background

This is the first case report demonstrating the use of a smartphone device, enabling the diagnosis of an arrhythmia in the sports cardiology literature.

Case summary

A 17-year-old semi-professional rugby player presented with recurrent episodes of palpitations terminated by vagal manoeuvres. The rugby player’s resting 12-lead electrocardiogram (ECG), echocardiogram, and exercise stress test were normal. Due to his suggestive history and an ECG trace from a smartphone device, demonstrating a narrow complex tachycardia, an electrophysiological study was arranged. The study demonstrated a slow-fast atrioventricular nodal re-entrant tachycardia which was successfully ablated.

Discussion

The ambulatory use of a smartphone ECG device assisted in the timely diagnosis and management of an undiagnosed paroxysmal arrhythmia in a rugby player. This resulted in an expedited return to play.

Diagnostic Accuracy of Ambulatory Devices in Detecting Atrial Fibrillation: Systematic Review and Meta-analysis

BACKGROUND

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide. Early diagnosis of AF is crucial for preventing AF-related morbidity, mortality, and economic burden, yet the detection of the disease remains challenging. The 12-lead electrocardiogram (ECG) is the gold standard for the diagnosis of AF. Because of technological advances, ambulatory devices may serve as convenient screening tools for AF.

OBJECTIVE

The objective of this review was to investigate the diagnostic accuracy of 2 relatively new technologies used in ambulatory devices, non-12-lead ECG and photoplethysmography (PPG), in detecting AF. We performed a meta-analysis to evaluate the diagnostic accuracy of non-12-lead ECG and PPG compared to the reference standard, 12-lead ECG. We also conducted a subgroup analysis to assess the impact of study design and participant recruitment on diagnostic accuracy.

METHODS

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. MEDLINE and EMBASE were systematically searched for articles published from January 1, 2015 to January 23, 2021. A bivariate model was used to pool estimates of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the summary receiver operating curve (SROC) as the main diagnostic measures. Study quality was evaluated using the quality assessment of diagnostic accuracy studies (QUADAS-2) tool.

RESULTS

Our search resulted in 16 studies using either non-12-lead ECG or PPG for detecting AF, comprising 3217 participants and 7623 assessments. The pooled estimates of sensitivity, specificity, PLR, NLR, and diagnostic odds ratio for the detection of AF were 89.7% (95% CI 83.2%-93.9%), 95.7% (95% CI 92.0%-97.7%), 20.64 (95% CI 10.10-42.15), 0.11 (95% CI 0.06-0.19), and 224.75 (95% CI 70.10-720.56), respectively, for the automatic interpretation of non-12-lead ECG measurements and 94.7% (95% CI 93.3%-95.8%), 97.6% (95% CI 94.5%-99.0%), 35.51 (95% CI 18.19-69.31), 0.05 (95% CI 0.04-0.07), and 730.79 (95% CI 309.33-1726.49), respectively, for the automatic interpretation of PPG measurements.

CONCLUSIONS

Both non-12-lead ECG and PPG offered high diagnostic accuracies for AF. Detection employing automatic analysis techniques may serve as a useful preliminary screening tool before administering a gold standard test, which generally requires competent physician analyses. Subgroup analysis indicated variations of sensitivity and specificity between studies that recruited low-risk and high-risk populations, warranting future validity tests in the general population.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42020179937; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=179937.

Comparison between a 6‑lead smartphone ECG and 12‑lead ECG in athletes

Athletes sometimes experience transient arrhythmias during intense exercise, which may be difficult to capture with traditional Holter monitors. New and highly portable technology, such as smartphone electrocardiogram (ECG) devices, may be useful in documenting and contribute to diagnosis of exercise-induced arrhythmias. There are little data available regarding the new Kardia 6 lead device (6L) and no data regarding its use in athletic populations. In this short communication, we present pilot data from 30 healthy athletes who underwent a 12‑lead ECG and subsequent 6L reading. Our pilot data show relatively high levels of agreement for QTc and PR interval and QRS duration, with the 6L readings slightly but significantly shorter on average.

Evaluation of general practitioners' single-lead electrocardiogram interpretation skills: a case-vignette study

BACKGROUND

Handheld single-lead electrocardiograms (1L-ECG) present a welcome addition to the diagnostic arsenal of general practitioners (GPs). However, little is known about GPs' 1L-ECG interpretation skills, and thus its reliability in real-world practice.

OBJECTIVE

To determine the diagnostic accuracy of GPs in diagnosing atrial fibrillation or flutter (AF/Afl) based on 1L-ECGs, with and without the aid of automatic algorithm interpretation, as well as other relevant ECG abnormalities.

METHODS

We invited 2239 Dutch GPs for an online case-vignette study. GPs were asked to interpret four 1L-ECGs, randomly drawn from a pool of 80 case-vignettes. These vignettes were obtained from a primary care study that used smartphone-operated 1L-ECG recordings using the AliveCor KardiaMobile. Interpretation of all 1L-ECGs by a panel of cardiologists was used as reference standard.

RESULTS

A total of 457 (20.4%) GPs responded and interpreted a total of 1613 1L-ECGs. Sensitivity and specificity for AF/Afl (prevalence 13%) were 92.5% (95% CI: 82.5-97.0%) and 89.8% (95% CI: 85.5-92.9%), respectively. PPV and NPV for AF/Afl were 45.7% (95% CI: 22.4-70.9%) and 98.8% (95% CI: 97.1-99.5%), respectively. GP interpretation skills did not improve in case-vignettes where the outcome of automatic AF-detection algorithm was provided. In detecting any relevant ECG abnormality (prevalence 22%), sensitivity, specificity, PPV and NPV were 96.3% (95% CI: 92.8-98.2%), 68.8% (95% CI: 62.4-74.6%), 43.9% (95% CI: 27.7-61.5%) and 97.9% (95% CI: 94.9-99.1%), respectively.

CONCLUSIONS

GPs can safely rule out cardiac arrhythmias with 1L-ECGs. However, whenever an abnormality is suspected, confirmation by an expert-reader is warranted.

Scoping Review of Healthcare Literature on Mobile, Wearable, and Textile Sensing Technology for Continuous Monitoring

Remote monitoring of health can reduce frequent hospitalisations, diminishing the burden on the healthcare system and cost to the community. Patient monitoring helps identify symptoms associated with diseases or disease-driven disorders, which makes it an essential element of medical diagnoses, clinical interventions, and rehabilitation treatments for severe medical conditions. This monitoring can be expensive and time-consuming and provide an incomplete picture of the state of the patient. In the last decade, there has been a significant increase in the adoption of mobile and wearable devices, along with the introduction of smart textile solutions that offer the possibility of continuous monitoring. These alternatives fuel a technology shift in healthcare, one that involves the continuous tracking and monitoring of individuals. This scoping review examines how mobile, wearable, and textile sensing technology have been permeating healthcare by offering alternate solutions to challenging issues, such as personalised prescriptions or home-based secondary prevention. To do so, we have selected 222 healthcare literature articles published from 2007 to 2019 and reviewed them following the PRISMA process under the schema of a scoping review framework. Overall, our findings show a recent increase in research on mobile sensing technology to address patient monitoring, reflected by 128 articles published in journals and 19 articles in conference proceedings between 2014 and 2019, which represents 57.65% and 8.55% respectively of all included articles.

Evaluating the use of a mobile device for detection of atrial fibrillation in primary care

A trial fibrillation (AF) increases cardio-embolic stroke risk, yet AF diagnosis and subsequent prophylactic anticoagulant prescription rates are suboptimal globally. This project aimed to increase AF diagnosis and subsequent anticoagulation prescription rates in East Midlands Clinical Commissioning Groups (CCGs). This service improvement evaluation of the East Midlands AF Advance programme investigated the implementation of mobile AF detection devices (Kardia, AliveCor) into primary-care practices within East Midlands CCGs, along with audit tools and clinician upskilling workshops designed to increase AF diagnosis and anticoagulation prescription rates. AF prevalence and prescription data were collected quarterly from July to September (Q3) 2017/18 to April to June/July to September (Q2/3) 2018/19. AF prevalence increased from 1.9% (22,975 diagnoses) in Q3 2017/18 to 2.4% (24,246 diagnoses) in Q2 2018/19 (p=0.026), while the percentage of high-risk AF patients receiving anticoagulants increased from 80.5% in Q3 2017/18 to 86.9% in Q3 2018/19 (p=0.57), surpassing the Public Health England 2019 target of 85%. The East Midlands AF Advance programme increased AF diagnosis and anticoagulation rates, which is expected to be of significant clinical benefit. The mobile AF detection devices provide a more practical alternative to traditional 12-lead electrocardiograms (ECGs) and should be incorporated into routine clinical practice for opportunistic AF detection, in combination with medication reviews to increase anticoagulant prescription.

Validating and implementing cardiac telemetry for continuous QTc monitoring: A novel approach to increase healthcare personnel safety during the COVID-19 pandemic

BACKGROUND

Minimizing direct patient contact among healthcare personnel is crucial for mitigating infectious risk during the coronavirus disease 2019 (COVID-19) pandemic. The use of remote cardiac telemetry as an alternative to 12‑lead electrocardiography (ECG) for continuous QTc monitoring may facilitate this strategy, but its application has not yet been validated or implemented.

METHODS

In the validation component of this two-part prospective cohort study, a total of 65 hospitalized patients with simultaneous ECG and telemetry were identified. QTc obtained via remote telemetry as measured by 3 independent, blinded operators were compared with ECG as assessed by 2 board-certified electrophysiologists as the gold-standard. Pearson correlation coefficients were calculated to measure the strength of linear correlation between the two methods. In a separate cohort comprised of 68 COVID-19 patients treated with combined hydroxychloroquine and azithromycin, telemetry-based QTc values were compared at serial time points after medication administration using Friedman rank-sum test of repeated measures.

RESULTS

Telemetry-based QTc measurements highly correlated with QTc values derived from ECG, with correlation coefficients of 0.74, 0.79, 0.85 (individual operators), and 0.84 (mean of all operators). Among the COVID-19 cohort, treatment led to a median QTc increase of 15 milliseconds between baseline and following the 9th dose (p = 0.002), with 8 (12%) patients exhibiting an increase in QTc ≥ 60 milliseconds and 4 (6%) developing QTc ≥ 500 milliseconds.

CONCLUSIONS

Cardiac telemetry is a validated clinical tool for QTc monitoring that may serve an expanding role during the COVID-19 pandemic strengthened by its remote and continuous monitoring capability and ubiquitous presence throughout hospitals.

Conduction Disorders: The Value of Surface ECG

PURPOSE OF REVIEW

The purpose of the current mini-review is to describe the importance of surface ECG for the diagnosis of conduction disorder.

METHODS

The MEDLINE/PubMed database was used, with the keywords "ECG" and "conduction disorders"; over the past 10 years. Other documents were included because of their relevance.

MAIN FINDINGS

Data on the anatomy and function of the cardiac electrical system have been described. Conduction disorders including sinus node dysfunction, atrioventricular blocks, intraventricular conduction disorders are exposed as to their epidemiology, etiology, presentation, anatomical site of impaired conduction of the electrical stimulus. The importance of ECG in patients with a cardiac implantable electronic device was also discussed, in addition to future perspectives.

CONCLUSION

Surface ECG allows the diagnosis of atrioventricular and intraventricular conduction disorder and its anatomical block site most of the time, without the need for invasive tests such as electrophysiological study. Dysfunctions of cardiac implantable electronic devices can be diagnosed by ECG, as well as the prediction of response to cardiac resynchronization therapy.

The use of a traditional nonlooping event monitor versus a loan-based program with a smartphone ECG device in the pediatric cardiology clinic

Background

A smartphone-enabled device has been developed that provides a single-lead electrocardiogram using a portable monitor. The increase in direct-to-consumer medical devices may lead to health disparities affecting members of socially disadvantaged populations.

Objective

Here we provide a single center’s experience in the use of this device in a pediatric cardiology clinic using a loan-based program. We also compare it to retrospective data from patients who received a traditional nonlooping event monitor.

Methods

Forty AliveCor Kardia monitor devices were purchased with grant support from the South Carolina TeleHealth Alliance. The devices were provided between June 2018 and August 2019 to patients presenting to the pediatric cardiology clinic who would have otherwise received a nonlooping event monitor. A retrospective chart review was performed for all patients who were given a MicroER nonlooping event monitor between May and December of 2017.

Results

Over a 15-month period, 65 patients were given the smartphone device. A total of 692 tracings were recorded by patients with 9 abnormal recordings. Of the devices expected to be returned, 35 devices have been returned to clinic (54%). Over an 8-month period, 61 patients received the traditional event monitors, accounting for a total of 142 transmissions with 3 abnormal transmissions.

Conclusion

Our results reveal adequate use of the device with reliable tracings and show more frequent utilization of the smartphone-enabled device. Utilization of these devices in a loan-based program may improve access to care with improved methods to ensure return of the devices.

Comparison of Continuous ECG Monitoring by Wearable Patch Device and Conventional Telemonitoring Device

BACKGROUND

Detection of arrhythmias is crucial for the treatment of cardiovascular diseases. However, conventional devices do not provide sufficient diagnostic accuracy while patients should suffer from bothersome diagnostic process. We sought to evaluate diagnostic capability and safety of the new adhesive electrocardiogram (ECG) monitoring device in patients who need ECG monitoring during admission.

METHODS

We enrolled 10 patients who admitted to Seoul National University Bundang Hospital and required continuous ECG monitoring between October 31, 2019 and December 18, 2019. New adhesive ECG monitoring device and conventional ECG monitoring device were simultaneously applied to the patients and maintained for 48 hours. From each patient, 48 pairs of ECG signal were collected and analyzed by two cardiologists independently. Discrepancy of diagnosis and frequency of noise or signal loss were compared between the two devices.

RESULTS

From analyzable ECG data, discrepancy of arrhythmia diagnosis was not observed between the two devices. Noise rate was higher in conventional ECG monitoring device (2.5% vs. 17.3%, P < 0.001) and signal loss was not observed in new adhesive device while there was 9.4% of signal losses in conventional Holter recorder group. The new device was well-tolerated among 48 hours of monitoring period and no adverse event was observed.

CONCLUSION

A newer adhesive ECG monitoring device demonstrated similar diagnostic accuracy compared to conventional ECG monitoring device.

Comparison between smartphone electrocardiography and standard three-lead base apex electrocardiography in healthy horses

BACKGROUND

Cardiac arrhythmias are commonly auscultated during routine physical examinations in horses and determining the underlying electrical abnormality using an ECG is important. The most commonly used device is a three-lead base apex system (Televet), however few practitioners carry this for routine visits. With recognition of the utility of smartphone-based ECGs in humans, dogs and ruminants, the AliveCor single-lead bipolar smartphone-based ECG has gained popularity. The objective of this study was to determine if AliveCor and Televet ECG measurements were comparable in healthy horses using multiple observers.

METHODS

ECGs were performed on 15 healthy horses simultaneously using the AliveCor and Televet.

RESULTS

There was very good to perfect interdevice and interobserver agreement for heart rate and RR interval measurement, and moderate-to-good interdevice and interobserver agreement for detection of non-pathological arrhythmias. Interdevice agreement for measurement of P-wave and QRS duration, QT, PR and T-peak to T-end interval was poor to fair. Interestingly, interobserver agreement for P-wave and QRS duration, QT, PR, and T-peak to T-end interval measurements was fair to good.

CONCLUSION

Overall, the AliveCor is comparable to the Televet for heart rate and RR measurement, and for the detection of non-pathogenic arrhythmias with acceptable agreement between observers.