Bioimpedance Integration for Optimized Fluid Management in Decompensated Heart Failure

Heart Failure, Decompensated Heart Failure

Bioimpedance Analysis, Decompensated Heart Failure, Fluid Assessment

The goal of this clinical trial is to test whether using Bioimpedance Analysis (BIA) can help manage fluid levels in patients with heart failure who are admitted to the hospital with worsening symptoms. The main questions it aims to answer are: 1\. Does BIA-guided fluid management reduce the need for extra treatment (in the form of diuretics which helps remove excess fluid from the body) or re-hospitalization for heart failure within 90 days after discharge? Researchers will compare a group receiving BIA-guided treatment to a standard care group to see if BIA provides better results in managing fluid levels. Participants will be randomly assigned to one of two groups: BIA-Guided Treatment Group: Have BIA measurements done within 24 hours of admission and throughout their hospital stay to guide diuretic treatment. Standard Care Group: Have BIA measurements taken at admission and discharge, but the results will not be shared with the clinical team, who will manage fluid levels as usual. All patients will attend a follow-up visit in 2-4 weeks after discharge where the patient will undergo standard health checks, blood tests, and a questionnaire about how heart failure affects their quality of life. The investigators will then compare both groups for the primary outcome measure, which is the rates of rehospitalisation or need for additional decongestive treatment, within 90 days of discharge from hospital.

SCIENTIFIC RATIONALE Heart failure (HF) is a global health challenge affecting over 64 million people, with rising prevalence. Managing HF effectively is crucial to improving outcomes, but assessing and managing fluid status remains a significant challenge. Fluid congestion is a common cause of symptoms and hospitalizations for acute decompensated heart failure (ADHF). National audits indicate many patients are discharged before achieving adequate decongestion, increasing the risk of readmission and worsening prognosis. Traditional methods, such as physical exams and imaging, correlate poorly with congestion. Conditions like obesity (BMI \>30) and kidney disease further reduce the accuracy of diagnostic tools, including echocardiography and biomarkers like NT-proBNP. Hospitalizations for decompensated HF are associated with worse prognosis, progressive cardiac dysfunction, and higher mortality, highlighting the need for improved in-hospital management and prevention of readmissions. Bioimpedance Analysis (BIA) is a promising non-invasive tool that measures body composition and fluid distribution, providing insights into total, intra-, and extracellular water. BIA is inexpensive, portable, and reproducible, making it suitable for regular clinical use. Studies suggest BIA-guided therapy may improve fluid management and reduce NT-proBNP levels, potentially enhancing outcomes. This study aims to evaluate BIA's effectiveness in guiding fluid management in hospitalized HF patients with worsening symptoms. By enabling precise fluid assessment, BIA could optimize diuretic therapy and improve patient outcomes. PRIMARY RESEARCH OBJECTIVE The principal research objective is to determine if BIA guided management of heart failure inpatients, compared to usual standard of care, results in a reduction in heart failure events within 90 days post discharge. A heart failure event is defined as an outpatient requirement to increase oral diuretics or hospitalization for intravenous diuretics, due to decompensated heart. SECONDARY RESEARCH OBJECTIVE The secondary objectives are to determine if BIA guided management of heart failure inpatients, compared to usual standard of care, results in: 1. A higher rate of Acute Kidney Injury (defined by serum creatinine increase by (defined \>=1.5 and \<2 fold increase from baseline at any time) 2. A longer hospital Length of Stay including within a virtual ward. 3. A reduction in NTproBNP at 2-4 weeks after discharge from hospital. 4. An improvement in Patient Reported Outcomes (KCCQ-12), 2-4 weeks after discharge from hospital. 5. A lower rate of heart failure related events within 3, 6 months and 12 months. 6. A lower rate of All-cause mortality at 12 months STUDY DESIGN This study is a single-centre, single-blinded, randomized controlled trial designed to evaluate the effectiveness of bioimpedance analysis (BIA) in guiding fluid management in patients who are hospitalized with acute decompensated heart failure (ADHF). The study aims to compare the outcomes of BIA-guided therapy versus standard care in terms of fluid management and HF-related outcomes. PATIENT COHORT Eligible participants would include patients hospitalized for the management of Acute Decompensated Heart failure (ADHF), at Basildon and Thurrock University Hospital. All patients would be enrolled in the outpatients heart failure disease management programme. Consent Potential participants will be identified and screened by the direct clinical team. If patients fulfil the eligibility criteria they will be approached by a member of their clinical care team. The clinical team will briefly explain the study and provide the patient with an ethically approved patient information sheet. This document will outline the details of the study, including its purpose, what participation involves, and how the patient's information would be used. The potential participants would be offered at least 24 hours to review the information and will have the opportunity to ask questions and consider whether they are interested in participating. This approach ensures that potential participants are introduced to the study by trusted healthcare professionals with whom they already have a clinical relationship. If the patient expresses interest and agrees, the research team can follow up to obtain formal consent and enrol the patient in the study. The original consent form will be retained in the site file, a copy provided to the patient and a copy inserted into the patient medical notes. Randomization Participants provide consent will be randomized sequentially, in a 1:1 ratio using an online random number generator with an upper limit of 255, to either the BIA-guided therapy group or the standard care group. Odd-numbered patients will be assigned to the BIA-guided group (Group 1), and even-numbered patients will be assigned to the standard care group (Group 2). Interventions BIA-Guided Group Bioimpedance Analysis (BIA) will be performed within 24 hours of admission using the portable Bioscan touch i8 device (Maltron International, Essex, UK). BIA measurements will include total body water (TBW), intracellular water (ICW), extracellular water (ECW), and the derived parameter dry weight. Results are available at the bedside within 2 minutes. A member of the research team not involved in the patient's care will conduct the BIA and record the estimated dry weight in the patient's medical record. Diuretic therapy and other fluid management strategies will be adjusted based on the BIA estimated dry weight, in addition to standard clinical assessments, including physical examination, patient symptoms, and conventional diagnostic tools (e.g., chest X-ray, echocardiography), to achieve euvolaemia. BIA will also be performed at discharge for comparison to baseline results. Standard Care Group A member of the research team not involved in the patient's care will conduct the BIA and will record the estimated dry weight in the research records at 24 hours of admission and at discharge. These results would be blinded to clinicians managing the patient, who will aim to achieve euvolemia based on usual clinical judgement, discretion and conventional diagnostic tools. FOLLOW-UP All patients will be followed up in line with NICE guidelines for these patients, at 2-4 weeks post discharge. This will be conducted based on standard clinical assessments along with usual blood tests, to include NTproBNP. Furthermore, patients will be administered a quality-of-life questionnaire; Kansas City Cardiomyopathy Questionnaire (KCCQ-12); which is validated to assess symptoms, physical and social limitations, and quality of life in patients with heart failure, with respect to the preceding 2 weeks. Any additional contact with patients will be in line with routine clinical requirements. Outcomes will be recorded at pre-specified secondary endpoints. SAMPLE SIZE CALCULATION 30-180-day readmission for heart failure is reported between 10-25%. The investigators have determined that a sample size of 232 (116 for each group) provides a two-sided 95% confidence interval for the difference in the event proportions with a width that is equal to 0.2. This provides a reasonable estimate of clinical significance for this pilot study when the estimated event proportion for the control group is 20% and 10% for the intervention group. The sample size was increased to 255 (an added 10%) to allow for some loss of information due to early study discontinuation. DATA MANAGEMENT The data would be collected in an anonymized fashion and would be collated along with baseline demographic data as part of each hospital episode. The data would be analysed after 220 consecutive hospitalized patients have been entered into the study and each patient has been followed up for a minimum of 12 months. STATISTICAL ANALYSES Statistical analyses would be performed using commercial software. A statistical significance level of 0.05 will be used. Discrete variables would be expressed as n (%) and continuous variables as mean (SD) or median (interquartile range \[IQR\]). Comparisons between survivors and non-survivors will be done with the use of chi-square test and Fisher exact test for categoric variables and t test for continuous variables if normally distributed or Mann-Whitney test if not normally distributed. The Spearman rank correlation would used to perform correlation analyses. All hypothesis testing will be 2 tailed. Cumulative incidences will be analysed by the method of Kaplan-Meier and compared using the log-rank test. In addition, the relationship between several clinical variables would be tested in a multivariate Cox model to predict long- term mortality and this will be described with hazard ratios (HR) and 95% Confidence Intervals.

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