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BackgroundThe results of telemedicine intervention studies in patients with heart failure (HF) to reduce rehospitalization rate and mortality by early detection of HF decompensation are encouraging. However, the benefits are lower than expected. A possible reason for this could be the fact that vital signs, including blood pressure, heart rate, heart rhythm, and weight changes, may not be ideal indicators of the early stages of HF decompensation but are more sensitive for acute events triggered by ischemic episodes or rhythm disturbances. Preliminary results indicate a potential role of ambient sensor–derived digital biomarkers in this setting. ObjectiveThe aim of this study is to identify changes in ambient sensor system–derived digital biomarkers with a high potential for early detection of HF decompensation. MethodsThis is a prospective interventional cohort study. A total of 24 consecutive patients with HF aged 70 years and older, living alone, and hospitalized for HF decompensation will be included. Physical activity in the apartment and toilet visits are quantified using a commercially available, passive, infrared motion sensing system (DomoHealth SA). Heart rate, respiration rate, and toss-and-turns in bed are recorded by using a commercially available Emfit QS device (Emfit Ltd), which is a contact-free piezoelectric sensor placed under the participant’s mattress. Sensor data are visualized on a dedicated dashboard for easy monitoring by health professionals. Digital biomarkers are evaluated for predefined signs of HF decompensation, including particularly decreased physical activity; time spent in bed; increasing numbers of toilet visits at night; and increasing heart rate, respiration rate, and motion in bed at night. When predefined changes in digital biomarkers occur, patients will be called in for clinical evaluation, and N-terminal pro b-type natriuretic peptide measurement (an increase of >30% considered as significant) will be performed. The sensitivity and specificity of the different biomarkers and their combinations for the detection of HF decompensation will be calculated. ResultsThe study is in the data collection phase. Study recruitment started in February 2024. Data analysis is scheduled to start after all data are collected. As of manuscript submission, 5 patients have been recruited. Results are expected to be published by the end of 2025. ConclusionsThe results of this study will add to the current knowledge about opportunities for telemedicine to monitor older patients with HF living at home alone by evaluating the potential of ambient sensor systems for this purpose. Timely recognition of HF decompensation could enable proactive management, potentially reducing health care costs associated with preventable emergency presentations or hospitalizations. Trial RegistrationClinicalTrials.gov NCT06126848; https://clinicaltrials.gov/study/NCT06126848 International Registered Report Identifier (IRRID)PRR1-10.2196/55953

Purpose: Acute heart failure (AHF) is associated with high morbidity and mortality, and the prognosis is particularly poor in older patients. Although the application of guideline-directed medical therapy (GDMT) has shown a positive impact on prognosis, the effects are less clear in older age groups. The aim of this study was to analyze real-world data regarding GDMT and outcomes in older HF patients. Methods: This is a prospective cohort study from a secondary care hospital in central Switzerland. A total of 97 consecutive patients aged ≥60 years were enrolled between January 2019 and 2022. The main outcome parameters were prescribed GDMT at discharge, and in case of rehospitalization, GDMT at readmission, and survival in terms of all-cause mortality and HF-related hospitalizations during a 3-year follow-up period. Results: Follow-up data were available for 93/97 patients. The mean age was 77.8 ± 9.8 years, 46% being female. The mean left ventricular ejection fraction (LVEF) was 35.3 ± 13.9%, with a mean BNP level of 2204.3 ± 239 ng/L. Upon discharge, 86% received beta-blockers and 76.3% received renin–angiotensin system (RAS) inhibitors. At rehospitalization for AHF, beta-blockers use was significantly lower and decreased to 52.8% (p = 0.003), whereas RAS inhibitor use increased slightly to 88.9% (p = 0.07), and SGLT-2 inhibitors showed a significant increase from 5.4% vs. 47.2% (p = 0.04). GDMT prescription was not dependent on LVEF. Overall, 73.1% of patients received two-stage or three-stage GDMT at discharge, whereas this percentage decreased to 61% at rehospitalization (p = 0.01). Kaplan–Meier analysis for the combined outcome rehospitalization and death stratified by LV function showed significant differences between LVEF groups (aHR: 0.6 [95% CI: 0.44 to 0.8]; p = 0.0023). Conclusions: Our results indicate that first, the majority of older AHF patients from a secondary care hospital in Switzerland were not on optimal GDMT at discharge and even fewer at readmission, and second, that prognosis of the population is still poor, with almost half of the patients having been rehospitalized or died during a 3-year follow-up period under real-world conditions, without significant difference between women and men. Our findings underline the need for further improvements in the medical treatment of AHF, in particular in older patients, to improve prognosis and to reduce the burden of disease.

Abstract Using connected sensing devices to remotely monitor health is a promising way to help transition healthcare from a rather reactive to a more precision medicine oriented proactive approach, which could be particularly relevant in the face of rapid population ageing and the challenges it poses to healthcare systems. Sensor derived digital measures of health, such as digital biomarkers or digital clinical outcome assessments, may be used to monitor health status or the risk of adverse events like falls. Current research around such digital measures has largely focused on exploring the use of few individual measures obtained through mobile devices. However, especially for long-term applications in older adults, this choice of technology may not be ideal and could further add to the digital divide. Moreover, large-scale systems biology approaches, like genomics, have already proven beneficial in precision medicine, making it plausible that the same could also hold for remote-health monitoring. In this context, we introduce and describe a zero-interaction digital exhaust: a set of 1268 digital measures that cover large parts of a person’s activity, behavior and physiology. Making this approach more inclusive of older adults, we base this set entirely on contactless, zero-interaction sensing technologies. Applying the resulting digital exhaust to real-world data, we then demonstrate the possibility to create multiple ageing relevant digital clinical outcome assessments. Paired with modern machine learning, we find these assessments to be surprisingly powerful and often on-par with mobile approaches. Lastly, we highlight the possibility to discover novel digital biomarkers based on this large-scale approach.

Abstract Background Whereas the dietary intake of industrial trans fatty acids (iTFA) has been specifically associated with inflammation, cardiovascular disease, and type 2 diabetes, understanding the impact of dietary fats on human health remains challenging owing to their complex composition and individual effects of their lipid components on metabolism. The aim of this study is to profile the composition of blood, measured by the fatty acid (FAs) profile and untargeted metabolome of serum and the transcriptome of blood cells, in order to identify molecular signatures that discriminate dietary fat intakes. Methods In a parallel study, the molecular effects of consuming dairy fat containing ruminant TFA (rTFA) or margarine containing iTFA were investigated. Healthy volunteers (n = 42; 45–69 y) were randomly assigned to diets containing margarine without TFA as major source of fat (wTFA control group with 0.4 g TFA per 100 g margarine), margarine with iTFA (iTFA group with 4.1 g TFA per 100 g margarine), or butter with rTFA (rTFA group with 6.3 g TFA per 100 g butter) for 4 weeks. The amounts of test products were individually selected so that fat intake contributed to 30–33% of energy requirements and TFA in the rTFA and iTFA groups contributed to up to 2% of energy intake. Changes in fasting blood values of lipid profiles (GC with flame-ionization detection), metabolome profiles (LC-MS, GC-MS), and gene expression (microarray) were measured. Results Eighteen FAs, as well as 242 additional features measured by LC-MS (185) and GC-MS (54) showed significantly different responses to the diets (PFDR-adjusted

BackgroundCoronary heart disease (CHD) and its major risk factor hypertension have both been associated with altered activity of the hypothalamus-pituitary-adrenal (HPA)-axis but the biological mechanisms underlying prospective associations with adverse disease outcomes are unclear. We investigated diurnal HPA-axis activity in CHD-patients, hypertensive (HT) and healthy normotensive men (NT) and tested for prospective associations with biological CHD risk factors.MethodsEighty-three male CHD-patients, 54 HT and 54 NT men repeatedly measured salivary cortisol over two consecutive days. Prospective CHD risk was assessed by changes between baseline and follow-up in the prothrombotic factors D-dimer and fibrinogen, the pro-inflammatory measures interleukin (IL)-6, tumor necrosis factor-alpha (TNF-α), and acute phase protein C-reactive protein (CRP), as well as blood lipids in terms of total cholesterol (tChol)/high-density-lipoprotein cholesterol (HDL)-ratio. We aggregated coagulation and inflammatory measures to respective indices.ResultsThe groups differed in repeated daytime cortisol (dayCort) secretion (p=.005,η2p=.03,f=0.18) and cortisol awakening response (CAR) (p=.006,η2p=.03,f=0.18), with similarly lower overall dayCort and CAR in CHD-patients and HT, as compared to NT. The groups differed further in cortisol at awakening (p=.015,η2p=.04,f=0.20) with highest levels in HT (p´s≤.050), and in diurnal slope between waking and evening cortisol (p=.033,η2p=.04,f=0.20) with steepest slopes in HT (p´s≤.039), although in part not independent of confounders. Lower aggregated dayCort and CAR in terms of area-under-the-curve (AUC) independently predicted increases in future overall CHD risk (AUCdayCort: p=.021,η2p=.10,f=0.33;AUCCAR: p=.028,η2p=.09,f=0.31) 3.00 ± 0.06(SEM) years later, with risk prediction most pronounced in fibrinogen (AUCdayCort: p=.017,ΔR2= 0.12;AUCCAR: p=.082).ConclusionWe found evidence for an HPA-axis hypoactivity in CHD and HT with lower diurnal HPA-axis activity predicting increases in cardiovascular risk as evidenced by increases in circulating levels of biomarkers of atherothrombotic risk. Down-regulation of basal HPA-axis activity may contribute to the pathogenesis of atherosclerosis and thrombosis in CHD via effects on coagulation.

Background: The aim of this study was to evaluate the impact of single and combined effects of persistent medication adherence and compliance with lifestyle recommendations on the incidence of major adverse cardiovascular events (MACE) and one-year all-cause mortality in patients with type 2 diabetes (T2D) and peripheral artery disease (PAD) after partial foot amputation (PFA), representing a unique cohort of patients with advanced stages of atherosclerosis. Methods: This is a prospective cohort study of 785 consecutive patients (mean age 60.9 ± 9.1 years; 64.1% males). Medication adherence was evaluated by using the proportion of days covered (PDC) measure calculation and was defined as a PDC ≥80%. It derived as an average of PDCs of the following four classes of drugs: a) antidiabetics (oral hypoglycemic medications and/or insulin); b) ACEI or ARBs; c) Statins; d) antiplatelet drugs. Lifestyle compliance was defined as a PDC ≥80% comprising of PDCs of a) physical activity of ≥30 minutes per day; b) healthy nutrition and weight management; c) non-smoking. Cox proportional hazard models adjusted for confounders were used. Results: Total all-cause mortality was 16.9% (n = 133) at one-year follow-up. After adjusting for confounders, compared to adherent/compliant patients (n = 432), non-adherent and/or non-compliant patients had an increased risk of one-year mortality: HR = 8.67 (95% CI [5.29, 14.86] in non-adherent/non-compliant patients (n = 184), p < 0.001; HR = 3.81 (95% CI [2.03, 7.12], p < 0.001) in adherent/non-compliant patients (n = 101) and HR = 3.14 (95% CI [1.52, 6.45] p = 0.002) in non-adherent/compliant patients (n = 184). The incidence of MACE followed similar pattern (HR = 9.66 (95% CI [6.55, 14.25] for non-adherence/non-compliance; HR = 3.48 (95% CI [2.09, 5.77] and HR = 3.35 (95% CI [1.89, 5.91], p < 0.001 for single adherence or compliance. Conclusions: Medication adherence and compliance to lifestyle recommendations have shown to be equally effective to reduce the incidence of MACE and one-year mortality in patients with diabetes and PAD after PFA representing a population with highly advanced stages of atherosclerotic disease. Our findings underline the necessity to give lifestyle intervention programs a high priority and that costs for secondary prevention medications should be covered for patients under these circumstances. Lay Summary • This study analyzed the single and combined effects of medication adherence and compliance with lifestyle recommendations on cardiovascular events and mortality in patients with type 2 diabetes and advances stages of atherosclerosis over a period of one year. • Evaluation of medication adherence included antidiabetics, statins, dual antiplatelets and ACEI/ARBs, whereas lifestyle recommendations included healthy nutrition, physical activity and smoking cessation. • Persistent medication adherence and lifestyle changes have shown to be equally effective to reduce the incidence of MACE and one-year mortality in patients representing a population with highly advanced stages of atherosclerotic disease, and positive effects added up to a double effect if patients were persistently adherent and compliant with both interventions.

Background Electrical muscle stimulation (EMS) is being evaluated as a possible alternative to exercise training to improve functional capacity in severely deconditioned patients with heart failure (HF). However, there is insufficient data on delayed effects of EMS starting early after decompensation. The aim of this study was to determine the impact of a short inpatient EMS intervention in severely deconditioned patients with HF on functional capacity and quality of life (QoL) over a follow-up period of 1 month.Methods This is a prospective randomised sham-controlled pilot study. 45 patients hospitalised for decompensated systolic HF (58% men, mean age 66.4±10.2 years) were randomised to EMS (n=22) or sham stimulation (n=23) of lower limbs starting within 3 days after admission. The intervention included 7–10 sessions lasting from 30 to 90 min. The 6-minute walking test distance (6-MWTD), Duke Activity Status Index (DASI) and Minnesota Living with Heart Failure Questionnaire (MLHFQ) were evaluated at baseline, discharge and after 1 month.Results All patients completed the programme with good EMS tolerance. 37 patients were included in the final analysis. At discharge, 6-MWTD improved from 206,1±61,3 to 299.5±91 m, DASI from 12.1±5.6 to 18.3±7.2 and MLHFQ from 55.6±8.5 to 34.2±9 with EMS compared with smaller improvements in the sham group (p

Aims: To investigate the potential of a signal processed by smartphone-case based on single lead electrocardiogram (ECG) for left ventricular diastolic dysfunction (LVDD) determination as a screening method. Methods and Results: We included 446 subjects for sample learning and 259 patients for sample test aged 39 to 74 years for testing with 2D-echocardiography, tissue Doppler imaging and ECG using a smartphone-case based single lead ECG monitor for the assessment of LVDD. Spectral analysis of ECG signals (spECG) has been used in combination with advanced signal processing and artificial intelligence methods. Wavelengths slope, time intervals between waves, amplitudes at different points of the ECG complexes, energy of the ECG signal and asymmetry indices were analyzed. The QTc interval indicated significant diastolic dysfunction with a sensitivity of 78% and a specificity of 65%, a Tpeak parameter >590 ms with 63% and 58%, a T value off >695 ms with 63% and 74%, and QRSfi > 674 ms with 74% and 57%, respectively. A combination of the threshold values from all 4 parameters increased sensitivity to 86% and specificity to 70%, respectively (OR 11.7 [2.7-50.9], P

Background Cardiopulmonary exercise testing (CPET) has shown to be useful for preoperative risk stratification in various types of intra-abdominal and thoracic surgery. However, data about the predictive value of CPET for cardiovascular outcome after gastric or oesophageal cancer surgery are inconclusive. The aim of this study was to evaluate the prognostic value of CPET parameters for the prediction of cardiovascular complications in patients with this type of surgery.Methods This is a prospective single-centre interventional cohort study including 200 consecutive patients who underwent elective surgery for oesophageal and/or gastric cancer. Symptom-limited CPET was performed preoperatively to evaluate the potential of various test-derived parameters including anaerobic threshold (AT) to predict cardiovascular complications within 30 days after surgery.Results 200 patients (mean age 68±14.2 years) met inclusion and exclusion criteria: oesophageal surgery 54 pts, gastric surgery 132 pts and combined oesophageal/gastric surgery 14 pts. 41/200 pts (20.5%) experienced cardiovascular complications during and within 30 days after surgery including 4 non-fatal myocardial infarctions (2%), 1 stroke (0.5%); 6 dead from cardiovascular causes (3%) and less serious complications in 30 patients (15%) including angina attacks and antiarrhythmic therapy for ventricular arrhythmias or for atrial fibrillation/flutter. Results from preoperative CPET indicate that an AT level below 11 mL/kg/min was highly predictive for any cardiovascular complication (p=0.02, OR 6.33, 95% CI 1.78 to 22.47). An AT level

Background: Based on current evidence, it is not clear whether lone hypertension increases the risk for severe illness from COVID-19, or if increased risk is mainly associated with age, obesity and diabetes. The objective of the study was to evaluate whether lone hypertension is associated with increase mortality or a more severe course of COVID-19, and if treatment and control of hypertension mitigates this risk. Methods: This is a prospective multi-center observational cohort study with 30-day outcomes of 9,531 consecutive SARS-CoV-2 PCR-positive patients ≥ 18 years old (41.9 ± 9.7 years, 49.2% male), Uzbekistan, June 1-September 30, 2020. Patients were subclassified according to JNC8 criteria into six blood pressure stages. Univariable and multiple logistic regression was conducted to examine how variables predict outcomes. Results: The 30-days all-cause mortality was 1.18% (n = 112) in the whole cohort. After adjusting for age, sex, history of myocardial infarction (MI), type-2 diabetes, and obesity, none of six JNC8 groups showed any significant difference in all-cause mortality. However, age was associated with an increased risk of 30-days all-cause mortality (OR = 1.09, 95%CI [1.07–1.12], p < 0.001), obesity (OR = 7.18, 95% CI [4.18–12.44], p < 0.001), diabetes (OR 4.18, 95% CI [2.58–6.76], p < 0.001), and history of MI (OR = 2.68, 95% CI [1.67–4.31], p < 0.001). In the sensitivity test, being ≥ 65 years old increased mortality 10.56-fold (95% CI [5.89–18.92], p < 0.001). Hospital admission was 12.4% (n = 1,183), ICU admission 1.38% (n = 132). The odds of hospitalization increased having stage-2 untreated hypertension (OR = 4.51, 95%CI [3.21–6.32], p < 0.001), stage-1 untreated hypertension (OR = 1.97, 95%CI [1.52–2.56], p < 0.001), and elevated blood pressure (OR = 1.82, 95% CI [1.42–2.34], p < 0.001). Neither stage-1 nor stage-2 treated hypertension patients were at statistically significant increased risk for hospitalization after adjusting for confounders. Presenting with stage-2 untreated hypertension increased the odds of ICU admission (OR = 3.05, 95 %CI [1.57–5.93], p = 0.001). Conclusions: Lone hypertension did not increase COVID-19 mortality or in treated patients risk of hospitalization.

Background: Screening for atrial fibrillation has the potential to significantly reduce cardiovascular morbidity and mortality. However, questions in regard to how to screen, on whom to screen, and the optimal setting of screening remain unanswered. Objective: To assess the applicability of a federal cardiac monitoring for atrial fibrillation (AF) screening and remote heart rhythm monitoring in patients at high cardiovascular risk in a mixed urban and rural population in Russia. Methods: This is a prospective multicenter cohort study including 3249 individuals with high cardiovascular risk (mean age 56 ± 12.8 years) from the larger Moscow region who were screened for AF using a smartphone-case based single-lead ECG monitor over a period of 18 month. The endpoints were considered as number of newly diagnosed AF; mean time to diagnosis; number of patients for the first time assigned to anticoagulation therapy; frequency of adverse events. Results: A trial fibrillation was diagnosed in 126 patients, 36 of them for the first time. The mean time to diagnosis was 3 ± 2 days. Of 36 patients, the CHA2DS2-VASc score was ≥1 in 34 cases, ≥2 in 29 cases. Anticoagulant therapy was first induced in 31 patients. One death in newly diagnosed group and two deaths in chronic group were registered. There were a total of eight hospitalizations: one in newly diagnosed and seven in chronic AF patients. Conclusion: Our results indicate that a Federal AF screening system in patients at high cardiovascular risk by using a smartphone-case based single lead ECG which is supported by centrally located ECG specialist and central data management is feasible and reliable when performed in a mixed urban and rural area. Further studies are needed to evaluate the full potential of this approach.

Aim: To identify associations of anxiety symptoms (AS) and depressive symptoms (DS) with other psychosocial and lifestyle risk factors in primary care patients with arterial hypertension (AH) and/or coronary heart disease (CHD). Methods: COMETA (Clinical-epidemiOlogical prograM of studying psychosocial risk factors in cardiological practice in patiEnts with arterial hyperTension and ischemic heArt disease) is a multicenter cross-sectional study performed in 30 big cities of Russia with two to five out-patient clinics per city randomly selected and two to five general practitioners (GPs) per an out-patient clinic. Each GP included 8–10 consecutive patients with AH and/or CHD. AS and DS were assessed by the Hospital Anxiety and Depression Scale. Results: 325 GPs enrolled 2775 patients (mean age 66.7 years, 72% women) with AH (60.8%), CHD (2.6%), and AH plus CHD (36.6%). Moderate/severe (≥11 HADS) AS were found in 25.5% and DS in 16.3% patients. The strongest associations of AS and DS were revealed for high stress level (OR 5.79; 95% CI [4.18–8.03]), moderate stress level (OR 2.34; 95% CI [1.73–3.16]), low social support (OR 1.87; 95% CI [1.31–2.68]) and female gender (OR 1.78; 95% CI [1.41–2.25]). Low physical activity, unhealthy eating, unemployment and low income were also positively associated with both AS and DS (p < 0.003 for all). Conclusion: In out-patients with AH and CHD, AS and DS were strongly associated with higher levels of stress, low social support, unemployment, low family income and unhealthy lifestyle such as low physical activity, low fruit and vegetables intake and excessive salt consumption. Our findings indicate that patients with AH and CHD, who have anxiety and depressive symptoms need extra attention and monitoring in regard to stress and lifestyle risk factor control.

Telehealth strategies may offer an advantage over standard institutional based interventions for improvement of cardiovascular risk in high-risk patients long-term Background: Telehealth strategies are increasingly used to support people at high cardiovascular risk long-term, but is it unclear if these interventions are effective at improving cardiovascular risk. Objective: To evaluate the effects of a telemedicine technology-based program on risk factor control and body composition in patients at high cardiovascular risk. Methods: This is a population based randomized controlled trial. 100 patients at high and very high cardiovascular risk were randomly assigned to a telemedicine technology-based program consisting of: Comprehensive counseling on risk factors delivered by a physician; biweekly remote support via phone delivered by a trained nurse during the first three months after enrollment; and a control group receiving routine care with individual single-session counseling on patients’ current risk factors without further support. The follow-up period was 1 year. Results: Mean age of participants was 59.9 ± 4.5 years, 80% were women. Weight (–0.582; p < 0.001), waist circumference (–0.429; p = 0.01), body mass index (–0.216; p < 0.001) diastolic blood pressure (–0.881; p = 0.04), total cholesterol (–0.149; p = 0.01) and LDL cholesterol (–0.123; p = 0.003) were lower in the intervention group compared to the control group after 12-month. Body fat mass was also lower (–0.352; p = 0.01) and lean mass was higher (0.92; p = 0.03) in the intervention group. Anxiety scores (–2.5; p < 0.002) and depression scores (–2.6; p < 0.001) were also lower in the intervention group. Conclusions: Among older people at high cardiovascular risk, the addition of telehealth strategies using remote support by phone calls over a period of 3 month resulted in small but significant improvements of cardiovascular risk factors, body composition, anxiety, and depression which are maintained long-term. Such telehealth strategies may offer an advantage over standard institution-based interventions.

Home monitoring systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. More recently, multimodal ambient sensor systems are also used to monitor digital biomarkers to detect clinically relevant health problems over longer time periods. Clinical signs of HF decompensation including increase of heart rate and respiration rate, decreased physical activity, reduced gait speed, increasing toilet use at night and deterioration of sleep quality have a great potential to be detected by non-intrusive contactless ambient sensor systems and negative changes of these parameters may be used to prevent further deterioration and hospitalization for HF decompensation. This is to our knowledge the first report about the potential of an affordable, contactless, and unobtrusive ambient sensor system for the detection of early signs of HF decompensation based on data with prospective data acquisition and retrospective correlation of the data with clinical events in a 91 year old senior with a serious heart problem over 1 year. The ambient sensor system detected an increase of respiration rate, heart rate, toilet use at night, toss, and turns in bed and a decrease of physical activity weeks before the decompensation. In view of the rapidly increasing prevalence of HF and the related costs for the health care systems and the societies, the real potential of our approach should be evaluated in larger populations of HF patients.

Background: Although it is well acknowledged that psychosocial risk factors (PSRF) such as low socio-economic status, stress, social isolation, negative emotions and negative personality patterns may contribute to the development and adverse outcome of cardiovascular disease (CVD), screening for PSRF in CVD patients is usually limited to anxiety and depression, mainly for feasibility reasons. We therefore aimed to develop a user-friendly screening battery for routine assessment of PSRFs and to evaluate this instrument regarding feasibility of application, PSRF results and attendance of psychological counselling if recommended to cardiac rehabilitation (CR) patients. Methods: This is a prospective single center cohort study including 609 consecutive CR patients. We first developed a screening instrument based on seven validated scales for the most relevant PSRFs with totally 90 questions presented in a uniform graphical design to facilitate completion called Psychocardiogram® (PCG) and applied the instrument in consecutive patients attending CR. Patients with positive screening results were invited to a psychological counseling session. Results: Six hundred and nine consecutive patients, aged 34 to 86 years (mean 60.7 years), 85% men, entering the CR program at the Bern University Hospital with ischemic heart failure (CHF), coronary artery disease (CAD) or peripheral artery disease, were included in this study. Eighty-three point three percent of the patients completed the PCG within 40 minutes. Vital exhaustion and Type-D personality were the most prevalent PSRFs (56.9% and 51.1%, respectively), whereas low social support (14.4%) and elevated depressive symptoms (15.9%), were the least prevalent ones. After screening, 120 patients (52.86%) with at least one PSRF made use of psychological counseling. Conclusions: We found the PCG to be a useful screening tool for PSRF in CR patients with the potential to get new insights into the prevalence of particular PSRF in specific populations and to better study their impact on occurrence and outcome of CVD.

Passive infrared motion sensors are commonly used in telemonitoring applications to monitor older community-dwelling adults at risk. One possible use case is quantification of in-home physical activity, a key factor and potential digital biomarker for healthy and independent aging. A major disadvantage of passive infrared sensors is their lack of performance and comparability in physical activity quantification. In this work, we calibrate passive infrared motion sensors for in-home physical activity quantification with simultaneously acquired data from wearable accelerometers and use the data to find a suitable correlation between in-home and out-of-home physical activity. We use data from 20 community-dwelling older adults that were simultaneously provided with wireless passive infrared motion sensors in their homes, and a wearable accelerometer for at least 60 days. We applied multiple calibration algorithms and evaluated results based on several statistical and clinical metrics. We found that using even relatively small amounts of wearable based ground-truth data over 7–14 days, passive infrared based wireless sensor systems can be calibrated to give largely better estimates of older adults' daily physical activity. This increase in performance translates directly to stronger correlations of measured physical activity levels with a variety of age relevant health indicators and outcomes known to be associated with physical activity.

Introduction: Population aging is increasing the needs and costs of healthcare. Both frailty and the chronic diseases affecting older people reduce their ability to live independently. However, most older people prefer to age in their own homes. New development of in-home monitoring can play a role in staying independent, active, and healthy for older people. This 12-month observational study aimed to evaluate a new in-home monitoring system among home-dwelling older adults (OA), their family caregivers (FC), and nurses for the support of home care.Methods: The in-home monitoring system evaluated in this study continuously monitored OA's daily activities (e.g., mobility, sleep habits, fridge visits, door events) by ambient sensor system (DomoCare®) and health-related events by wearable sensors (Activity tracker, ECG). In the case of deviations in daily activities, alerts were transmitted to nurses via email. Using specific questionnaires, the opinions of 13 OA, 13 FC, and 20 nurses were collected at the end of 12-months follow-up focusing on user experience and the impact of in-home monitoring on home care services.Results: The majority of OA, FC, and nurses considered that in-home sensors can help with staying at home, improving home care and quality of life, preventing domestic accidents, and reducing family stress. The opinion tended to be more frequently favorable toward ambient sensors (76%; 95% CI: 61–87%) than toward wearable sensors (Activity tracker: 65%; 95% CI: 50–79%); ECG: 60%; 95% CI: 45–75%). On average, OA (74%; 95% CI: 46–95%) and FC (70%; 95% CI: 39–91%) tended to be more enthusiastic than nurses (60%; 95% CI: 36–81%). Some barriers reported by nurses were a fear of weakening of the relationship with OA and lack of time.Discussion/Conclusion: Overall, the opinions of OA, FC, and nurses were positively related to in-home sensors, with nurses being less enthusiastic about their use in clinical practice.

Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of clinically relevant health problems over longer time periods.Methods: Data were collected with a longitudinal home monitoring study in Switzerland (StrongAge Cohort Study) in a cohort of 24 old and oldest-old, community-dwelling adults over a period of 1 to 2 years. Physical activity in the apartment, toilet visits, refrigerator use, and entrance door openings were quantified using a commercially available passive infrared motion sensing system (Domosafety S.A., Switzerland). Heart rate, respiration rate, and sleep quality were recorded with the commercially available EMFIT QS bed sensor device (Emfit Ltd., Finland). Vital signs and contextual data were collected using a wearable sensor on the upper arm (Everion, Biovotion, Switzerland). Sensor data were correlated with health-related data collected from the weekly visits of the seniors by health professionals, including information about physical, psychological, cognitive, and behavior status, health problems, diseases, medication, and medical diagnoses.Results: Twenty of the 24 recruited participants (age 88.9 ± 7.5 years, 79% females) completed the study; two participants had to stop their study participation because of severe health deterioration, whereas two participants died during the course of the study. A history of chronic disease was present in 12/24 seniors, including heart failure, heart rhythm disturbances, pulmonary embolism, severe insulin-dependent diabetes, and Parkinson's disease. In total, 242,232 person-hours were recorded. During the monitoring period, 963 health status records were reported and repeated clinical assessments of aging-relevant indicators and outcomes were performed. Several episodes of health deterioration, including heart failure worsening and heart rhythm disturbances, could be captured by sensor signals from different sources.Conclusions: Our results indicate that monitoring of seniors with a multimodal sensor and pervasive computing system over longer time periods is feasible and well-accepted, with a great potential for detection of health deterioration. Further studies are necessary to evaluate the full range of the clinical potential of these findings.

The availability of simple, accurate, and affordable cuffless blood pressure (BP) devices has the potential to greatly increase the compliance with measurement recommendations and the utilization of BP measurements for BP telemonitoring. The aim of this study is to evaluate the correlation between findings from routine BP measurements using a conventional sphygmomanometer with the results from a portable ECG monitor combined with photoplethysmography (PPG) for pulse wave registration in patients with arterial hypertension. Methods: The study included 500 patients aged 32–88 years (mean 64 ± 7.9 years). Mean values from three routine BP measurements by a sphygmomanometer with cuff were selected for comparison; within one minute after the last measurement, an electrocardiogram (ECG) was recorded for 3 min in the standard lead I using a smartphone-case based single-channel ECG monitor (CardioQVARK®-limited responsibility company “L-CARD”, Moscow, Russia) simultaneously with a PPG pulse wave recording. Using a combination of the heart signal with the PPG, levels of systolic and diastolic BP were determined based on machine learning using a previously developed and validated algorithm and were compared with sphygmomanometer results. Results: According to the Bland–Altman analysis, SD for systolic BP was 3.63, and bias was 0.32 for systolic BP. SD was 2.95 and bias was 0.61 for diastolic BP. The correlation between the results from the sphygmomanometer and the cuffless method was 0.89 (p = 0.001) for systolic and 0.87 (p = 0.002) for diastolic BP. Conclusion: Blood pressure measurements on a smartphone-case without a cuff are encouraging. However, further research is needed to improve the accuracy and reliability of clinical use in the majority of patients.

QUESTION UNDER STUDY: Physical activity is known to play an important role in protection against cardiovascular disease. At present, there is no validated questionnaire recording physical activity for German-speaking cardiac patients. The aim of this study was to develop and validate a new physical activity questionnaire for German-speaking patients attending a cardiac rehabilitation programme. METHODS: A questionnaire on physical activity was developed on the basis of personal and telephone interviews, using qualitative and quantitative approaches. The questionnaire was validated in 48 patients during or after cardiac rehabilitation. For this purpose, data on energy expenditure in MET (metabolic equivalent) hours per day, collected from the questionnaire, were compared with the results of combined heart rate and accelerometry measurement (ECG-accelerometry) using an ACTIHEART-monitor and a physical activity diary. Test-retest reliability was examined in a subset of 33 patients who completed the questionnaire twice within 3 weeks. RESULTS: There was a significant correlation between the questionnaire data and the ECG-accelerometry (r = 0.407, p = 0.004). The mean (± standard deviation) difference between the results derived from the questionnaire and those from ECG-accelerometry was 1.05 ± 4.79 MET-hours per day. The retest showed a correlation of r = 0.624 (p