scholarly journals Influential Factors in Remote Monitoring of Heart Failure Patients: A Review of the Literature and Direction for Future Research

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3575
Author(s):  
Sashini Senarath ◽  
Geoff Fernie ◽  
Atena Roshan Fekr
Keyword(s):  
Heart Failure ◽  
Remote Monitoring ◽  
Influential Factors ◽  
Future Research ◽  
False Alarms ◽  
Cardiac Events ◽  
Readmission Rates ◽  
Daily Monitoring ◽  
Multiple Parameters ◽  
Physiological Variables

With new advances in technology, remote monitoring of heart failure (HF) patients has become increasingly prevalent and has the potential to greatly enhance the outcome of care. Many studies have focused on implementing systems for the management of HF by analyzing physiological signals for the early detection of HF decompensation. This paper reviews recent literature exploring significant physiological variables, compares their reliability in predicting HF-related events, and examines the findings according to the monitored variables used such as body weight, bio-impedance, blood pressure, heart rate, and respiration rate. The reviewed studies identified correlations between the monitored variables and the number of alarms, HF-related events, and/or readmission rates. It was observed that the most promising results came from studies that used a combination of multiple parameters, compared to using an individual variable. The main challenges discussed include inaccurate data collection leading to contradictory outcomes from different studies, compliance with daily monitoring, and consideration of additional factors such as physical activity and diet. The findings demonstrate the need for a shared remote monitoring platform which can lead to a significant reduction of false alarms and help in collecting reliable data from the patients for clinical use especially for the prevention of cardiac events.

scholarly journals Remote monitoring of patients with heart failure during the first national lockdown for COVID-19 in France

2021 ◽  
Author(s):  
Sylvain Ploux ◽  
Marc Strik ◽  
Saer Abu-Alrub ◽  
F Daniel Ramirez ◽  
Samuel Buliard ◽  
...  
Keyword(s):  
Heart Failure ◽  
Health Care ◽  
Heart Rate ◽  
Remote Monitoring ◽  
Marked Decrease ◽  
Clinical Status ◽  
Health Care Use ◽  
Physiological Variables ◽  
Patients With Heart Failure ◽  
Vital Parameters

Abstract Background Multiparametric remote monitoring of patients with heart failure (HF) has the potential to mitigate the health risks of lockdowns for COVID-19. Aims To compare health care use, physiological variables, and HF decompensations during one month before and during the first month of the first French national lockdown for COVID-19 among patients undergoing remote monitoring. Methods Transmitted vital parameters and data from cardiac implantable electronic devices were analyzed in 51 patients. Medical contact was defined as the sum of visits and days of hospitalization. Results The lockdown was associated with a marked decrease in cardiology medical contact (118 days before vs 26 days during, -77%, p = 0.003) and overall medical contact (180 days before vs 79 days during, -58%, p = 0.005). Patient adherence with remote monitoring was 84±21% before and 87±19% during lockdown. The lockdown was not associated with significant changes in various parameters, including physical activity (2±1 to 2±1 h/day), weight (83±16 to 83±16 kg), systolic blood pressure (121±19 to 121±18 mmHg), heart rate (68±10 to 67±10 bpm), heart rate variability (89±44 to 78±46 ms, p = 0.05), atrial fibrillation burden (84±146 vs 86±146 h/month), or thoracic impedance (66±8 to 66±9 Ω). Seven cases of HF decompensations were observed before lockdown, all but one of which required hospitalization, versus six during lockdown, all but one of which were managed remotely. Conclusions The lockdown restrictions caused a marked decrease in health care use but no significant change in the clinical status of HF patients under multiparametric remote monitoring. lay summary The first French COVID-19 lockdown had a huge detrimental impact on conventional health care use (-78% in cardiology medical contact). However the lockdown had little impact over the short-term, if any, on vital parameters and the clinical status of patients with heart failure who were adherent to multiparametric remote monitoring. This remote monitoring strategy allowed early identification and home management of most of the heart failure decompensations during the lockdown.

P4537Impact of body composition analysis on prediction of short-term readmission events in heart failure: muscle wasting vs. obesity

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K Ohori ◽  
T Yano ◽  
S Katano ◽  
S Honma ◽  
K Shimomura ◽  
...  
Keyword(s):  
Heart Failure ◽  
Body Composition ◽  
Muscle Wasting ◽  
Functional Class ◽  
Composition Analysis ◽  
Class Iii ◽  
Cardiac Events ◽  
Short Term ◽  
Readmission Rates

Abstract Background Obesity, defined as higher body mass index (BMI), is associated with better prognosis in patients with chronic heart failure (CHF), though the presence of obesity is a risk factor of development of CHF (Obesity paradox). On the other hand, muscle wasting, i.e. reduction in skeletal muscle mass, is frequently observed in CHF, leading to lower exercise capacity and poor cardiovascular outcome. Purpose The aim of this study was to examine whether analysis of body composition improves prediction of short-term readmission rates in patients with CHF. Methods We retrospectively analyzed data for 167 consecutive HF patients who were admitted to our institute for management of HF and received a Dual-energy X-ray absorptiometry (DEXA) scan. Muscle wasting was defined as DEXA-measured appendicular skeletal muscle mass index <7.0 kg/m2 in male and <5.4 kg/m2 in female according to the Asian Working Group for Sarcopenia criteria. Obesity was defined according to the criteria by the use of DEXA-measured percent body fat mass: >25% in male, >30% in female. The primary endpoint was readmission due to cardiac events including worsening heart failure, arrhythmia, and cardiopulmonary arrest during a 180-days follow-up period after discharge. Results The mean age of the patients was 74±13 years and 46% of them were male. The mean BMI was 21.8±3.8 kg/m2. Forty-seven percent of the patients were classified as NYHA functional class III. The most frequent etiology of HF was cardiomyopathy (30%), followed by ischemic heart disease (27%) and valvular heart disease (27%). The prevalence of muscle wasting and that of obesity were 69% and 59%, respectively. Patients with muscle wasting had lower BMI level, higher prevalence of NYHA functional class III and diabetes mellitus compared with those without muscle wasting. On the other hand, patients with obesity had higher prevalence of hypertension and dyslipidemia, higher level of BMI, fasting plasma insulin and triglyceride, and lower level of HDL-cholesterol compared with those without obesity. During the follow-up period, 34 patients (19%) were re-hospitalized due to cardiac events. Kaplan-Meier survival curves showed that patients with obesity had a significantly lower readmission rate during a 180-days follow-up period than did the patients without obesity (14.3% vs. 29.0%, Log-Rank test, p<0.01). There was no difference in readmission rates between patients with and without muscle wasting (20.0% vs. 21.2%, p=0.88). In multivariate Cox regression analyses adjusted for age, sex, diabetes, and renal function, obesity was independently associated with lower readmission rates (hazard ratio 0.45, 95% confidence interval 0.22–0.93). However, the association between obesity and readmission rate was lost after the adjustment for NT-proBNP levels. Conclusion Body composition analysis by DEXA enables to find CHF patients with increased fat mass who have lower risk of short-term readmission.

Assessing Acute Decompensated Heart Failure – Strategies and Tools

2012 ◽  
Vol 8 (2) ◽  
pp. 128
Author(s):  
Ali Vazir ◽  
Martin R Cowie ◽  
◽  
Keyword(s):  
Heart Failure ◽  
Acute Decompensated Heart Failure ◽  
Pulse Contour Analysis ◽  
Decompensated Heart Failure ◽  
Rapid Onset ◽  
Clinical Syndrome ◽  
Response To Therapy ◽  
Contour Analysis ◽  
Physiological Variables ◽  
Co Morbidity

Acute heart failure – the rapid onset of, or change in, signs and/or symptoms of heart failure requiring urgent treatment – is a serious clinical syndrome, associated with high mortality and healthcare costs. History, physical examination and early 2D and Doppler echocardiography are crucial to the proper assessment of patients, and will help determine the appropriate monitoring and management strategy. Most patients are elderly and have considerable co-morbidity. Clinical assessment is key to monitoring progress, but a number of clinical techniques – including simple Doppler and echocardiographic tools, pulse contour analysis and impedance cardiography – can help assess the response to therapy. A pulmonary artery catheter is not a routine monitoring tool, but can be very useful in patients with complex physiology, in those who fail to respond to therapy as would be anticipated, or in those being considered for mechanical intervention. As yet, the serial measurement of plasma natriuretic peptides is of limited value, but it does have a role in diagnosis and prognostication. Increasingly, the remote monitoring of physiological variables by completely implanted devices is possible, but the place of such technology in clinical practice is yet to be clearly established.

scholarly journals High percent body fat mass predicts lower risk of cardiac events in patients with heart failure: an explanation of the obesity paradox

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katsuhiko Ohori ◽  
Toshiyuki Yano ◽  
Satoshi Katano ◽  
Hidemichi Kouzu ◽  
Suguru Honma ◽  
...  
Keyword(s):  
Heart Failure ◽  
Body Fat ◽  
Fat Mass ◽  
Cardiac Event ◽  
Muscle Wasting ◽  
Obesity Paradox ◽  
Percent Body Fat ◽  
Body Fat Mass ◽  
Cardiac Events ◽  
Kaplan Meier

Abstract Background Although high body mass index (BMI) is a risk factor of heart failure (HF), HF patients with a higher BMI had a lower mortality rate than that in HF patients with normal or lower BMI, a phenomenon that has been termed the “obesity paradox”. However, the relationship between body composition, i.e., fat or muscle mass, and clinical outcome in HF remains unclear. Methods We retrospectively analyzed data for 198 consecutive HF patients (76 years of age; males, 49%). Patients who were admitted to our institute for diagnosis and management of HF and received a dual-energy X-ray absorptiometry scan were included regardless of left ventricular ejection fraction (LVEF) categories. Muscle wasting was defined as appendicular skeletal muscle mass index < 7.0 kg/m2 in males and < 5.4 kg/m2 in females. Increased percent body fat mass (increased FM) was defined as percent body fat > 25% in males and > 30% in females. Results The median age of the patients was 76 years (interquartile range [IQR], 67–82 years) and 49% of them were male. The median LVEF was 47% (IQR, 33–63%) and 33% of the patients had heart failure with reduced ejection fraction. Increased FM and muscle wasting were observed in 58 and 67% of the enrolled patients, respectively. During a 180-day follow-up period, 32 patients (16%) had cardiac events defined as cardiac death or readmission by worsening HF or arrhythmia. Kaplan-Meier survival curves showed that patients with increased FM had a lower cardiac event rate than did patients without increased FM (11.4% vs. 22.6%, p = 0.03). Kaplan-Meier curves of cardiac event rates did not differ between patients with and those without muscle wasting (16.5% vs. 15.4%, p = 0.93). In multivariate Cox regression analyses, increased FM was independently associated with lower cardiac event rates (hazard ratio: 0.45, 95% confidence interval: 0.22–0.93) after adjustment for age, sex, diabetes, muscle wasting, and renal function. Conclusions High percent body fat mass is associated with lower risk of short-term cardiac events in HF patients.

Length of Stay and Readmission Rates in Pediatric Acute Heart Failure

2021 ◽  
Vol 40 (4) ◽  
pp. S122-S123
Author(s):  
D.S. Burstein ◽  
C. Connelly ◽  
C.S. Almond ◽  
R.A. Niebler ◽  
J.A. Godown ◽  
...  
Keyword(s):  
Heart Failure ◽  
Length Of Stay ◽  
Acute Heart Failure ◽  
Readmission Rates

External validation of a heart failure risk prediction model in a remote monitoring cohort submitted to cardiac resynchronization therapy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Cardoso ◽  
M Coutinho ◽  
G Portugal ◽  
A Valentim ◽  
A.S Delgado ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
High Risk ◽  
Remote Monitoring ◽  
Hospital Admissions ◽  
External Validation ◽  
Left Ventricular Ejection ◽  
National Database ◽  
Failure Risk

Abstract Background Patients (P) submitted to cardiac ressynchronization therapy (CRT) are at high risk of heart failure (HF) events during follow-up. Continuous analysis of various physiological parameters, as reported by remote monitoring (RM), can contribute to point out incident HF admissions. Tailored evaluation, including multi-parameter modelling, may further increase the accuracy of such algorithms. Purpose Independent external validation of a commercially available algorithm (“Heart Failure Risk Status” HFRS, Medtronic, MN USA) in a cohort submitted to CRT implantation in a tertiary center. Methods Consecutive P submitted to CRT implantation between January 2013 and September 2019 who had regular RM transmissions were included. The HFRS algorithm includes OptiVol (Medtronic Plc., MN, USA), patient activity, night heart rate (NHR), heart rate variability (HRV), percentage of CRT pacing, atrial tachycardia/atrial fibrillation (AT/AF) burden, ventricular rate during AT/AF (VRAF), and detected arrhythmia episodes/therapy delivered. P were classified as low, medium or high risk. Hospital admissions were systematically assessed by use of a national database (“Plataforma de Dados de Saúde”). Accuracy of the HFRS algorithm was evaluated by random effects logistic regression for the outcome of unplanned hospital admission for HF in the 30 days following each transmission episode. Results 1108 transmissions of 35 CRT P, corresponding to 94 patient-years were assessed. Mean follow-up was 2.7 yrs. At implant, age was 67.6±9.8 yrs, left ventricular ejection fraction 28±7.8%, BNP 156.6±292.8 and NYHA class &gt;II in 46% of the P. Hospital admissions for HF were observed within 30 days in 9 transmissions. Stepwise increase in HFRS was significantly associated with higher risk of HF admission (odds ratio 12.7, CI 3.2–51.5). HFRS had good discrimination for HF events with receiving-operator curve AUC 0.812. Conclusions HFRS was significantly associated with incident HF admissions in a high-risk cohort. Prospective use of this algorithm may help guide HF therapy in CRT recipients. Funding Acknowledgement Type of funding source: None

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