Aims: In this study, we compare the diagnostic accuracy of a standard 12-lead electrocardiogram (ECG) with a novel 13-lead ECG derived from a self-applicable 3-lead ECG recorded with the right exploratory left foot (RELF) device. The 13th lead is a novel age and sex orthonormalized computed ST (ASO-ST) lead to increase the sensitivity for detecting ischaemia during acute coronary artery occlusion.
Methods and results: A database of simultaneously recorded 12-lead ECGs and RELF recordings from 110 patients undergoing coronary angioplasty and 30 healthy subjects was used. Five cardiologists scored the learning data set and five other cardiologists scored the validation data set. In addition, the presence of non-ischaemic ECG abnormalities was compared. The accuracy for detection of myocardial supply ischaemia with the derived 12 leads was comparable with that of the standard 12-lead ECG (P = 0.126). By adding the ASO-ST lead, the accuracy increased to 77.4% [95% confidence interval (CI): 72.4-82.3; P < 0.001], which was attributed to a higher sensitivity of 81.9% (95% CI: 74.8-89.1) for the RELF 13-lead ECG compared with a sensitivity of 76.8% (95% CI: 71.9-81.7; P < 0.001) for the 12-lead ECG. There was no significant difference in the diagnosis of non-ischaemic ECG abnormalities, except for Q-waves that were more frequently detected on the standard ECG compared with the derived ECG (25.9 vs. 13.8%; P < 0.001).
Conclusion: A self-applicable and easy-to-use 3-lead RELF device can compute a 12-lead ECG plus an ischaemia-specific 13th lead that is, compared with the standard 12-lead ECG, more accurate for the visual diagnosis of myocardial supply ischaemia by cardiologists.
[This corrects the article DOI: 10.1093/ehjdh/ztab001.].
Aims: Aortopathies are a series of disorders requiring multiple indicators to assess risk. Time-averaged wall shear stress (TAWSS) is currently considered as the primary indicator of aortopathies progression, which can only be calculated by Computational Fluid Dynamics (CFD). However, CFD's complexity and high computational cost, greatly limit its application. The study aimed to construct a deep learning platform which could accurately estimate TAWSS in ascending aorta.
Methods and results: A total of 154 patients who had thoracic computed tomography angiography were included and randomly divided into two parts: training set (90%, n = 139) and testing set (10%, n = 15). TAWSS were calculated via CFD. The artificial intelligence (AI)-based model was trained and assessed using the dice coefficient (DC), normalized mean absolute error (NMAE), and root mean square error (RMSE). Our AI platform brought into correspondence with the manual segmentation (DC = 0.86) and the CFD findings (NMAE, 7.8773% ± 4.7144%; RMSE, 0.0098 ± 0.0097), while saving 12000-fold computational cost.
Conclusion: The high-efficiency and robust AI platform can automatically estimate value and distribution of TAWSS in ascending aorta, which may be suitable for clinical applications and provide potential ideas for CFD-based problem solving.
Aims: Despite general awareness that screening for atrial fibrillation (AF) could reduce health hazards, large-scale implementation is lagging behind technological developments. As the successful implementation of a screening programme remains challenging, this study aims to identify facilitating and inhibiting factors from healthcare providers' perspectives.
Methods and results: A mixed-methods approach was used to gather data among practice nurses in primary care in the southern region of the Netherlands to evaluate the implementation of an ongoing single-lead electrocardiogram (ECG)-based AF screening programme. Potential facilitating and inhibiting factors were evaluated using online questionnaires (N = 74/75%) and 14 (of 24) semi-structured in-depth interviews (58.3%). All analyses were performed using SPSS 26.0. In total, 16 682 screenings were performed on an eligible population of 64 000, and 100 new AF cases were detected. Facilitating factors included 'receiving clear instructions' (mean ± SD; 4.12 ± 1.05), 'easy use of the ECG-based device' (4.58 ± 0.68), and 'patient satisfaction' (4.22 ± 0.65). Inhibiting factors were 'time availability' (3.20 ± 1.10), 'insufficient feedback to the practice nurse' (2.15 ± 0.89), 'absence of coordination' (54%), and the 'lack of fitting policy' (32%).
Conclusion: Large-scale regional implementation of an AF screening programme in primary care resulted in a low participation of all eligible patients. Based on the perceived barriers by healthcare providers, future AF screening programmes should create preconditions to fit the intervention into daily routines, appointing an overall project lead and a General Practitioner (GP) as a coordinator within every GP practice.
Aims: Home blood pressure telemonitoring (HBPT) is a useful way to manage BP. Recent advances in digital technology to automatically transmit BP data without the patient input may change the approach to long-term BP treatment and follow-up. The purpose of this review is to summarize the latest data on the HBPT with automatic data transmission.
Methods and results: Articles in English from 1980 to 2021 were searched by electronic databases. Randomized controlled trials comparing HBPT with automatic data transmission with usual BP management and including systolic BP (SBP) and/or diastolic BP (DBP) as outcomes in hypertension patients were included in the systematic review. A meta-analysis was conducted. After removing duplicates, 474 papers were included and 23 papers were identified. The HBPT with automatic data transmission had a significant beneficial impact on BP reduction (mean difference for office SBP -6.0 mm Hg; P < 0.001). Subgroup analyses showed that the studies using smartphone applications reduced BP significantly more in the intervention group than in the control group (standardized mean difference for office and home SBP -0.25; P = 0.01) as did the studies using HBPT other than the applications. Longer observation periods showed a sustained effect, and multidisciplinary cooperation was effective.
Conclusion: This review suggests that a care path based on HBPT with automatic data transmission can be more effective than classical management of hypertension. In particular, the studies using smartphone applications have shown beneficial effects. The results support the deployment of digital cardiology in the field of hypertension management.
Aims: Simplified detection of atrial arrhythmias via consumer-electronics would enable earlier therapy in at-risk populations. Whether this is feasible and effective in older populations is not known.
Methods and results: The fully remote, investigator-initiated Smartphone and wearable detected atrial arrhythmia in Older Adults Case finding study (Smart in OAC-AFNET 9) digitally enrolled participants ≥65 years without known atrial fibrillation, not receiving oral anticoagulation in Germany, Poland, and Spain for 8 weeks. Participants were invited by media communications and direct contacts. Study procedures adhered to European data protection. Consenting participants received a wristband with a photoplethysmography sensor to be coupled to their smartphone. The primary outcome was the detection of atrial arrhythmias lasting 6 min or longer in the first 4 weeks of monitoring. Eight hundred and eighty-two older persons (age 71 ± 5 years, range 65-90, 500 (57%) women, 414 (47%) hypertension, and 97 (11%) diabetes) recorded signals. Most participants (72%) responded to adverts or word of mouth, leaflets (11%) or general practitioners (9%). Participation was completely remote in 469/882 persons (53%). During the first 4 weeks, participants transmitted PPG signals for 533/696 h (77% of the maximum possible time). Atrial arrhythmias were detected in 44 participants (5%) within 28 days, and in 53 (6%) within 8 weeks. Detection was highest in the first monitoring week [incidence rates: 1st week: 3.4% (95% confidence interval 2.4-4.9); 2nd-4th week: 0.55% (0.33-0.93)].
Conclusion: Remote, digitally supported consumer-electronics-based screening is feasible in older European adults and identifies atrial arrhythmias in 5% of participants within 4 weeks of monitoring (NCT04579159).