Use of sugar in coffee and tea and long-term risk of mortality in older adult Danish men: 32 years of follow-up from a prospective cohort study.

BACKGROUND: Tea and coffee are the most consumed beverages worldwide and very often sweetened with sugar. However, the association between the use of sugar in tea or coffee and adverse events is currently unclear. OBJECTIVES: To investigate the association between the addition of sugar to coffee or tea, and the risk of all-cause mortality, cardiovascular mortality, cancer mortality and incident diabetes mellitus. METHODS: Participants from the prospective Copenhagen Male Study, included from 1985 to 1986, without cardiovascular disease, cancer or diabetes mellitus at inclusion, who reported regular coffee or tea consumption were included. Self-reported number of cups of coffee and tea and use of sugar were derived from the study questionnaires. Quantity of sugar use was not reported. Primary outcome was all-cause mortality and secondary endpoints were cardiovascular mortality, cancer mortality and incident diabetes mellitus, all assessed through the Danish national registries. The association between adding sugar and all-cause mortality was analyzed by Cox regression analysis. Age, smoking status, daily alcohol intake, systolic blood pressure, body mass index, number of cups of coffee and/or tea consumed per day and socioeconomic status were included as covariates. Vital status of patients up and until 22.03.2017 was assessed. Sugar could be added to either coffee, tea or both. RESULTS: In total, 2923 men (mean age at inclusion: 63±5 years) were included, of which 1007 (34.5%) added sugar. In 32 years of follow-up, 2581 participants (88.3%) died, 1677 in the non-sugar group (87.5%) versus 904 in the sugar group (89.9%). Hazard ratio of the sugar group compared to the non-sugar group was 1.06 (95% CI 0.98;1.16) for all-cause mortality. An interaction term between number of cups of coffee and/or tea per day and adding sugar was 0.99 (0.96;1.01). A subgroup analysis of coffee-only drinkers showed a hazard ratio of 1.11 (0.99;1.26). The interaction term was 0.98 (0.94;1.02). Hazard ratios for the sugar group compared to the non-sugar group were 1.11 (95% CI 0.97;1.26) for cardiovascular disease mortality, 1.01 (95% CI 0.87;1.17) for cancer mortality and 1.04 (95% CI 0.79;1.36) for incident diabetes mellitus. CONCLUSION: In the present population of Danish men, use of sugar in tea and/or coffee was not significantly associated with increased risk of mortality or incident diabetes.

Fewer Worsening Heart Failure Events With HeartLogic on top of Standard Care: a Propensity-Matched Cohort Analysis.

BACKGROUND: The implantable cardiac defibrillator-based HeartLogic algorithm aims to detect impending fluid retention in patients with heart failure (HF). Studies show that HeartLogic is safe to integrate into clinical practice. The current study investigates whether HeartLogic provides clinical benefit on top of standard care and device telemonitoring in patients with HF. METHODS: A multicenter, retrospective, propensity-matched cohort analysis was performed in patients with HF and implantable cardiac defibrillators, and it compared HeartLogic to conventional telemonitoring. The primary endpoint was the number of worsening HF events. Hospitalizations and ambulatory visits due to HF were also evaluated. RESULTS: Propensity score matching yielded 127 pairs (median age 68 years, 80% male). Worsening HF events occurred more frequently in the control group (2; IQR 0-4) compared to the HeartLogic group (1; IQR 0-3; P = 0.004). The number of HF hospitalization days was higher in controls than in the HeartLogic group (8; IQR 5-12 vs 5; IQR 2-7; P = 0.023), and ambulatory visits for diuretic escalation were more frequent in the control group than in the HeartLogic group (2; IQR 0-3 vs 1; IQR 0-2; P = 0.0001). CONCLUSION: Integrating the HeartLogic algorithm in a well-equipped HF care path on top of standard care is associated with fewer worsening HF events and shorter duration of fluid retention-related hospitalizations.

Mobile health vs. standard care after cardiac surgery: results of The Box 2.0 study.

AIMS: Postoperative atrial fibrillation (POAF) is a common complication of cardiac surgery, yet difficult to detect in ambulatory patients. The primary aim of this study is to investigate the effect of a mobile health (mHealth) intervention on POAF detection after cardiac surgery. METHODS AND RESULTS: We performed an observational cohort study among 730 adult patients who underwent cardiac surgery at a tertiary care hospital in The Netherlands. Of these patients, 365 patients received standard care and were included as a historical control group, undergoing surgery between December 2017 and September 2018, and 365 patients were prospectively included from November 2018 and November 2020, undergoing an mHealth intervention which consisted of blood pressure, temperature, weight, and electrocardiogram (ECG) monitoring. One physical outpatient follow-up moment was replaced by an electronic visit. All patients were requested to fill out a satisfaction and quality of life questionnaire. Mean age in the intervention group was 62 years, 275 (70.4%) patients were males. A total of 4136 12-lead ECGs were registered. In the intervention group, 61 (16.7%) patients were diagnosed with POAF vs. 25 (6.8%) patients in the control group [adjusted risk ratio (RR) of POAF detection: 2.15; 95% confidence interval (CI): 1.55-3.97]. De novo atrial fibrillation was found in 13 patients using mHealth (6.5%) vs. 4 control group patients (1.8%; adjusted RR 3.94, 95% CI: 1.50-11.27). CONCLUSION: Scheduled self-measurements with mHealth devices could increase the probability of detecting POAF within 3 months after cardiac surgery. The effect of an increase in POAF detection on clinical outcomes needs to be addressed in future research.

Performance of a HeartLogicTM Based Care Path in the Management of a Real-World Chronic Heart Failure Population.

Aim: Early detection of impending fluid retention and timely adjustment of (medical) therapy can prevent heart failure related hospitalizations. The multisensory cardiac implantable electronic device (CIED) based algorithm HeartLogicTM aims to alert in case of impending fluid retention. The aim of the current analysis is to evaluate the performance of the HeartLogicTM guided heart failure care path in a real-world heart failure population and to investigate whether the height of the index and the duration of the alert state are indicative of the degree of fluid retention. Methods: Consecutive adult heart failure patients with a CIED and an activated HeartLogicTM algorithm were eligible for inclusion. Patients were followed up according to the hospital's heart failure care path. The device technician reviewed alerts for a technical CIED checkup. Afterwards, the heart failure nurse contacted the patient to identify impending fluid retention. An alert was either true positive or false positive. Without an alert a patient was true negative or false negative. Results: Among 107 patients, [82 male, 70 (IQR 60-77) years, left ventricular ejection fraction 37 ± 11%] 130 HeartLogicTM alerts were available for analysis. Median follow up was 14 months [IQR 8-23]. The sensitivity to detect impending fluid retention was 79%, the specificity 88%. The positive predictive was value 71% and the negative predictive value 91%. The unexplained alert rate was 0.23 alerts/patient year and the false negative rate 0.17 alerts/patient year. True positive alerts [42 days (IQR 28-63)] lasted longer than false positive alerts [28 days (IQR 21-44)], p = 0.02. The maximal HeartLogicTM index was higher in true positive alerts [26 (IQR 21-34)] compared to false positive alerts [19 (IQR 17-24)], p < 0.01. Patients with higher HeartLogicTM indexes required more intense treatment (index height in outpatient setting 25 [IQR 20-32], day clinic treatment 28 [IQR 24-36] and hospitalized patients 45 [IQR 35-58], respectively), p < 0.01. Conclusion: The CIED-based HeartLogicTM algorithm facilitates early detection of impending fluid retention and thereby enables clinical action to prevent this at early stage. The current analysis illustrates that higher and persistent alerts are indicative for true positive alerts and higher index values are indicative for more severe fluid retention.

Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review.

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate. OBJECTIVE: The goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up-for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient's chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates. METHODS: Two reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size. RESULTS: A total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I2 of 61.9, and therefore it was decided to not pool the results into a meta-analysis. CONCLUSIONS: Although the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

Early Detection of Fluid Retention in Patients with Advanced Heart Failure: A Review of a Novel Multisensory Algorithm, HeartLogicTM.

Heart failure (HF) hospitalisations due to decompensation are associated with shorter life expectancy and lower quality of life. These hospitalisations pose a significant burden on the patients, doctors and healthcare resources. Early detection of an upcoming episode of decompensation may facilitate timely optimisation of the ambulatory medical treatment and thereby prevent heart-failure-related hospitalisations. The HeartLogicTM algorithm combines data from five sensors of cardiac implantable electronic devices into a cumulative index value. It has been developed for early detection of fluid retention in heart failure patients. This review aims to provide an overview of the current literature and experience with the HeartLogicTM algorithm, illustrate how the index can be implemented in daily clinical practice and discuss ongoing studies and potential future developments of interest.

Clinical and economic impact of HeartLogic™ compared with standard care in heart failure patients.

AIMS: The implantable cardiac defibrillator/cardiac resynchronization therapy with defibrillator-based HeartLogic™ algorithm has recently been developed for early detection of impending decompensation in heart failure (HF) patients; but whether this novel algorithm can reduce HF hospitalizations has not been evaluated. We investigated if activation of the HeartLogic algorithm reduces the number of hospital admissions for decompensated HF in a 1 year post-activation period as compared with a 1 year pre-activation period. METHODS AND RESULTS: Heart failure patients with an implantable cardiac defibrillator/cardiac resynchronization therapy with defibrillator with the ability to activate HeartLogic and willingness to have remote device monitoring were included in this multicentre non-blinded single-arm trial with historical comparison. After a HeartLogic alert, the presence of HF symptoms and signs was evaluated. If there were two or more symptoms and signs apart from the HeartLogic alert, lifestyle advices were given and/or medication was adjusted. After activation of the algorithm, patients were followed for 1 year. HF events occurring in the 1 year prior to activation and in the 1 year after activation were compared. Of the 74 eligible patients (67.2 ± 10.3 years, 84% male), 68 patients completed the 1 year follow-up period. The total number of HF hospitalizations reduced from 27 in the pre-activation period to 7 in the post-activation period (P = 0.003). The number of patients hospitalized for HF declined from 21 to 7 (P = 0.005), and the hospitalization length of stay diminished from average 16 to 7 days (P = 0.079). Subgroup analysis showed similar results (P = 0.888) for patients receiving cardiac resynchronization therapy during the pre-activation period or not receiving cardiac resynchronization therapy, meaning that the effect of hospitalizations cannot solely be attributed to reverse remodelling. Subanalysis of a single-centre Belgian subpopulation showed important reductions in overall health economic costs (P = 0.025). CONCLUSION: Activation of the HeartLogic algorithm enables remote monitoring of HF patients, coincides with a significant reduction in hospitalizations for decompensated HF, and results in health economic benefits.

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-in collaboration with the European Heart Rhythm Association, European Association of Preventive Cardiology, Association of Cardiovascular Nursing and Allied Professionals, Patient Forum, and the Digital Health Committee.

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 (HR) and activity tracking, in clinical cardiovascular healthcare to support their implementation into clinical care. The widespread use of HR 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 HR tracking especially during activity need to be further validated. How to analyse, 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.

Potential of eHealth smart technology in optimization and monitoring of heart failure treatment in adults with systemic right ventricular failure.

Aims: Patients with a systemic right ventricle (sRV) in the context of transposition of the great arteries (TGA) after atrial switch or congenitally corrected TGA are prone to heart failure and arrhythmias. This study evaluated feasibility, patient adherence, and satisfaction of a smart technology-based care pathway for heart failure treatment optimization in these patients. Methods and results: Patients with symptomatic sRV failure eligible for initiation of sacubitril/valsartan were provided with four smartphone compatible devices (blood pressure monitor, weight scale, step counter, and rhythm monitor) and were managed according to a smart technology-based care pathway. Biweekly sacubitril/valsartan titration visits were replaced by electronical visits, patients were advised to continue measurements at least weekly after titration. Data of 24 consecutive sRV patients (median age 47 years, 50% female) who participated in the smart technology-based care pathway were analysed. Median home-hospital distance was 65 km (maximum 227 km). Most patients (20, 83.3%) submitted weekly measurements; 100% submitted prior to electronical visits. Titration conventionally occurs during a hospital visit. By implementing eHealth smart technology, 68 such trips to hospital were replaced by virtual visits facilitated by remote monitoring. An eHealth questionnaire was completed by 22 patients (92%), and 96% expressed satisfaction. After titration, 30 instances of remote adjustment of heart failure medication in addition to scheduled outpatient clinic visits occurred, one (4%) heart failure admission followed, despite ambulant adjustments. Five patients (21%) sent in rhythm registrations (n = 17), of these 77% showed sinus rhythm, whereas supraventricular tachycardia was detected in the remaining four registrations. Conclusion: These data suggest that implementation of a smart technology-based care pathway for optimization of medical treatment sRV failure is feasible with high measurement adherence and patient satisfaction.

Continuum of Care: Positioning of the Virtual Hospital.

Introduction: Patients with multiple chronic diseases suffer from reduced life expectancy. Care for these patients is often divided over multiple healthcare professionals. eHealth might help to integrate care for these patients and create a continuum. It is the primary purpose of this paper to describe an intervention that integrates first, second, and third line care in patients with multiple chronic conditions using remote monitoring, remote therapy and data automatization, all integrated in a virtual care center (VCC). Methods: Patients diagnosed with three or more chronic conditions are included and given smartphone compatible devices for remote monitoring and a tablet for video consultations. Patients will be followed-up by the VCC, consisting of nurses who will coordinate care, supervised by general practitioners and medical specialists. Data is reviewed on a daily basis and patients are contacted on a weekly basis. Review of data is automated by computer algorithms. Patients are contacted in case of outcome abnormalities in the data. Patients can contact the VCC at any time. Follow-up of the study is 1 year. Results: The primary outcome of this study is the median number of nights admitted to the hospital per patient compared to the hospitalization data 12 months before enrolment. Secondary outcomes include all-cause mortality, event free survival, quality of life and satisfaction with technology and care. Conclusion: This study presents the concept of a VCC that integrates first, second, and third line care into a virtual ward using remote monitoring and video consultation.