Heart rate and blood pressure monitoring in heart failure.

It has been long known that incessant tachycardia and severe hypertension can cause heart failure (HF). In recent years, it has also been recognized that more modest elevations in either heart rate (HR) or blood pressure (BP), if sustained, can be a risk factor both for the development of HF and for mortality in patients with established HF. Heart rate and BP are thus both modifiable risk factors in the setting of HF. What is less clear is the question whether routine systematic monitoring of these simple physiological parameters to a target value can offer clinical benefits. Measuring these parameters clinically during patient review is recommended in HF management in most HF guidelines, both in the acute and chronic phases of the disease. More sophisticated systems now allow long-term automatic or remote monitoring of HR and BP and whether this more detailed patient information can improve clinical outcomes will require prospective RCTs to evaluate. In addition, analysis of patterns of both HR and BP variability can give insights into autonomic function, which is also frequently abnormal in HF. This window into autonomic dysfunction in our HF patients can also provide further independent prognostic information and may in itself be target for future interventional therapies. This article, developed during a consensus meeting of the Heart Failure Association of the ESC concerning the role of physiological monitoring in the complex multi-morbid HF patient, highlights the importance of repeated assessment of HR and BP in HF, and reviews gaps in our knowledge and potential future directions

Renal function, electrolytes, and congestion monitoring in heart failure.

Congestion, renal function, and electrolyte imbalance (particularly potassium) are common problems in the management of the complex multi-morbid patient with heart failure (HF). Poor control of these fundamental clinical features is associated with adverse outcomes. Close monitoring of serum potassium and renal function is recommended by most current guidelines during the management of an episode of acute decompensated HF, yet the recommendations remain poorly implemented. Physicians are advised to treat a state of euvolaemia after an admission with decompensated HF and residual congestion is a marker of worse outcome, yet control of congestion is poorly assessed and managed in real-world practice. This document reflects the key points discussed by a panel of experts during a Heart Failure Association meeting on physiological monitoring of the complex multi-morbid HF patient, and here, we present to aspects related to renal function, electrolyte, and congestion monitoring

The effects of short-term omission of daily medication on the pathophysiology of heart failure

Aims Pharmacological therapies for heart failure (HF) aim to improve congestion, symptoms, and prognosis. Failing to take medication is a potential cause of worsening HF. Characterizing the effects of short-term medication omission could inform the development of better technologies and strategies to detect and interpret the reasons for worsening HF. We examined the effect of planned HF medication omission for 48 h on weight, echocardiograms, transthoracic bio-impedance, and plasma concentrations of NT-proBNP. Methods and results Outpatients with stable HF and an LVEF <45% were assigned to take or omit their HF medication for 48 h in a randomized, crossover trial. Twenty patients (16 men, LVEF 32 ± 9%, median NT-proBNP 962 ng/L) were included. Compared with regular medication, omission led to an increase in NT-proBNP by 99% (from 962 to 1883 ng/L, P < 0.001), systolic blood pressure by 16% (from 131 to 152 mmHg, P < 0.001), and left atrial volume by 21% (from 69 to 80 mL, P = 0.001), and reductions in transthoracic bio-impedance by 10% (from 33 to 30 Σ, P = 0.001) and serum creatinine by 8% (from 135 to 118 µmol/L, P = 0.012). No significant changes in body weight, heart rate, or LVEF were observed. Conclusions The characteristic pattern of response to short-term medication omission is of increasing congestion but, in contrast to the pattern reported for disease progression, with a rise in blood pressure and improved renal function. In stable HF, weight is not a sensitive marker of short-term diuretic omission

Telemonitoring after discharge from hospital with heart failure: cost-effectiveness modelling of alternative service designs.

Objectives To estimate the cost-effectiveness of remote monitoring strategies versus usual care for adults recently discharged after a heart failure (HF) exacerbation. Design Decision analysis modelling of cost-effectiveness using secondary data sources. Setting Acute hospitals in the UK. Patients Patients recently discharged (within 28 days) after a HF exacerbation. Interventions Structured telephone support (STS) via human to machine (STS HM) interface, (2) STS via human to human (STS HH) contact and (3) home telemonitoring (TM), compared with (4) usual care. Main outcome measures The incremental cost per quality-adjusted life year (QALY) gained by each strategy compared to the next most effective alternative and the probability of each strategy being cost-effective at varying willingness to pay per QALY gained. Results TM was the most cost-effective strategy in the scenario using these base case costs. Compared with usual care, TM had an estimated incremental cost effectiveness ratio (ICER) of £11 873/QALY, whereas STS HH had an ICER of £228 035/QALY against TM. STS HM was dominated by usual care. Threshold analysis suggested that the monthly cost of TM has to be higher than £390 to have an ICER greater than £20 000/QALY against STS HH. Scenario analyses performed using higher costs of usual care, higher costs of STS HH and lower costs of TM do not substantially change the conclusions. Conclusions Cost-effectiveness analyses suggest that TM was an optimal strategy in most scenarios, but there is considerable uncertainty in relation to clear descriptions of the interventions and robust estimation of costs

Systems of Preventive Cardiological Monitoring: Models, Algorithms, First Results, and Perspectives

The results of work on creating methods, models, and computational algorithms for remote preventive health-monitoring systems are presented, in particular, cardiac preventive monitoring. The main attention is paid to the models and computational algorithms of preventive monitoring, the interaction of the computing kernels of a remote cluster with portable ECG recorders, implantable devices, and sensors. Computational kernels of preventive monitoring are a set of several thousand interacting automata of analog of Turing machines, recognizing the characteristic features and evolution of the hidden predictors of atrial fibrillation(AF), ventricular tachycardia or fibrillation (VT-VF), sudden cardiac death, and heart failure (HF) revealed by them. The estimation of the time for reaching the heart events boundaries is calculated on the basis of the evolution equations for the ECG multi-trajectories determined by recognizing automata. Evaluation time of heart event (HE) boundaries to achieve is calculated on the basis of the evolution equations for ECG multi-paths defined by recognizing machines. Ultimately, the computational cores reconstruct the ECG of the forecast and give temporary estimates of its achievement. Cloud computing cluster supports low-cost ECG ultra-portable recorders and does not limit the possibilities of using a more complex patient telemetry containing wearable and implantable devices: CRT and ICD, CardioMEMS HF System, and so on