Diagnostic accuracy of a single-lead portable ECG device for measuring QTc prolongation

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.

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.

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.

Is there a doctor on the plane? A review of in-flight emergencies for the on-board radiologist

In-flight medical emergencies (IFME) are the acute on-service events involving illness or injury to a passenger with the potential for long-term health compromise. With the continuously rising number of flights available, both domestically and internationally, it is conceivable that the number of IFMEs will similarly continue to rise. Although most of these instances are relatively self-limited, the rare instance of a severe occurrence justifies preparation, both from in-flight staff and healthcare providers traveling on these flights. Given these events' sporadic nature and the variable availability of medical support, all physicians need to understand their in-flight ethical and legal capabilities, the available medical supplies, and the most likely etiologies to manage such situations successfully. Most radiologists rarely utilize the hands-on, clinical skills developed in medical school or internship for emergencies beyond allergic contrast reactions. Therefore, they may not be adept in caring for patients during an IFME. As such, we present a thorough overview and literature review for the radiologist regarding the management of various acute IFMEs, with consideration for ethical and legal precedence and a review of medical equipment available on-board.

Remote Cardiac Safety Monitoring through the Lens of the FDA Biomarker Qualification Evidentiary Criteria Framework: A Case Study Analysis

Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.

An Evaluation of Biometric Monitoring Technologies for Vital Signs in the Era of COVID-19

The novel coronavirus disease 2019 (COVID-19) global pandemic has shifted how many patients receive outpatient care. Telehealth and remote monitoring have become more prevalent, and measurements taken in a patient's home using biometric monitoring technologies (BioMeTs) offer convenient opportunities to collect vital sign data. Healthcare providers may lack prior experience using BioMeTs in remote patient care, and, therefore, may be unfamiliar with the many versions of BioMeTs, novel data collection protocols, and context of the values collected. To make informed patient care decisions based on the biometric data collected remotely, it is important to understand the engineering solutions embedded in the products, data collection protocols, form factors (physical size and shape), data quality considerations, and availability of validation information. This article provides an overview of BioMeTs available for collecting vital signs (temperature, heart rate, blood pressure, oxygen saturation, and respiratory rate) and discusses the strengths and limitations of continuous monitoring. We provide considerations for remote data collection and sources of validation information to guide BioMeT use in the era of COVID-19 and beyond.

QT interval measurement with portable device during COVID-19 outbreak

Coronavirus Disease 2019 continues to spread and to date, no definitive treatment is available. Overcrowded and under-resourced healthcare centres have had to design different strategies to treat these patients, what includes the control of the electrocardiogram (ECG), as some drugs that have been used to treat this disease may prolong the QT interval as a side effect. During the COVID-19 outbreak, we designed a protocol for monitoring the QT interval using a portable device with Bluetooth connectivity. After a validation study with 50 patients, we found a very good correlation between the QT interval measured both with this device and with the conventional body surface ECG. In this article, we provide a brief overview of the protocol and then analyse the QT changes observed in a group of patients during their hospitalization and treatment for SARS-CoV-2 infection. 81 patients with confirmed SARS-CoV-2 infection were enrolled in the protocol (age 63.4 SD 17.2 years; 70.3% men), while being treated with lopinavir/ritonavir, azithromycin and hydroxychloroquine, both individually or combined. Ten patients developed long drug-related QT interval, and the QT prolongation was statically significant for all treatment schemes. All patients with drug induced QT prolongation corrected the QT interval following the indications of the protocol, and no patients died of arrhythmic causes after its implementation. In our experience, a protocol for the electrocardiographic monitoring of these patients minimizes the risk of iatrogenic QT interval prolongation and consequently reduces sudden death events, and for that purpose, portable devices like the one used in this protocol may constitute a useful tool to minimize the contact with such patients.

Diagnostic accuracy of a single-lead portable ECG device for measuring QTc prolongation

Background

To assess the diagnostic accuracy of a single‐lead portable ECG device for measuring QTc‐intervals in comparison with a standard 12‐lead ECG.

Methods

Adult patients visiting the cardiology outpatient clinic for a 12‐lead recording were also measured with a portable single‐lead ECG recorder (HeartcheckTM). QTc‐intervals were determined by two cardiologists. Perfect agreement was defined as a limit of ≤10 ms between the two measurement methods.

Results

Hundred one ECGs were recorded. QTc‐interval mean differences between the two measurement methods was substantially outside our definition of perfect agreement (‐31.9 [SD±41.3] ms).

Conclusion

In conclusion, the Heartcheck single‐lead ECG device is not accurate for measuring QTc‐intervals.