Device profile of the Coala Heart Monitor for remote monitoring of the heart rhythm: overview of its efficacy (original) (raw)
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Netherlands Heart Journal, 2018
Background In recent years many mobile devices able to record health-related data in ambulatory patients have emerged. However, well-organised programs to incorporate these devices are sparse. Hartwacht Arrhythmia (HA) is such a program, focusing on remote arrhythmia detection using the AliveCor Kardia Mobile (KM) and its algorithm. Objectives The aim of this study was to assess the benefit of the KM device and its algorithm in detecting cardiac arrhythmias in a real-world cohort of ambulatory patients. Methods All KM ECGs recorded in the HA program between January 2017 and March 2018 were included. Classification by the KM algorithm was compared with that of the Hartwacht team led by a cardiologist. Statistical analyses were performed with respect to detection of sinus rhythm (SR), atrial fibrillation (AF) and other arrhythmias. Results 5,982 KM ECGs were received from 233 patients (mean age 58 years, 52% male). The KM algorithm categorised 59% as SR, 22% as possible AF, 17% as unclassified and 2% as unreadable. According to the Hartwacht team, 498 (8%) ECGs were uninterpretable. Negative predictive value for detection of AF was 98%. However, positive predictive value as well as detection of other arrhythmias was poor. In 81% of
International Journal Of Community Medicine And Public Health, 2020
Background: Electrocardiogram (ECG) is a non-invasive test which can provide clue for the presence of cardiac diseases. Simple, handheld devices, sufficiently miniaturized are useful for a widespread use. New devices, however, need to be compared with the standard ones for their performance in the real-world practice. Here in we report clinical utility of a handheld device.Methods: KardioscreenTM is a mobile and handheld device. It’s been approved for safety and performance standards and it has been certified for ‘Conformite Europeenne’ (CE). Using this device, a comparative blinded study with a conventional and commercially available standard 12 lead ECG machine was one. 604 ECGs recorded from 302 patients with various clinical disorders were coded and analyzed by two blinded observers. A third cardiologist adjudicated the reports. The reports were then correlated for the ECG patterns generated and with the clinical diagnosis. Computer generated measurements of various durations an...
Europace, 2016
To determine the usability, accuracy, and cost-effectiveness of two handheld single-lead electrocardiogram (ECG) devices for atrial fibrillation (AF) screening in a hospital population with an increased risk for AF. Methods and results Hospitalized patients (n ¼ 445) at cardiological or geriatric wards were screened for AF by two handheld ECG devices (MyDiagnostick and AliveCor). The performance of the automated algorithm of each device was evaluated against a full 12-lead or 6-lead ECG recording. All ECGs and monitor tracings were also independently reviewed in a blinded fashion by two electrophysiologists. Time investments by nurses and physicians were tracked and used to estimate cost-effectiveness of different screening strategies. Handheld recordings were not possible in 7 and 21.4% of cardiology and geriatric patients, respectively, because they were not able to hold the devices properly. Even after the exclusion of patients with an implanted device, sensitivity and specificity of the automated algorithms were suboptimal (Cardiology: 81.8 and 94.2%, respectively, for MyDiagnostick; 54.5 and 97.5%, respectively, for AliveCor; Geriatrics: 89.5 and 95.7%, respectively, for MyDiagnostick; 78.9 and 97.9%, respectively, for AliveCor). A scenario based on automated AliveCor evaluation in patients without AF history and without an implanted device proved to be the most cost-effective method, with a provider cost to identify one new AF patient of E193 and E82 at cardiology and geriatrics, respectively. The cost to detect one preventable stroke per year would be E7535 and E1916, respectively (based on average CHA 2 DS 2-VASc of 3.9 + 2.0 and 5.0 + 1.5, respectively). Manual interpretation increases sensitivity, but decreases specificity, doubling the cost per detected patient, but remains cheaper than sole 12-lead ECG screening. Conclusion Using AliveCor or MyDiagnostick handheld recorders requires a structured screening strategy to be effective and cost-effective in a hospital setting. It must exclude patients with implanted devices and known AF, and requires targeted additional 12-lead ECGs to optimize specificity. Under these circumstances, the expenses per diagnosed new AF patient and preventable stroke are reasonable.
European heart journal supplements : journal of the European Society of Cardiology, 2017
The electrocardiogram (ECG) signal can be derived from different sources. These include systems for surface ECG, Holter monitoring, ergometric stress tests, and telemetry systems and bedside monitoring of vital parameters, which are useful for rhythm and ST-segment analysis and ECG screening of electrical sudden cardiac death predictors. A precise ECG diagnosis is based upon correct recording, elaboration, and presentation of the signal. Several sources of artefacts and potential external causes may influence the quality of the original ECG waveforms. Other factors that may affect the quality of the information presented depend upon the technical solutions employed to improve the signal. The choice of the instrumentations and solutions used to offer a high-quality ECG signal are, therefore, of paramount importance. Some requirements are reported in detail in scientific statements and recommendations. The aim of this consensus document is to give scientific reference for the choice o...
The Annals of Family Medicine
PURPOSE To validate a smartphone-operated, single-lead electrocardiography (1L-ECG) device (AliveCor KardiaMobile) with an integrated algorithm for atrial fibrillation (AF) against 12-lead ECG (12L-ECG) in a primary care population. METHODS We recruited consecutive patients who underwent 12L-ECG for any nonacute indication. Patients held a smartphone with connected 1L-ECG while local personnel simultaneously performed 12L-ECG. All 1L-ECG recordings were assessed by blinded cardiologists as well as by the smartphone-integrated algorithm. The study cardiologists also assessed all 12L-recordings in random order as the reference standard. We determined the diagnostic accuracy of the 1L-ECG in detecting AF or atrial flutter (AFL) as well as any rhythm abnormality and any conduction abnormality with the simultaneously performed 12L-ECG as the reference standard. RESULTS We included 214 patients from 10 Dutch general practices. Mean ± SD age was 64.1 ± 14.7 years, and 53.7% of the patients were male. The 12L-ECG diagnosed AF/AFL, any rhythm abnormality, and any conduction abnormality in 23, 44, and 28 patients, respectively. The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for AF/AFL of 100% (95% CI, 85.2%-100%) and 100% (95% CI, 98.1%-100%). The AF detection algorithm had a sensitivity and specificity of 87.0% (95% CI, 66.4%-97.2%) and 97.9% (95% CI, 94.7%-99.4%). The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for any rhythm abnormality of 90.9% (95% CI, 78.3%-97.5%) and 93.5% (95% CI, 88.7%-96.7%) and for any conduction abnormality of 46.4% (95% CI, 27.5%-66.1%) and 100% (95% CI, 98.0%-100%). CONCLUSIONS In a primary care population, a smartphone-operated, 1L-ECG device showed excellent diagnostic accuracy for AF/AFL and good diagnostic accuracy for other rhythm abnormalities. The 1L-ECG device was less sensitive for conduction abnormalities.
Anytime ECG Monitoring through the Use of a Low-Cost, User-Friendly, Wearable Device
Sensors
Every year cardiovascular diseases kill the highest number of people worldwide. Among these, pathologies characterized by sporadic symptoms, such as atrial fibrillation, are difficult to be detected as state-of-the-art solutions, e.g., 12-leads electrocardiogram (ECG) or Holter devices, often fail to tackle these kinds of pathologies. Many portable devices have already been proposed, both in literature and in the market. Unfortunately, they all miss relevant features: they are either not wearable or wireless and their usage over a long-term period is often unsuitable. In addition, the quality of recordings is another key factor to perform reliable diagnosis. The ECG WATCH is a device designed for targeting all these issues. It is inexpensive, wearable (size of a watch), and can be used without the need for any medical expertise about positioning or usage. It is non-invasive, it records single-lead ECG in just 10 s, anytime, anywhere, without the need to physically travel to hospital...
Efficacy of diagnostic tools for detecting cardiac arrhythmias: systematic literature search
Netherlands Heart Journal, 2010
Symptoms suggestive of cardiac arrhythmias are a challenge to the diagnosis. Physical examination and a 12-lead ECG are of limited value, as rhythm disturbances are frequently of a paroxysmal nature. New technologies facilitate a more accurate diagnosis. The objective of this study was to review the medical literature in an effort to define a guide to rational diagnostic testing. Primary studies on the use of a diagnostic tool in the evaluation of palpitations were searched in MEDLINE, and EMBASE with an additional reference check. TWO TYPES OF STUDIES WERE FOUND: descriptive and experimental studies, which compared the yield of two or more devices or diagnostic strategies. Holter monitors seemed to have less diagnostic yield (33 to 35%) than event recorders. Automatically triggered recorders detect more arrhythmias (72 to 80%) than patient-triggered devices (17 to 75%). Implantable devices are used for prolonged monitoring periods in patients with infrequent symptoms or unexplained syncope. The choice of the device depends on the characteristics of the symptoms and the patient. Due to methodological shortcomings of the included studies no evidence-based diagnostic strategy can be proposed. (Neth Heart J 2010;18:543-51.).
Electrocardiograph: A Portable Bedside Monitor
Electrocardiograph is a biomedical device that measures electrical potential generated by electrical activity that occurs due to the heart's pumping action. The graphical presentation of the Electrocardiogram (ECG) can be interpreted so that normal and abnormal rhythms of the heart can be detected and diagnosed. Design, construction and manufacturing of this device in Africa would improve access to health care, create employment and improve the African economy. The major materials considered for the implementation include the instrumentation amplifier AD624, Low Noise JFET Operational Amplifier TL074, a clinical standard 12-lead ECG electrode, various electrical and electronic components such as resistors, capacitors and diodes for protection and an oscilloscope. The electrodes connected to the body convert the heart signal into electrical voltage. These voltages obtained from the body are too small for the oscilloscope to capture and so are amplified using AD624. Noise from the environment affects the ECG signal. To suppress the noise, the signal from the amplifier is filtered. According to the International Electrotechnical Commission (IEC) specification, the bandwidth required for an ECG filtering is between 0.5Hz – 150Hz. Band-pass filtering is used. The signal obtained from the band pass filter stage is then passed through a notch filter to further eliminate 50 Hz noise from the power line. The result is then displayed on an oscilloscope. The Electrocardiograph was tested on different subjects and the results compare favourably with results obtained with imported ECG monitor.