Quantitative Assessment of Fluid Accumulation Using Bioelectrical Impedance Analysis in Patients With Acute Decompensated Heart Failure

Abstract

Background: Acute decompensated heart failure (ADHF) is generally considered to be a problem of fluid volume overload, therefore accurately quantifying the degree of fluid accumulation is of critical importance in assessing whether adequate decongestion has been achieved. The aim of this study was to develop and validate a method to quantify the degree of fluid accumulation in patients with ADHF.

Methods and Results: Using multi-frequency bioelectrical impedance analysis (BIA), we measured extracellular water (ECW) volume in 130 ADHF patients on admission and at discharge. We also predicted optimal ECW volume using original equations based on data from 60 control subjects without the signs of HF. Measured/predicted (M/P) ratio of ECW in ADHF patients was observed to decrease from 1.26±0.25 to 1.04±0.17 during hospitalization (P<0.001). The amount of ECW volume reduction was significantly correlated with reduction in body weight (r=0.766, P<0.001). On multivariate analysis, higher M/P ratio of ECW at discharge was associated with increased risk of ADHF readmission or cardiac death within 6 months after discharge.

Conclusions: Multi-frequency BIA-measured ECW was found to offer valuable information for analyzing the pathophysiology of ADHF, and may be a useful guide in the management of this disease.

A cute decompensated heart failure (ADHF) is generally considered to be a problem of fluid volume overload accompanied by increased ventricular filling pressure with or without low cardiac output.¹ In addition, previous studies have shown fluid volume overload to be the principal factor causing hospitalization in patients with ADHF,^2–6 despite the other mechanisms that are also implicated in its pathogenesis. The treatment of ADHF usually involves systemic and pulmonary decongestion while avoiding intravascular underfilling and detrimental neurohumoral upregulation.⁷ For this reason, accurate quantification of the degree of fluid accumulation in each ADHF patient is of critical importance in assessing whether adequate decongestion has been achieved. Although there are several methods currently available for assessing fluid accumulation in ADHF patients, these allow only qualitative evaluation and are therefore inadequate for supporting effective ADHF management.¹

Bioelectrical impedance analysis (BIA) has been proposed as a tool for clinical body fluid evaluation, because it is a safe, non-invasive, rapid, reproducible, and relatively affordable option.^8–11 Because electrical current at low frequency is unable to pass through the cell membrane (which acts as a capacitor), extracellular water (ECW) volume is theoretically inversely proportional to resistance at very low-frequency (<1 kHz) current. Impedance meters using surface electrodes, however, are limited to a frequency range of 5–1,000 kHz. ECW measurement therefore requires extrapolation to negate the capacitive behavior of the cell membrane. A multi-frequency BIA method has been developed to derive ECW volume from impedance data obtained using currents with different frequencies.¹² This method is reported to facilitate the assessment of changes in body fluid volume with a reasonably low margin of error in dialyzed patients¹³ and critically ill patients,¹⁴ but there is a lack of clinical data on the applicability of this technology to the assessment of fluid overload in ADHF patients.

The aim of this study was to develop and validate a method to quantify the degree of fluid accumulation in ADHF patients using multi-frequency BIA to support the management of this disease.

Methods

Subjects

This study was approved by the institutional ethics review committee of Osaka National Hospital. The study sample consisted of 130 consecutive patients admitted with a primary diagnosis of ADHF who had been referred for intensive medical therapy between July 2012 and December 2014. ADHF was defined as new-onset decompensated HF or decompensation of chronic HF with symptoms that warrant hospitalization. All patients were admitted with clinical and radiographic evidence of congestion.¹ Patients with cardiogenic shock, defined as systolic blood pressure on admission <90 mmHg; serum creatinine >3.0 mg/dl; or those who had died during hospitalization were excluded from analysis. We ascertained if each patient had been admitted for ADHF within the past 12 months prior to the index admission.

For the control sample, we selected 60 patients who had been admitted to hospital for non-cardiac disease and did not have any signs or symptoms of HF. The control subjects were matched with the study subjects according to age and sex.

BIA

Bioelectrical impedance data for each patient were obtained using the BioScan 920-2 analyzer (Maltron International, Rayleigh, Essex, UK). The device has 8 electrodes: 4 electrodes were attached to each subject’s bilateral upper extremities (the dorsum of the wrists and third metacarpi), and the remaining 4 electrodes were attached to their bilateral lower extremities (the anterior surface of the ankles and the dorsum of the third metatarsi). Low-amplitude current at 4 different frequencies (5 kHz, 50 kHz, 100 kHz, and 200 kHz) was applied through the electrodes, and ECW was derived from the 4 sets of impedance data.

Development of Fluid Accumulation Index Using BIA

In order to validate the accuracy of the ECW measurements, we compared ECW in the control subjects measured using the BioScan analyzer and that predicted calculated using Moore’s body composition regression equations, which are based on the radioisotopic dilution method:

Men:

TBW=0.7945(wt)–0.0024(wt)²–0.0015(age)(wt)

ICW=0.623(TBW)–0.0016(age)(TBW)

ECW=TBW–ICW

Women:

TBW=0.6981(wt)–0.0026(wt)²–0.0012(age)(wt)

ICW=0.553(TBW)–0.0007(age)(TBW)

ECW=TBW–ICW

where wt is body weight, TBW is total body water, ICW is intracellular water, and ECW is extracellular water.^15,16

Using the measured values in control subjects, we then developed original regression equations via multivariate analysis that incorporate height, body weight, age, and sex to predict ECW in the normovolemic state of Japanese subjects.

In patients with ADHF, ECW was measured with the BioScan analyzer on admission and at discharge, and predicted ECW using the newly developed equations was also determined at each phase. The ratio of measured (M) to predicted (P) ECW (M/P ratio of ECW) was calculated as an index of the degree of fluid accumulation in ADHF patients.

Response to Medical Therapy During Hospitalization

All patients were treated at the direction of the treating physicians according to Japanese ADHF guidelines. B-type natriuretic peptide (BNP), serum creatinine, urea nitrogen, sodium, potassium, albumin, and hemoglobin were recorded on admission and immediately prior to discharge from hospital. Left ventricular ejection fraction (LVEF) was measured using M-mode echocardiography. Low LVEF was defined as <50% in the recovery phase. Trans-tricuspid pressure gradient (TRPG), maximal diameter of the inferior vena cava (IVC), and respiratory change in IVC were determined on admission and immediately prior to discharge. Patients were discharged after the treating physician confirmed the restoration of clinical stability. Change in body weight during hospitalization was compared with change in M/P ratio of ECW.

Follow-up and Outcome Measures

Before discharge, all patients underwent medical and nurse examinations; patients and their families were also provided with comprehensive discharge education. The patients were then discharged with guideline-compliant pharmacologic therapy. Follow-up clinic visits were scheduled for every 2 or 4 weeks. Primary clinical outcome measures were cardiac death (death from HF, myocardial infarction, or sudden cardiac death) and readmission due to ADHF within 6 months after discharge.

Statistical Analysis

Data are expressed as mean±SD. Statistical significance was set at P<0.05. Relationships between variables were assessed using univariate linear regression analysis and Pearson’s correlation coefficients. Comparison of parameters between the control and ADHF groups was performed using paired or Student’s t-test, as appropriate. To predict ECW, multiple linear regression analysis was performed: ECW was included in the regression models as a dependent variable, and the independent variables were patient height, body weight, age, and sex. Cumulative survival estimates were calculated using the Kaplan-Meier method. Univariate and multivariate Cox regression analysis were used to determine independent relationships between the M/P ratio of ECW and other characteristics at discharge with the outcome measures. We included all of these factors in the first multivariate model, and applied a forward stepwise variable selection method (selection criteria: significance level for inclusion and exclusion of variables was set at P<0.05). The association of each variable with the outcome is expressed as a hazard ratio (HR) and 95% confidence interval (95% CI). Statistical analysis was performed using MedCalc for Windows, version 13.1.2.0 (MedCalc Software, Ostend, Belgium).

Results

Subject Characteristics

The clinical characteristics of the control subjects and ADHF patients are listed in Table 1. The mean age of the control subjects was 75±7 years, which was almost identical to that of the ADHF patients in the acute decompensated HF syndrome (ATTEND) registry in Japan.¹⁷ There were no significant differences in the incidence of comorbidities (eg, hypertension and diabetes mellitus) between the 2 groups.

Table 1. Subject Characteristics on Admission

	Control group (n=60)	ADHF group (n=130)	P-value
Sex (M/F)	30/30	72/58	0.489
Age (years)	75±7 (56–89)	74±11 (40–92)	0.249
Ischemic/non-ischemic	–	30/100	–
LVEF on admission (%)	–	45±19	–
Serum Cre on admission (mg/dl)	0.91±0.66	1.24±0.57	–
Body height on admission (cm)	158±9	158±10	0.995
Body weight on admission (kg)	57.3±9.8 (40–79)	59.8±16.2 (36–137)	0.195
BSA on admission (m2)	1.57±0.16	1.60±0.24	0.413
SBP on admission (mmHg)	124±14	137±33	–
DBP on admission (mmHg)	70±10	78±18	–
Heart rate on admission (beats/min)	73±11	89±26	–
Comorbidities
Hypertension	34 (57)	92 (71)	–
Diabetes	20 (33)	48 (37)	–
Atrial fibrillation	4 (6.7)	68 (52)	–
Medications
β-blockers	7 (12)	72 (55)	–
ACEI/ARB	16 (27)	73 (56)	–
MRA	2 (3)	40 (31)	–
Loop diuretics	6 (10)	87 (67)	–

Data given as mean±SD or n (%). –, not assessed. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; ADHF, acute decompensated heart failure; BSA, body surface area; Cre, creatinine; DBP, diastolic blood pressure; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonists; SBP, systolic blood pressure.

The number (and percentage) of patients given initial treatment and medication for ADHF are as follows: intubation, 8 (6.2%); non-invasive positive-pressure ventilation, 8 (6.2%); i.v. infusion of furosemide, 46 (35.4%); human atrial natriuretic peptide (carperitide), 82 (63.1%); nitroglycerine, 9 (6.9%); dobutamine, 31 (23.8%); and milrinone, 16 (12.3%).

Regression Equations to Predict ECW

In the control subjects, measured ECW was 13.2±1.8 L in men and 9.7±2.1 L in women, and had a high linear correlation with that calculated using the regression equations from Moore et al¹⁵ (r=0.850, P<0.001). After validating the BIA measurements, we developed original regression equations for the prediction of optimal ECW in Japanese patients. The results of multiple linear regression analysis of the control subjects are given in Table 2. The coefficient of determination (R²) of this model to predict ECW was 0.859. From these results, we derived the following regression equations to predict ECW from patient height, body weight, age, and sex:

Table 2. Multivariate Linear Regression Analysis for Control ECW

	B	SE	β	t	P-value
Intercept	−7.369
Height	11.849	2.429	0.550	4.879	<0.001
Weight	0.105	0.017	0.638	6.142	<0.001
Age	−0.086	0.019	−0.517	−4.482	<0.001
Men	1.115	0.424	0.334	2.630	0.011

β, standardized coefficient; B, partial regression coefficient; ECW, extracellular water; SE, standard error; t, t-test statistic.

Men:

ECW=11.849(Height)+0.105(Weight)–0.086(Age)–6.254

Women:

ECW=11.849(Height)+0.105(Weight)–0.086(Age)–7.369

Quantification of Body Fluid in ADHF Patients

Mean measured ECW in all ADHF patients on admission was 15.0±5.5 L (17.8±5.4 L in men and 11.5±3.2 L in women). Using the aforementioned regression equations, predicted ECW on admission was calculated to be 11.8±3.6 L, which was not statistically significantly different to that of the control subjects (Figure 1). In contrast, the measured values were significantly higher than the predicted values (P<0.001), indicating the presence of fluid accumulation on admission. Measured ECW significantly decreased from 15.0±5.5 L to 11.8±4.3 L during hospitalization (P<0.001). Mean M/P ratio of ECW, which indicates the degree of fluid accumulation, exceeded 1.2 (1.26±0.25) on admission but was reduced to approximately 1.0 (1.04±0.17) at discharge. Consequently, the M/P ratio of ECW at discharge was not statistically significantly different to that of the control subjects.

Figure 1.

Changes in measured and predicted extracellular water (ECW) and the degree of fluid accumulation during hospitalization in acute decompensated heart failure (ADHF) subjects. (Left) Whiskers, standard deviation; (Right) boxes, 75th and 25th percentiles; whiskers, maximum and minimum. M/P ratio of ECW, ratio of measured to predicted ECW. *P<0.001.

Changes in Other Clinical Parameters in ADHF Subjects

In all ADHF subjects, plasma BNP was observed to decrease significantly (653±586 pg/ml to 252±218 pg/ml, P<0.001), whereas potassium increased significantly (4.1±0.5 mEq/L to 4.5±0.5 mEq/L, P<0.001) during hospitalization. In addition, echocardiography showed significant reduction in TRPG (37±12 mmHg to 28±10 mmHg, P<0.001) and in IVC diameter (22±5 mm to 17±6 mm, P<0.001), while respiratory change increased significantly (23±18% to 45±20%, P<0.001). Body weight decreased by 5.1±3.3 kg (59.8±16.2 kg to 54.7±14.6 kg). The extent of decrease in body weight correlated with reduction in ECW (r=0.766, P<0.001; Figure 2). Table 3 lists the clinical parameters on admission for all patients and at discharge for the 2 groups of patients according to M/P ratio of ECW at discharge (≤1.0 or >1.0). When compared with patients with M/P ratio ≤1.0, those with M/P ratio >1.0 had clearly higher body weight and slightly higher serum sodium concentration; there were no significant differences observed in the other parameters.

Figure 2.

Relationship between changes in bioelectrical impedance analysis-measured extracellular water (ECW) and body weight loss during hospitalization.

Table 3. Clinical Parameters on Admission vs. at Discharge

	Admission	Discharge
	All patients	ECW M/P ratio at discharge		P-value
		≤1.0 (n=58)	>1.0 (n=72)
Body weight (kg)	59.8±16.2	51.1±16.9	57.7±11.8	0.014
Serum UN (mg/dl)	26±13	29±13	29±13	0.855
Serum Cre (mg/dl)	1.24±0.57	1.22±0.57	1.34±0.60	0.234
eGFR (ml/min/1.73 m2)	49±24	48±23	44±17	0.301
Serum sodium (mEq/L)	141±4	139±4	141±3	0.030
Serum potassium (mEq/L)	4.1±0.5	4.5±0.5	4.4±0.6	0.437
Serum albumin (g/dl)	3.7±0.4	3.7±0.5	3.7±0.5	0.625
Hemoglobin (g/dl)	12.0±2.5	12.2±2.3	11.9±2.0	0.581
BNP (pg/ml)	653±586	242±176	260±247	0.635
TRPG (mmHg)	37±12	28±8	28±11	0.954
IVC diameter (mm)	22±5	16±5	18±6	0.135
IVC respiratory change (%)	23±18	45±20	45±21	0.982

Data given as mean±SD. BNP, brain natriuretic peptide; ECW M/P ratio, ratio of measured to predicted extracellular water; eGFR, estimated glomerular filtration rate; IVC, inferior vena cava; TRPG, tricuspid regurgitation pressure gradient; UN, urea nitrogen. Other abbreviation as in Table 1.

Determinants of Outcome

The number of cardiac events within 6 months after discharge was 37; of these, 35 events were rehospitalizations for HF and the remaining 2 were cases of sudden cardiac death. As shown in Figure 3, on Kaplan-Meier curve analysis, M/P ratio of ECW at discharge >1.0 was significantly associated with higher 6-month event rate (43.1% vs 10.3%; HR, 5.280; 95% CI: 2.210–12.61, P<0.001). On multivariate Cox regression analysis the variables at discharge associated with increased risk of cardiac death or ADHF readmission within 6 months after discharge were prior ADHF admission and M/P ratio of ECW (Table 4).

Figure 3.

Kaplan-Meier analysis of cumulative incidence of cardiac death and readmission for acute decompensated heart failure. M/P ratio of ECW, ratio of measured to predicted extracellular water.

Table 4. Predictors of ADHF Readmission and Cardiac Death After Discharge

Variables at discharge	ADHF readmission and cardiac death
	Univariate HR (95% CI)	Univariate P-value
Age (years)	1.009 (0.979–1.039)	0.563
Prior ADHF admissions (last 12 months)	3.560 (1.868–6.786)	<0.001
β-blockers	1.567 (0.754–3.258)	0.232
ACEI/ARB	1.746 (0.858–3.552)	0.126
MRA	1.608 (0.811–3.189)	0.177
Serum UN (mg/dl)	1.023 (1.000–1.047)	0.051
Serum Cre per 0.1 mg/dl	1.045 (0.999–1.094)	0.057
eGFR (ml/min/1.73 m2)	0.978 (0.960–0.996)	0.016
Serum sodium (mEq/L)	1.045 (0.946–1.154)	0.391
Serum potassium (mEq/L)	1.177 (0.590–2.347)	0.645
Hemoglobin (g/dl)	0.808 (0.638–1.024)	0.079
BNP per 10 pg/ml	1.021 (1.008–1.034)	0.002
LVEF <50%	1.874 (0.774–4.534)	0.166
TRPG (mmHg)	1.021 (0.995–1.048)	0.124
IVC diameter >25 mm	2.434 (1.113–5.323)	0.027
IVC respiratory change <50%	1.873 (0.925–3.792)	0.083
ECW M/P ratio per 0.1 unit	1.473 (1.250–1.735)	<0.001
	Multivariate HR (95% CI)	Multivariate P-value
Prior ADHF admissions (last 12 months)	3.060 (1.047–8.942)	0.042
ECW M/P ratio per 0.1 unit	1.483 (1.200–1.834)	<0.001

HR, hazard ratio. Other abbreviations as in Tables 1,3.

Discussion

In this study, BIA-measured ECW in ADHF patients on admission was found to be substantially higher than the optimal level predicted from the present regression equations. During hospitalization, measured ECW gradually approached the predicted level, indicating a return to normovolemic state. A significant positive correlation was observed between ECW reduction and loss of body weight. In addition, M/P ratio of ECW at discharge was found to be an independent prognostic factor in ADHF patients.

The transition from compensated to decompensated HF is often accompanied by fluid retention.^18,19 The quantification of fluid accumulation is essential not only for the diagnosis of ADHF, but also for its management. Clinicians need to know body fluid volume in the compensated state in order to accurately quantify the amount of fluid accumulation in ADHF patients. TBW volume and ECW volume in patients with compensated systolic HF have been reported to be equal to those of normal subjects.^20,21 Therefore, we postulated that the ECW volumes in normal subjects can be substituted for those of ADHF patients in the compensated state. Moore et al had quantified body water volume in healthy individuals using the radioisotopic dilution method to generate regression equations based on patient weight, age, and sex.^15,16 The significant correlation between the present BIA-measured ECW and that calculated using the Moore et al regression equations in the control subjects verified the reliability of the BioScan measurements. We then developed original regression equations for estimating ECW based on height, body weight, age, and sex using BIA-measured ECW in the control subjects. As a result, we were able to demonstrate that ECW was higher than expected in patients with ADHF on admission. These results are consistent with previous reports indicating elevated ECW volume in patients with ADHF.^22–24

Therapy for ADHF in this study was associated with a weight loss of approximately 5 kg, and was accompanied by hemodynamic improvements such as decrease in plasma BNP, TRPG, and IVC diameter. In a study using single-frequency BIA, Coodley et al reported that 3 days of diuretic therapy with furosemide for congestive HF was associated with a mean weight loss of approximately 4 kg and significant decrease in TBW.²⁵ That study, however, was unable to demonstrate a statistically significant relationship between weight loss and decrease in TBW. They concluded that single-frequency BIA had limited clinical usefulness as a method of assessing decongestion, although it may have applications in tracking serial changes in individual patients or patient populations that are physiologically or metabolically homogeneous. In contrast, the present multi-frequency BIA method showed significant correlation between weight loss and decrease in ECW. This suggests that the degree of fluid accumulation is measured more accurately using multi-frequency BIA than the single-frequency method. Furthermore, the present ECW measurements showed that patients approached normovolemic level with treatment, and that M/P ratio approached 1.0 at discharge. This indicates that decongestion was achieved before discharge in most cases, and that the present M/P ratio-guided decongestion may be applied to optimize fluid management in patients with ADHF.

This study has shown that the M/P ratio of ECW at discharge is an independent prognostic factor in ADHF patients. Hypervolemia has been reported to be a marker of poor outcome,^26,27 and ACC/AHA guidelines recommend not discharging a patient until euvolemia has been achieved.²⁸ Hemoconcentration, which is identified by increase in hemoglobin, hematocrit, or plasma albumin indicating reduction in intravascular volume, has been suggested as a means of assessing changes in volume status.^29–31 These surrogate markers, however, lack adequate sensitivity and specificity. Miller and Mullan measured plasma volume using a radiolabeled-albumin dilution technique, and showed that total plasma volume varied widely in the extent of intravascular overload.³² In that study, plasma volume was reported to decrease marginally on diuretic therapy despite an approximate 7-kg reduction in body weight. The bulk of the observed volume reduction may have been from the interstitial space, which would explain the marginal reduction in plasma volume. Plasma volume is, therefore, inadequate as a surrogate marker of excess fluid retention in patients with ADHF. Although hypervolemia is usually defined as an abnormal increase in plasma volume, we may also consider hypervolemia to be an expansion of extracellular volume, including the volume of both intravascular and extravascular spaces. Given that ECW in patients with compensated HF is reported to be equivalent to that of normal subjects,^20,21 and also that M/P ratio before discharge in this study was found to be nearly equal to 1.0, we propose that ECW could be a suitable surrogate marker for fluid status assessment.

Common surrogate markers include the presence or absence of elevated jugular venous pressure, dyspnea, peripheral edema, S3, or hepatojugular reflux, and are considered the mainstays of clinical evaluation of intravascular volume. Hemoconcentration or change in IVC diameter are also useful surrogate markers to monitor intravascular volume. The new method proposed here for volume assessment, however, is quantitative, non-invasive, rapid, and repeatable, which are all advantages in the evaluation of volume overload.

The high incidence of rehospitalization for HF (as a post-discharge cardiovascular event) observed in patients with M/P ratio >1.0 suggests a relationship between rehospitalization for HF and inadequate decongestion during the initial hospitalization. This implies that patients with ADHF should be discharged without volume overload. It should also be noted, however, that normovolemia is not the only factor that would prevent post-discharge cardiovascular events.

This study has several limitations. Although ECW volume was predicted using an equation generated in subjects without HF, this prediction may still be considered valid because ECW volume in compensated HF patients has been documented to be equivalent to that in normal subjects.^20,21 In addition, we calculated control ECW of ADHF patients using equations involving patient height, body weight, age, and sex. Because we could use only actual body weight on admission for these calculations, predicted ECW on admission would invariably be overestimated, while the M/P ratio of ECW would be correspondingly underestimated. The significantly higher M/P ratio on admission, however, indicates the need for dehydration. Given that body weight usually approaches that of the compensated state of HF throughout treatment, the estimated M/P ratio of ECW at discharge can be considered to be indicative of the actual level. Next, the underlying principle of the BIA method is that the resistance of the body to an electrical current is proportional to the degree of fat-free mass in young or middle-aged adults.³³ The variability in fat-free mass hydration in the elderly has been reported to be larger than in younger individuals, which may decrease the accuracy of the BIA method for this demographic.³⁴ In this study, however, we observed a high level of agreement between BIA-measured ECW and that calculated using the Moore et al equations, despite using older individuals as control subjects. Further validation studies are needed to evaluate the clinical usefulness of the present method for quantifying the degree of fluid accumulation in a wide range of ADHF patients.

Conclusions

Multi-frequency BIA-measured ECW is a useful quantitative surrogate marker of fluid accumulation in patients with ADHF. M/P ratio of ECW at discharge was found to be an independent prognostic factor of post-discharge outcome. The simple methods proposed in this study offer valuable information with regard to analysis of the pathophysiology of ADHF and provide useful support for its management.

Funding

The authors received no external funding for this study.

Conflicts of Interest

None.

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