To investigate the combination of heart rate turbulence (HRT) and deceleration capacity (DC) as risk predictors in post-infarction patients with left ventricular ejection fraction (LVEF) > 30%. We enrolled 2343 consecutive survivors of acute myocardial infarction (MI) (30% (cumulative 5-year mortality rates of 37.9% and 7.8%, respectively). Among patients with LVEF > 30%, SAF identified another high-risk group of 117 patients with 37 deaths (cumulative 5-year mortality rates of 38.6% and 6.1%, respectively). Merging both high-risk groups (i.e. LVEF ≤ 30% and/or SAF) doubled the sensitivity of mortality prediction compared with LVEF ≤ 30% alone (21.1% vs. 42.1%, P < 0.001) while preserving 5-year mortality rate (38.2%). In post-MI patients with LVEF>30%, SAF identifies a high-risk group equivalent in size and mortality risk to patients with LVEF ≤ 30%.

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Exposure to ambient particles has been shown to be responsible for cardiovascular effects, especially in elderly with cardiovascular disease. The study assessed the association between deceleration capacity (DC) as well as heart rate variability (HRV) and ambient particulate matter (PM) in patients with coronary artery disease (CAD). A prospective study with up to 12 repeated measurements was conducted in Erfurt, Germany, between October 2000 and April 2001 in 56 patients with physician-diagnosed ischemic heart disease, stable angina pectoris or prior myocardial infarction at an age of at least 50 years. Twenty-minute ECG recordings were obtained every two weeks and 24-hour ECG recordings every four weeks. Exposure to PM (size range from 10 nm to 2.5 μm), and elemental (EC) and organic (OC) carbon was measured. Additive mixed models were used to analyze the association between PM and ECG recordings. The short-term recordings showed decrements in the high-frequency component of HRV as well as in RMSSD (root-mean-square of successive differences of NN intervals) in association with increments in EC and OC 0-23 hours prior to the recordings. The long-term recordings revealed decreased RMSSD and pNN50 (% of adjacent NN intervals that differed more than 50 ms) in association with EC and OC 24-47 hours prior to the recordings. In addition, highly significant effects were found for DC which decreased in association with PM2.5, EC and OC concurrent with the ECG recordings as well as with a lag of up to 47 hours. The analysis showed significant effects of ambient particulate air pollution on DC and HRV parameters reflecting parasympathetic modulation of the heart in patients with CAD. An air pollution-related decrease in parasympathetic tone as well as impaired heart rate deceleration capacity may contribute to an increased risk for cardiac morbidity and sudden cardiac death in vulnerable populations.

Risk stratification of sudden cardiac death after myocardial infarction and prevention by defibrillator rely on left ventricular ejection fraction (LVEF). Improved risk stratification across the whole LVEF range is required for decision-making on defibrillator implantation. The analysis pooled 20 data sets with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). Primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy. Using a competing risk framework and systematic internal–external cross-validation, a model using LVEF only, a multivariable flexible parametric survival model, and a multivariable random forest survival model were developed and externally validated. Predictive performance was assessed by random effect meta-analysis. There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In these three subgroups, LVEF poorly predicted sudden cardiac death (c-statistics between 0.50 and 0.56). Considering additional parameters did not improve calibration and discrimination, and model generalizability was poor. More accurate risk stratification for sudden cardiac death and identification of low-risk individuals with severely reduced LVEF or of high-risk individuals with preserved LVEF was not feasible, neither using LVEF nor using other predictors. Brief summary of the background, methodology, and results of the PROFID data analysis. ICD patients, patients with left ventricular ejection fraction ≤ 35% who had received a cardioverter-defibrillator implantation for primary prevention of sudden cardiac death; non-ICD patients ≤35%, patients who did not carry a cardioverter-defibrillator and had a left ventricular ejection fraction ≤ 35%; and non-ICD patients >35%, patients who did not carry a cardioverter-defibrillator and had a left ventricular ejection fraction > 35%. Detailed inclusion and exclusion criteria are provided in the text. CMR, cardiac magnetic resonance; ICD, implantable cardioverter-defibrillator; LVEF, left ventricular ejection fraction; MI, myocardial infarction.

Background: If a COVID-19 patient develops a so-called severe course, he or she must be taken to hospital as soon as possible. This proves difficult in domestic isolation, as patients are not continuously monitored. The aim of our study was to establish a telemonitoring system in this setting. Methods: Oxygen saturation, respiratory rate, heart rate and temperature were measured every 15 minutes using an in-ear device. The data was transmitted to the Telecovid Centre via mobile network or internet and monitored 24/7 by a trained team. The data were supplemented by daily telephone calls. The patients´ individual risk was assessed using a modified National Early Warning Score. In case of a deterioration, a physician initiated the appropriate measures. Covid-19 Patients were included if they were older than 60 years or fulfilled at least one of the following conditions: pre-existing disease (cardiovascular, pulmonary, immunologic), obesity (BMI >35), diabetes mellitus, hypertension, active malignancy, or pregnancy. Findings: 153 patients (median age 59 years, 77 female) were included. Patients were monitored for 9 days (median, IQR 6–13 days) with a daily monitoring time of 13.3 hours (median, IQR 9.4–17.0 hours). 20 patients were referred to the clinic by the Telecovid team. 3 of these required intensive care without invasive ventilation, 4 with invasive ventilation, 1 of the latter died. All patients agreed that the device was easy to use. About 90% of hospitalised patients indicated that they would have delayed hospitalisation further if they had not been part of the study. Interpretation: Our study demonstrates the successful implementation of a remote monitoring system in a pandemic situation. All clinically necessary information was obtained and adequate measures were derived from it without delay.