Four-compartment cellular level body composition model: comparison of two approaches

Fluid balance concepts in medicine: Principles and practice

The regulation of body fluid balance is a key concern in health and disease and comprises three concepts. The first concept pertains to the relationship between total body water (TBW) and total effective solute and is expressed in terms of the tonicity of the body fluids. Disturbances in tonicity are the main factor responsible for changes in cell volume, which can critically affect brain cell function and survival. Solutes distributed almost exclusively in the extracellular compartment (mainly sodium salts) and in the intracellular compartment (mainly potassium salts) contribute to tonicity, while solutes distributed in TBW have no effect on tonicity. The second body fluid balance concept relates to the regulation and measurement of abnormalities of sodium salt balance and extracellular volume. Estimation of extracellular volume is more complex and error prone than measurement of TBW. A key function of extracellular volume, which is defined as the effective arterial blood volume (EABV), is to ensure adequate perfusion of cells and organs. Other factors, including cardiac output, total and regional capacity of both arteries and veins, Starling forces in the capillaries, and gravity also affect the EABV. Collectively, these factors interact closely with extracellular volume and some of them undergo substantial changes in certain acute and chronic severe illnesses. Their changes result not only in extracellular volume expansion, but in the need for a larger extracellular volume compared with that of healthy individuals. Assessing extracellular volume in severe illness is challenging because the estimates of this volume by commonly used methods are prone to large errors in many illnesses. In addition, the optimal extracellular volume may vary from illness to illness, is only partially based on volume measurements by traditional methods, and has not been determined for each illness. Further research is needed to determine optimal extracellular volume levels in several illnesses. For these reasons, extracellular volume in severe illness merits a separate third concept of body fluid balance.

Postoperative fluid retention after heart surgery is accompanied by a strongly positive sodium balance and a negative potassium balance

The conventional model on the distribution of electrolyte infusions states that water will distribute proportionally over both the intracellular (ICV) and extracellular (ECV) volumes, while potassium homes to the ICV and sodium to the ECV. Therefore, total body potassium is the most accurate measure of ICV and thus potassium balances can be used to quantify changes in ICV. In cardiothoracic patients admitted to the ICU we performed complementary balance studies to measure changes in ICV and ECV. In 39 patients, fluid, sodium, potassium, and electrolyte‐free water (EFW) balances were determined to detect changes in ICV and ECV. Cumulatively over 4 days, these patients received a mean ± SE infusion of 14.0 ± 0.6 L containing 1465 ± 79 mmol sodium, 196 ± 11 mmol potassium and 2.1 ± 0.1 L EFW. This resulted in strongly positive fluid (4.0 ± 0.6 L) and sodium (814 ± 75 mmol) balances but in negative potassium (−101 ± 14 mmol) and EFW (−1.1 ± 0.2 L) balances. We subsequently compared potassium balances (528 patients) and fluid balances (117 patients) between patients who were assigned to either a 4.0 or 4.5 mmol/L blood potassium target. Although fluid balances were similar in both groups, the additionally administered potassium (76 ± 23 mmol) in the higher target group was fully excreted by the kidneys (70 ± 23 mmol). These findings indicate that even in the context of rapid and profound volume expansion neither water nor potassium moves into the ICV.

Revised Estimates for the Number of Human and Bacteria Cells in the Body

Reported values in the literature on the number of cells in the body differ by orders of magnitude and are very seldom supported by any measurements or calculations. Here, we integrate the most up-to-date information on the number of human and bacterial cells in the body. We estimate the total number of bacteria in the 70 kg "reference man" to be 3.8·10¹³. For human cells, we identify the dominant role of the hematopoietic lineage to the total count (≈90%) and revise past estimates to 3.0·10¹³ human cells. Our analysis also updates the widely-cited 10:1 ratio, showing that the number of bacteria in the body is actually of the same order as the number of human cells, and their total mass is about 0.2 kg.

Thoroughly revised estimates show that the typical adult human body consists of about 30 trillion human cells and about 38 trillion bacteria.

Revised Estimates for the Number of Human and Bacteria Cells in the Body

Reported values in the literature on the number of cells in the body differ by orders of magnitude and are very seldom supported by any measurements or calculations. Here, we integrate the most up-to-date information on the number of human and bacterial cells in the body. We estimate the total number of bacteria in the 70 kg "reference man" to be 3.8·1013. For human cells, we identify the dominant role of the hematopoietic lineage to the total count (≈90%) and revise past estimates to 3.0·1013 human cells. Our analysis also updates the widely-cited 10:1 ratio, showing that the number of bacteria in the body is actually of the same order as the number of human cells, and their total mass is about 0.2 kg.

The consequences of sudden fluid shifts on body composition in critically ill patients

INTRODUCTION

Estimation of body composition as fat-free mass (FFM) is subjected to many variations caused by injury and stress conditions in the intensive care unit (ICU). Body cell mass (BCM), the metabolically active part of FFM, is reported to be more specifically correlated to changes in nutritional status. Bedside estimation of BCM could help to provide more valuable markers of nutritional status and may promote understanding of metabolic consequences of energy deficit in the ICU patients. We aimed to quantify BCM, water compartments and FFM by methods usable at the bedside for evaluating the impact of sudden and massive fluid shifts on body composition in ICU patients.

METHODS

We conducted a prospective experimental study over an 6 month-period in a 18-bed ICU. Body composition of 31 consecutive hemodynamically stable patients requiring acute renal replacement therapy for fluid overload (ultrafiltration ≥5% body weight) was investigated before and after the hemodialysis session. Intra-(ICW) and extracellular (ECW) water volumes were calculated from the raw values of the low- and high-frequency resistances measured by multi-frequency bioelectrical impedance. BCM was assessed by a calculated method recently developed for ICU patients. FFM was derived from BCM and ECW.

RESULTS

Intradialytic weight loss was 3.8 ± 0.8 kg. Percentage changes of ECW (-7.99 ± 4.60%) and of ICW (-7.63 ± 5.11%) were similar, resulting ECW/ICW ratio constant (1.26 ± 0.20). The fall of FFM (-2.24 ± 1.56 kg, -4.43 ± 2.65%) was less pronounced than the decrease of ECW (P < 0.001) or ICW (P < 0.001). Intradialytic variation of BCM was clinically negligible (-0.38 ± 0.93 kg, -1.56 ± 3.94%) and was significantly less than FFM (P < 0.001).

CONCLUSIONS

BCM estimation is less driven by sudden massive fluid shifts than FMM. Assessment of BCM should be preferred to FFM when severe hydration disturbances are present in ICU patients.

Prediction of limb lean tissue mass from bioimpedance spectroscopy in persons with chronic spinal cord injury

BACKGROUND

Bioimpedance spectroscopy (BIS) is a non-invasive, simple, and inexpensive modality that uses 256 frequencies to determine the extracellular volume impedance (ECVRe) and intracellular volume impedance (ICVRi) in the total body and regional compartments. As such, it may have utility as a surrogate measure to assess lean tissue mass (LTM).

OBJECTIVE

To compare the relationship between LTM from dual-energy X-ray absorptiometry (DXA) and BIS impedance values in spinal cord injury (SCI) and able-bodied (AB) control subjects using a cross-sectional research design.

METHODS

In 60 subjects (30 AB and 30 SCI), a total body DXA scan was used to obtain total body and leg LTM. BIS was performed to measure the impedance quotient of the ECVRe and ICVRi in the total body and limbs.

RESULTS

BIS-derived ECVRe yielded a model for LTM in paraplegia, tetraplegia, and control for the right leg (RL) (R(2) = 0.75, standard errors of estimation (SEE) = 1.02 kg, P < 0.0001; R(2) = 0.65, SEE = 0.91 kg, P = 0.0006; and R(2) = 0.54, SEE = 1.31 kg, P < 0.0001, respectively) and left leg (LL) (R(2) = 0.76, SEE = 1.06 kg, P < 0.0001; R(2) = 0.64, SEE = 0.83 kg, P = 0.0006; and R(2) = 0.54, SEE = 1.34 kg, P < 0.0001, respectively). The ICVRi was similarly predictive of LTM in paraplegia, tetraplegia, and AB controls for the RL (R(2) = 0.85, SEE = 1.31 kg, P < 0.0001; R(2) = 0.52, SEE = 0.95 kg, P = 0.003; and R(2) = 0.398, SEE = 1.46 kg, P = 0.0003, respectively) and LL (R(2) = 0.62, SEE = 1.32 kg, P = 0.0003; R(2) = 0.57, SEE = 0.91 kg, P = 0.002; and R(2) = 0.42, SEE = 1.31 kg, P = 0.0001, respectively).

CONCLUSION

Findings demonstrate that the BIS-derived impedance quotients for ECVRe and ICVRi may be used as surrogate markers to track changes in leg LTM in persons with SCI.

Validity of extracellular water assessment with saliva samples using plasma as the reference biological fluid

Extracellular water (ECW) assessment is based on dilution techniques, commonly using blood sampling. However, plasma collection is an invasive procedure. We aimed to validate the use of saliva for ECW estimation by the bromide dilution technique using plasma as the reference method, in a sample of elite athletes. A total of 89 elite athletes with a mean age of 20.4 ± 4.4 years were evaluated. Baseline samples were collected before sodium bromide oral dose administration, and enriched samples were collected 3 h post-dose administration. The bromide concentration was assessed by high-performance liquid chromatography. Comparison of means, concordance coefficient correlation (CCC), multiple regression and Bland-Altman analysis were performed. The ECW from saliva explained 91% of the variance in ECW by plasma with a standard error of estimation of 0.91 kg. The CCC between alternative and reference methods was 0.952. No significant trend was observed between the mean and difference of the methods, with limits of agreement ranging between -1.5 and 2.1 kg. These findings reveal that bromide dilution volume calculated from saliva samples is a valid noninvasive method for ECW assessment in elite athletes.

Assessment of body cell mass at bedside in critically ill patients

Critical illness affects body composition profoundly, especially body cell mass (BCM). BCM loss reflects lean tissue wasting and could be a nutritional marker in critically ill patients. However, BCM assessment with usual isotopic or tracer methods is impractical in intensive care units (ICUs). We aimed to modelize the BCM of critically ill patients using variables available at bedside. Fat-free mass (FFM), bone mineral (Mo), and extracellular water (ECW) of 49 critically ill patients were measured prospectively by dual-energy X-ray absorptiometry and multifrequency bioimpedance. BCM was estimated according to the four-compartment cellular level: BCM = FFM - (ECW/0.98) - (0.73 × Mo). Variables that might influence the BCM were assessed, and multivariable analysis using fractional polynomials was conducted to determine the relations between BCM and these data. Bootstrap resampling was then used to estimate the most stable model predicting BCM. BCM was 22.7 ± 5.4 kg. The most frequent model included height (cm), leg circumference (cm), weight shift (Δ) between ICU admission and body composition assessment (kg), and trunk length (cm) as a linear function: BCM (kg) = 0.266 × height + 0.287 × leg circumference + 0.305 × Δweight - 0.406 × trunk length - 13.52. The fraction of variance explained by this model (adjusted r(2)) was 46%. Including bioelectrical impedance analysis variables in the model did not improve BCM prediction. In summary, our results suggest that BCM can be estimated at bedside, with an error lower than ±20% in 90% subjects, on the basis of static (height, trunk length), less stable (leg circumference), and dynamic biometric variables (Δweight) for critically ill patients.