- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02126254
Optimization of the Treatment of Acute HF by a Non Invasive Cardiac System-a Randomized Control Trial (HFNICAS)
Optimization of the Treatment of Acute Heart Failure by a Non Invasive Cardiac System-Randomized Control Trial
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Heart failure is a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood. Although survival has improved, the absolute mortality rates for HF remain approximately 50% within 5 years of diagnosis. In the ARIC study, the 30-day, 1-year, and 5-year mortallity rates after hospitalization for HF were 10.4%, 22%, and 42.3%, respectively. HF represents a major burden in the developed world. In the United States, HF is the primary diagnosis for more than 1 million hospitalized patients annually. A significant number of patients with acute decompensated heart failure have baseline renal insufficiency. Yet perhaps more important is the change of renal function during hospitalization. Gottlieb et al. have shown that even a small increase in serum creatinine, e.g., 0.1 mg/dl will worsen the outcome of the patients. It is also noteworthy that a significant rise in serum Cr generally may occur in the first 3 d of the admission to the hospital. The mortality rate in ADHERE registry is 4% for all the patients; however, the mortality of patients with significant renal insufficiency, i.e., Cr >3 mg/dl, is 9.4%, and the length of hospital stay is also lengthened as compared with those who do not have renal insufficiency. In another study of 1681 patients admitted for ADHF, Krumholz et al. found worsening renal function during hospitalization in 28% of patients. In-hospital mortality was more than double in those with versus without worsening renal function (7% versus 3%). This significant difference remained at 30 d (10% versus 6%) and 6 mo (25% versus 19%). The CHARM investigators also studied predictors of outcome in all three component trials in 2680 patients for an average of 34 mo. They found that every 10 ml/min decrease in eGFR increased the adjusted HR of cardiovascular death or readmission to the hospital by 10% (1.10, CI 1.07 to 1.13, P < 0.001). Therefore, even small changes in Cr have an important impact on in-patient mortality as well as postdischarge mortality.
Patients hospitalized for HF are at high risk for all-cause rehospitalization, with a 1-month readmission rate of 25% [4]. In 2013, physician office visits for HF cost $1.8 billion. The total cost of HF care in the United States exceeds $30 billion annually, with over half of these costs spent on hospitalizations [3]. Presently, HF is the leading cause of hospitalization among patients >65 years of age; the largest percentage of expenditures related to HF are directly attributable to hospital costs. Moreover, in addition to costs, hospitalization for acutely decompensated HF represents a sentinel prognostic event in the course of many patients with HF, with a high risk for recurrent hospitalization (50% at 6 months). Median length of in-hospital stay in the United States is approximately 4 days, whereas lengths of stay in Europe are generally markedly longer with a median of 9 days as reported in the EuroHeart Failure Survey II. Although systemic and pulmonary congestion is the main reason for hospitalization in most patients, many do not have a decrease in body weight during their hospital stay and are discharged with signs and symptoms of HF. Given that re-hospitalization drives much of the cost associated with HF, there has been increased interest in predicting risk of re-hospitalization as a means to control health care costs and reduce future risk. These risk stratification models can serve as important clinical tools by helping to identify those patients at both ends of the spectrum of risk; patients who are at very high risk may be observed more closely or treated more intensively, whereas patients at low risk may need less rigorous follow-up and monitoring. In the cohort from the OPTIMIZE-HF study with 60- to 90-day follow-up data, the most important predictors for the combined endpoint of death or re-hospitalization were admission serum creatinine concentration, systolic blood pressure, admission hemoglobin level, discharge use of ACE inhibitor or ARB, and pulmonary disease. In the EVEREST trial, composed of patients admitted with worsening HF and reduced ejection fraction, independent predictors during hospitalization of readmission and mortality included low admission Kansas City Cardiomyopathy Questionnaire score, high BNP, hyponatremia, tachycardia, hypotension, absence of beta blocker therapy, and history of diabetes and arrhythmias. Nevertheless, both models fail to provide the treating physician a simple decision making tool for predicting which patient is stable enough to be discharged from the hospital without a high risk of readmission. On this regard, high levels of BNP were found to be a reliable prognostic marker for HF patients readmission after discharge. Hospitalized patients with HF can be classified into important subgroups. These include patients with acute coronary ischemia, accelerated hypertension and acutely decompensated HF, shock, and acutely worsening right HF. Each of these various categories of HF has specific etiologic factors leading to decompensation, presentation, management, and outcomes. Noninvasive modalities can be used to classify the patient with hospitalized HF. The history and physical examination allows estimation of a patient's hemodynamic status, that is, the degree of congestion ("dry" versus "wet"), as well as the adequacy of their peripheral perfusion ("warm" versus "cold"). There have been limited previous randomized trials of therapy tailored during continuous hemodynamic monitoring in heart failure. Use of an indwelling pulmonary artery catheters to adjust therapy in advanced heart failure was first described by Kovick et al and subsequently by Pierpont for vasodilator therapy in decompensated heart failure with high systemic vascular resistance. There have been 11 additional randomized trials of PACs in critical care. A meta-analysis of these trials, including ESCAPE, showed that PAC was neutral in its effect on mortality and rehospitalization. These trials support the safety of PACs and the overall neutral effect, while highlighting the challenge of assessing a diagnostic tool without a consistent strategy of response with effective therapies. These results might be explained by the balance effect of improved treatment by tailored medicine that was counteracted by the invasive nature of PAC.
The Non-Invasive Cardiac System (NICaS: NI Medical, Hod-Hasharon, Israel), calculates the cardiac output (CO) by measuring whole body bio impedance in a tetra-polar mode, derived from electrodes placed on both wrists or one wrist and the contra-lateral ankle. This simple to operate, non-invasive technique was validated in several studies to be reliable in estimation of CO compared to traditional, invasive techniques in different settings including HF patients. A previous study demonstrated that parameters derived from this system showed a highly significant correlation to echocardiogram estimated ejection fraction and serum BNP in chronic HF patients and were equally able to predict complications in this population
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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-
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Tel Aviv, Israel
- Tel Aviv Medical Center
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Written informed consent.
- HF admitted patient from cardiology and internal medicine departments in our institution.
- Reduced EF ≤ 40%.
- Elevated filling pressures, indicated by one symptom AND one physical sign: Symptoms : Dyspnea at rest, in the supine position, OR immediately upon routine activity, abdominal discomfort, severe anorexia, or nausea without apparent cause other than hepatosplanchnic congestion Signs: Jugular venous pressure elevation >10 cm above the right atrium, hepatomegaly, ascites, or edema in the absence of other obvious causes, rales greater than 1/3 lung fields, oxygen saturation < 90 % in room air, pulmonary venous congestion determined from chest x-ray films
Exclusion Criteria:
- Severe aortic valve regurgitation and/or aortic stenosis.
- Aortic aneurysm.
- Heart rate above 130 beats/min.
- Intra- and extra-cardiac shunts.
- Severe peripheral vascular disease.
- Severe pitting edema.
- Sepsis.
- Use of hemodialysis.
- Patients under 18 years of age.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
No Intervention: Control group
Control group will be treated in the cardiology and internal medicine departments according to the guidelines for the management of Heart Failure
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Active Comparator: Hemodynamic group
Hemodynamic group patients will be examined in the cardiology and internal medicine departments and treated according to the NICaS system in addition to current guidelines.
Patients in this group will be tested within 12 hours from hospitalization and thereafter on an everyday basis until discharge
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NICAS guided treatment
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Renal function deterioration during hospitalization
Time Frame: 6 months
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Renal function deterioration during hospitalization - worsening renal function (defined as an increase in the serum creatinine level of more than 0.3 mg per deciliter) at any time from randomization to dischage.
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6 months
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
30 days rehospitalization due to decompensated heart failure
Time Frame: 30 days
|
30 days rehospitalization due to decompensated heart failure
|
30 days
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Length of hospitalization
Time Frame: 3 months
|
Length of hospitalization
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3 months
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All cause mortality at 30 days
Time Frame: 30 days
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All cause mortality at 30 days
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30 days
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All cause mortality at 3 months
Time Frame: 3 months
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All cause mortality at 3 months
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3 months
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All cause rehospitalization at 3 months
Time Frame: 3 months
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All cause rehospitalization at 3 months
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3 months
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Heart failure rehospitalization at 3 months
Time Frame: 3 months
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Heart failure rehospitalization at 3 months
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3 months
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Weight Loss during hospitalization - changes in body weight and net fluid loss
Time Frame: 5 days
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Weight Loss during hospitalization - changes in body weight and net fluid loss
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5 days
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Health-Related Quality of Life and Functional Status - patient-reported dyspnea
Time Frame: 3 months
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Health-Related Quality of Life and Functional Status - patient-reported dyspnea
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3 months
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Usage of mechanical ventilation
Time Frame: 5 days
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Usage of mechanical ventilation
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5 days
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Change in BNP/ pro-BNP from baseline to discharge Peak Troponin during the hospitalization
Time Frame: 5 days
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Change in BNP/ pro-BNP from baseline to discharge Peak Troponin during the hospitalization
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5 days
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Free from congestion (defined as jugular venous pressure of <8 cm, with no orthopnea and with trace peripheral edema or no edema) at 72 hours
Time Frame: 72 hours
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Free from congestion (defined as jugular venous pressure of <8 cm, with no orthopnea and with trace peripheral edema or no edema) at 72 hours
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72 hours
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Emergency room visit within 60 days
Time Frame: 60 days
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Emergency room visit within 60 days
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60 days
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Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Principal Investigator: Yaron Arbel, MD, Tel Aviv Medical Center
Study record dates
Study Major Dates
Study Start
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimate)
Study Record Updates
Last Update Posted (Estimate)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- TASMC-14-YA-055-CTIL
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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