Cancellation of the Maternal and Extraction of the Fetal ECG in Noninvasive Recordings

Abstract No signal processin

Predictors of Recurrence of AF in Patients After Radiofrequency Ablation

Catheter ablation is a well-known treatment for patients with AF. Despite the growing knowledge in the field, the identification of predictors of recurrence of AF after catheter ablation is one of the primary goals and is of major importance to improve long-term results of the procedure. The aim of this article is to provide an overview of what has been published in recent years and to summarise the major predictors, helping cardiac electrophysiologists in the selection of the right candidates for catheter ablation

Left atrial volume changes during exercise stress echocardiography in heart failure and hypertrophic cardiomyopathy

We assessed feasibility and functional correlates of LAVI (left atrial volume index) changes during exercise stress echocardiography (ESE).ESE on bike or treadmill was performed in 363 patients with heart failure with preserved ejection fraction (HFpEF, n = 173), reduced ejection fraction (HFrEF, n = 59) or hypertrophic cardiomyopathy (HCM, n=131). LAVI stress-rest increase ≥ 6.8 ml/m2 was defined as dilation.LAVI measurements were feasible in 100%. LAVI did not change in HFrEF being at rest 32 (25-45) vs. at stress 36 (24 - 54) ml/m2, P = NS and in HCM at rest 35 (26 - 48) vs. at stress 38 (28 - 48) ml/m2, P = NS whereas it decreased in HFpEF from 30 (24 -40) to 29 (21 - 37) ml/m2 at stress, P = 0.007. LA dilation occurred in 107 (30%) patients (27% with treadmill vs. 33% with bike ESE, P = NS): 26 with HFpEF (15%), 26 with HFrEF (44%) and 55 with HCM (42%) with P 14 at rest with OR 4.4, LVEF < 50% with OR 2.9, and LAVI at rest < 35 ml/m2 with OR 2.7.LAVI assessment during ESE was highly feasible and dilation equally frequent with treadmill or bike. LA dilation was threefold more frequent in HCM and HFrEF and could be predicted by increased resting E/e' and impaired EF as well as smaller baseline LAVI

Post COVID-19 Conditions and the Cardiovascular System

One out of four patients affected by COVID-19 will experience persistent (>3-4 weeks) signs and symptoms (Post COVID-19 conditions or Post-Acute Sequelae of SARS-CoV-2 – PASC) and this fact will have a major significance for the healthcare and economic systems in the upcoming years. The cardiovascular system is one of the key targets for the Post COVID-19 syndrome, given the pathogenesis of the virus and prevalence of ACE-2 receptors. According to our initial personal experience via the campaign “Life after COVID” of the Bulgarian Cardiac Institute, a substantial proportion of patients having suffered from COVID-19 develop long-term cardiovascular consequences. They could range from rhythm disorder and blood pressure variation, through impairment of myocardial mechanics and heart failure, and to acute vascular manifestations of Post COVID-19 conditions, such as acute coronary syndrome, acute pulmonary embolism, and acute limb ischemia. These cardiovascular complications require special and dedicated medical attention, and we could share our personal experience on the matter

Dataset of manually measured QT intervals in the electrocardiogram

BACKGROUND: The QT interval and the QT dispersion are currently a subject of considerable interest. Cardiac repolarization delay is known to favor the development of arrhythmias. The QT dispersion, defined as the difference between the longest and the shortest QT intervals or as the standard deviation of the QT duration in the 12-lead ECG is assumed to be reliable predictor of cardiovascular mortality. The seventh annual PhysioNet/Computers in Cardiology Challenge, 2006 addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations? METHOD: The PTB Diagnostic ECG Database was given to 4 cardiologists and 1 biomedical engineer for manual marking of QRS onsets and T-wave ends in 458 recordings. Each recording consisted of one selected beat in lead II, chosen visually to have minimum baseline shift, noise, and artifact. In cases where no T wave could be observed or its amplitude was very small, the referees were instructed to mark a 'group-T-wave end' taking into consideration leads with better manifested T wave. A modified Delphi approach was used, which included up to three rounds of measurements to obtain results closer to the median. RESULTS: A total amount of 2*5*548 Q-onsets and T-wave ends were manually marked during round 1. To obtain closer to the median results, 8.58 % of Q-onsets and 3.21 % of the T-wave ends had to be reviewed during round 2, and 1.50 % Q-onsets and 1.17 % T-wave ends in round 3. The mean and standard deviation of the differences between the values of the referees and the median after round 3 were 2.43 ± 0.96 ms for the Q-onset, and 7.43 ± 3.44 ms for the T-wave end. CONCLUSION: A fully accessible, on the Internet, dataset of manually measured Q-onsets and T-wave ends was created and presented in additional file: 1 (Table 4) with this article. Thus, an available standard can be used for the development of automated methods for the detection of Q-onsets, T-wave ends and for QT interval measurements

ESC Working Group on e-Cardiology Position Paper: Use of Commercially Available Wearable Technology for Heart Rate and Activity Tracking in Primary and Secondary Cardiovascular Prevention

Commercially available health technologies such as smartphones and smartwatches, activity trackers and eHealth applications, commonly referred to as wearables, are increasingly available and used both in the leisure and healthcare sector for pulse and fitness/ activity tracking. The aim of the Position Paper is to identify specific barriers and knowledge gaps for the use of wearables, in particular for heart rate and activity tracking, in clinical cardiovascular healthcare to support their implementation into clinical care. The widespread use of heart rate and fitness tracking technologies provides unparalleled opportunities for capturing physiological information from large populations in the community, which has previously only been available in patient populations in the setting of healthcare provision. The availability of low-cost and high-volume physiological data from the community also provides unique challenges. While the number of patients meeting healthcare providers with data from wearables is rapidly growing, there are at present no clinical guidelines on how and when to use data from wearables in primary and secondary prevention. Technical aspects of heart rate tracking especially during activity need to be further validated. How to analyze, translate, and interpret large datasets of information into clinically applicable recommendations needs further consideration. While the current users of wearable technologies tend to be young, healthy and in the higher sociodemographic strata, wearables could potentially have a greater utility in the elderly and higher risk population. Wearables may also provide a benefit through increased health awareness, democratization of health data and patient engagement. Use of continuous monitoring may provide opportunities for detection of risk factors and disease development earlier in the causal pathway, which may provide novel applications in both prevention and clinical research. However, wearables may also have potential adverse consequences due to unintended modification of behaviour, uncertain use and interpretation of large physiological data, a possible increase in social inequality due to differential access and technological literacy, challenges with regulatory bodies and privacy issues. In the present position paper, current applications as well as specific barriers and gaps in knowledge are identified and discussed in order to support the implementation of wearable technologies from gadget-ology into clinical cardiology

Quality control of B-lines analysis in stress Echo 2020

Background The effectiveness trial “Stress echo (SE) 2020” evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion. Purpose To provide web-based upstream quality control and harmonization of B-lines reading criteria. Methods 60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module ( http://se2020.altervista.org ). Each test clip was scored for B-lines from 0 (black lung, A-lines, no B-lines) to 10 (white lung, coalescing B-lines). The diagnostic gold standard was the concordant assessment of two experienced readers of the Pisa lab. The answer of the reader was considered correct if concordant with reference standard reading ±1 (for instance, reference standard reading of 5 B-lines; correct answer 4, 5, or 6). The a priori determined pass threshold was 18/20 (≥ 90%) with R value (intra-class correlation coefficient) between reference standard and recruiting center) > 0.90. Inter-observer agreement was assessed with intra-class correlation coefficient statistics. Results All 60 readers were successfully accredited: 26 (43%) on first, 24 (40%) on second, and 10 (17%) on third attempt. The average diagnostic accuracy of the 60 accredited readers was 95%, with R value of 0.95 compared to reference standard reading. The 53 B-lines naive scored similarly to the 7 B-lines expert on first attempt (90 versus 95%, p = NS). Compared to the step-1 of quality control for regional wall motion abnormalities, the mean reading time per attempt was shorter (17 ± 3 vs 29 ± 12 min, p < .01), the first attempt success rate was higher (43 vs 28%, p < 0.01), and the drop-out of readers smaller (0 vs 28%, p < .01). Conclusions Web-based learning is highly effective for teaching and harmonizing B-lines reading. Echocardiographers without previous experience with B-lines learn quickly.info:eu-repo/semantics/publishedVersio

Sources of Variation in the QT Readings: What should you be Aware of?

The QT interval is measured manually or automatically. In comparison with manual methods, the automated ones offer advantages in terms of absolute repeatability of measurements, immunity from errors related to observer fatigue, lack of attention, as well as efficiency and cost effectiveness that permits either more extensive and rigorous testing for the same cost as manual methods, or more rapid testing at lower cost. But a question arises: 'Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations?' We created a dataset of manually measured Q-onsets and T-ends for the PTB Diagnostic ECG Database. Further on we developed a fully automated method for QT measurements and forwarded it to PhysioNet/Computers in Cardiology Challenge, 2006. The manually measured dataset was then used as a 'gold standard' for assessment of the accuracy of the automated method. The current lecture notes summarize all our up to date publications on the QT measurements topic. Sources of variation in the QT readings are for the first time discussed by the authors