BIA body water balance monitoring -
Page hits: , File downloaded: The impact of a positive fluid balance on morbidity and mortality has been well established. However, little is known about how to monitor fluid status and fluid overload.
This narrative review summarises the recent literature and discusses the different parameters related to bio-electrical impedance analysis BIA and how they might be used to guide fluid management in critically ill patients.
BIA allows calculation of body composition and volumes by means of a current going through the body considered as a cylinder.
Reproducible measurements can be obtained with tetrapolar electrodes with two current and two detection electrodes placed on hands and feet. Modern devices also apply multiple frequencies, further improving the accuracy and reproducibility of the results.
Some pitfalls and conditions are discussed that need to be taken into account for correct BIA interpretation. Although BIA is a simple, noninvasive, rapid, portable, reproducible, and convenient method of measuring body composition and fluid distribution with fewer physical demands than other techniques, it is still unclear whether it is sufficiently accurate for clinical use in critically ill patients.
However, the potential clinical applications are numerous. An overview regarding the use of BIA parameters in critically ill patients is given, based on the available literature. BIA seems a promising tool if performed correctly.
It is non-invasive and relatively inexpensive and can be performed at bedside, and it does not expose to ionising radiation. Modern devices have very limited between-observer variations, but BIA parameters are population-specific and one must be aware of clinical situations that may interfere with the measurement such as visible oedema, nutritional status, or fluid and salt administration.
BIA can help guide fluid management, resuscitation and de-resuscitation. The latter is especially important in patients not progressing spontaneously from the Ebb to the Flow phase of shock.
More research is needed in critically ill patients before widespread use of BIA can be suggested in this patient population. like us on Facebook. follow us on Twitter. join Discussion group. join us on Linkedin. A model specific for the first group Table 3 was set by multiple linear regression of variables that were correlated to ECW in this group.
When applied to the second group, this model created no bias Table 2. The reverse procedure was applied model established on the second group and applied to the first group and produced a very similar equation without bias. Therefore, data from the two groups were pooled and subjected to the multiple regression analysis procedure.
The present study tested, in geriatric patients, the validity of BIA equations that were derived in healthy elderly subjects. The main result of this multicentric trial is that, regardless of the hydration status of the patients, BIA can be used as a bed-site technique for estimating TBW.
BIA relies on a very simple principle. Cells are envisaged as floating in a water and electrolyte milieu TBW contained in a cylinder the body. The reciprocal of the impedance opposed to a light alternative current is proportional to TBW for a current frequency higher than or equal to 50 kHz or to ECW [for frequencies below 5 kHz 20 ].
This impedance then needs to be converted into TBW or ECW by means of equations that are said to be age, disease, and population specific 8.
Very few equations relate to TBW estimates in healthy elderly subjects 8 9 21 22 , and even fewer are pertinent to geriatric patients We chose Vaché and colleagues' 8 equations because they were acquired with the same bioelectrical impedance analyzer Analycor 3 and because the reference method 18 O dilution was the same.
The net result is that TBW estimates with 18 O are very precise, with a between-day, within-subject CV of 0. Because not all BIA users have machines delivering a kHz current, we investigated equations derived for 50 kHz and kHz frequencies.
For our group of patients, estimated TBW differed from reference measurements by 0. Although these differences are statistically significant probably as the result of the large number of degrees of freedom we believe that they are acceptable in clinical practice.
We also consider that height calculated from knee height 15 can be used because the difference it induces in comparison to measured height is minimal 0. Therefore, BIA can be used as a discriminative tool for TBW measurement.
It is also important that this applies to situations with varying degrees of hydration, precisely when clinicians require an estimate of TBW. The present study involved subjects with a mild degree of dehydration. This is because written informed consent was required for participating in the study.
Although dehydrated patients are numerous, dehydration impairs cognitive functions and prevents an informed consent. The high prevalence of fluid imbalance makes BIA an attractive tool. Even for those patients in whom the estimated TBW was different from the measured TBW, it could be hypothesized that BIA is a good tool for monitoring changes in fluid balance.
Support for this comes from a study by Olde Rikkert and colleagues This means that repeated measurements were within 1 l for those subjects.
Furthermore, Olde Rikkert and colleagues 14 showed that the weight and water loss induced by a furosemide administration were correctly monitored by BIA. Individual differences shown in Fig. However, the reproducibility of BIA estimates in the short term 8 and over longer periods [28 days 11 ] suggests that a subject with a large residual in Fig.
BIA could therefore be useful in monitoring changes in TBW. In contrast, BIA with published equations leads to systematic biases in estimating ECW when applied to the geriatric patients of the present study.
Visser and colleagues' equations 9 , derived from healthy elderly subjects, has proven accurate in our group of healthy subjects mean difference 0. The same was true for Segal and colleagues' equation 18 , although it was derived from adults mean difference 0.
The bias observed in the present geriatric patients could come from an inaccurate measurement of ECW with Br, from altered electrical properties of cell membranes, or from changes in fluid repartition.
It is unlikely that the Br measurements are erroneous. Indeed, the same technique was used for healthy subjects 8 , and in the present study, the mean CV for plateau concentration in Br was 1. Furthermore, Finn and colleagues 6 , in a study of critically ill patients, and Kim and colleagues 24 , in a study of AIDS patients, have shown that intracellular penetrance of the Br tracer is not changed appreciably.
Steen 25 showed that the ratio of ECW to TBW increased with age. If the extracellular fluid expansion was mostly in the limbs, impedance at 5 kHz would be underestimated and ECW artificially increased.
Furthermore, limbs represent the largest component of the impedance of the body. ECW was not correlated to plasma sodium, osmolality, or classical protein markers of malnutrition data not shown.
We have derived an equation to calculate ECW in geriatric patients. This equation remains to be evaluated in other diseased patients. In conclusion, BIA with specific equations for elderly subjects could be used as a bed-site tool for discriminative diagnosis and for monitoring changes in fluid balance in geriatric patients.
This validity applies to TBW across the range of hydration disorders. Data are limited to 84 values 47 women and 37 men and were obtained by bromide dilution.
See Methods for the description of the hydration categories. Regression Models Established to Predict Extracellular Water From Impedance Measured at 5 kHz. The y -axis is the difference between the two measurements, and the x -axis is the mean of measured and estimated values.
The Source Study is a French multicentric study coordinated by Dr. Ritz Human Nutrition Research Centre-Auvergne. Investigators were by alphabetical order : Dr. Acher Paris, Bichat , Pr. Beaufrère Clermont-Ferrand , F. Blondé-Cynober Paris, Hôtel-Dieu , Dr. Boulier Paris, Bichat , Dr.
Bouthier, Dr. Bouthier-Quintard Limoges , Pr. Constans, Dr. Dardaine Tours , Dr. Desport Limoges , Dr. Ghisolfi-Marque Toulouse , Dr. Hermet Clermont-Ferrand , Dr. Lambert Paris, E. Roux , Pr. Vellas Toulouse , Dr. Vincent Paris, E Roux , and Dr. Arnaud Perrier Vittel Water Institute.
We thank Line Godiveau for secretarial assistance and Miriam Ryan for correcting the English. Weinberg AD, Minaker KL, and the council of scientific affairs, American Medical Association Dehydration: evaluation and management in older adults.
Molaschi M, Ponzetto M, Massaia M, Scarafiotti C, Ferrario E, Hypernatremic dehydration in the elderly on admission to hospital. Age Nutrition. Leaf A, Dehydration in the elderly. N Engl J Med.
Mooradian AD, Water balance in the elderly. Morley JE, Korenman SG, , ed. Endocrinology and Metabolism in the Elderly Blackwell Scientific Publications, Boston, MA. Shizgal HM, Soloman S, Gutelius JR, Body water distribution after operation. Surg Gynecol Obstet : 35 Finn PJ, Plank LD, Clark MA, Connolly AB, Hill GL, Progressive cellular dehydration and proteolysis in critically ill patients.
Clasey JL, Kanaley JA, Wideman L, et al. Validity of methods of body composition assessment in young and older men and women.
J Appl Physiol. Vaché C, Rousset P, Gachon P, et al. Bioelectrical impedance analysis measurements of total body water and extracellular water in healthy elderly subjects.
Int J Obes. Visser M, Deurenberg P, Van Staveren WA, Multi-frequency bioelectrical impedance for assessing total body water and extracellular water in elderly subjects. Eur J Clin Nutr. Bussolotto M, Ceccon A, Sergi G, Giantin V, Beninca P, Enzi G, Assessment of body composition in elderly: accuracy of bioelectrical impedance analysis.
Olde Rikkert MGM, Deurenberg P, Jansen RWMM, van't Hof MA, Hoefnagels WHL, Validation of multifrequency bioelectrical impedance analysis in monitoring fluid balance in healthy elderly subjects. J Gerontol Med Sci. Deurenberg P, Schouten FJM, Loss of total body water and extracellular water assessed by multifrequency impedance.
De Lorenzo A, Barra PFA, Sasso GF, Battistini NC, Deurenberg P, Body impedance measurement during dialysis. Validation of multifrequency bioelectrical impedance analysis in detecting changes in fluid balance of geriatric patients.
J Am Geriatr Soc. Chumlea WC, Roche AF, Steinbaught ML, Estimating stature from knee height for persons 60 to 90 years of age. Miller ME, Cappon CJ, Anion exchange chromatographic determination of bromide in serum.
Clin Chim. Ritz P, Johnson PG, Coward WA, Measurement of 2 H and 18 O in body water: analytical considerations and physiological implications.
Br J Nutr. Segal KR, Burastero S, Chun A, Coronel P, Pierson RN, Jr Wang J, Estimation of extracellular and total body water by multiple-frequency bioelectrical impedance measurement.
Am J Clin Nutr. Bland JM, Altman DG, Statistical method for assessing agreement between two methods of clinical measurements. Lukaski HC, Methods for the assessment of human body composition: traditional and new.
Deurenberg P, VanderKooy K, Evers P, Hulshof T, Svendsen OL, Haarbo J, Heitmann BL, Godfredsen A, Christiansen C, Measurement of body fat in elderly subjects by dual-energy x-ray absorptiometry bioelectrical impedance and anthropometry.
Schoeller DA, Van Santen E, Peterson DW, Dietz W, Jaspan J, Klein PD, Total body water measurements in humans with 18 O and 2 H labelled water. Kim J, Wang ZM, Gallagher D, Kotler DP, Ma K, Heymsfield SB, Extracellular water: sodium bromide dilution estimates compared with other markers in patients with acquired immunodeficiency syndrome.
Steen B, Body composition and aging. Nutr Rev. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account.
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This study validates, Immune-boosting habits bofy patients, bioelectrical mpnitoring analysis BIA equations that had been Subcutaneous fat reduction surgery to estimate total bovy water Mojitoring and extracellular water ECW in bory elderly BIA body water balance monitoring. We performed a multicentric Vegetarian weight loss supplements in six geriatric wards. We studied patients with varying degrees of hydration: dehydrated, euvolemic, and overhydrated. BIA estimates of TBW and of ECW were compared with the measurement of TBW with 18 O dilution and of ECW with bromide Br dilution. BIA estimated TBW with a difference of 0. The difference was not affected by the hydration status. Estimates of ECW with BIA were systematically biased compared with Br dilution: 4.
BIA body water balance monitoring -
This might also lead to a decline of oxygenation of tissues and tissue edema that could culminate in cell necrosis or apoptosis as possible cause of delayed wound healing and instability of anastomosis. On the other hand, the lack of sufficient replacement of fluid in acute phase cause problems such as insufficient tissue perfusion and impaired organ functions including acute kidney injury, hepatic dysfunction, or decreased bowel motility.
Actually, a very acute postoperative phase such as the first 24 h right after surgery is the period when the loss of interstitial or intravascular fluid is common due to direct consequences of surgeries. During this period, adequate tissue perfusion through fluid resuscitation is important and the positive fluid imbalance observed in this period would be considered a natural course, not relevant to poor prognosis 17 , At the acute phase, previous oliguria caused by secretion of stress hormone and increase in renal reabsorption are usually improved followed by progression to a diuretic phase.
Colin et al. Therefore, authors suppose that the positive fluid imbalance observed in the period of 48—72 h after surgery is related to organ dysfunctions and thus relevant to the prognosis.
In this study, the ECW ratio of postoperative patients turned out to be the highest on the second day of ICU admission, and then it tended to decrease.
The ECW ratio refers to the proportion of extracellular fluid and it is known to reflect edematous status and malnutrition in patients We divided patients into two groups, OH and NH, according to their ECW ratio and identified a significant difference in outcomes between two groups.
This finding implies the feasibility of ECW ratio as a tool to assess volume status of a patient in the acute phase after surgery. ECW ratios higher than 0. This supports our conclusion that a proper volume status management in the acute postoperative phase would have clinical importance.
Additionally, the measurement using BIA usually takes less than two minutes as a non-invasive approach with a portable machine is suitable for an immobilized patient 4 , 21 , It could be also used safely for postoperative critical ill patients with poor clinical conditions such as bleeding without giving them time-related discomfort or any other risks of procedure.
Actually, there were no complication or discomfort of patients relevant to the BIA use in our study. Authors suppose that BIA could be helpful for measuring the volume status of a critical ill patient, especially in an acute phase for patients who suffer from severe pain due to operative wounds or multiple drains that are too serious to take repeated invasive examinations.
As shown in Fig. CLI is associated with increased vascular permeability that could result from inflammation and shock. Inflammation can lead to releases of pro-inflammatory cytokines and stress hormones that would consequently result in vascular permeability increase, and transcapillary albumin leak.
It can cause the impaired regional tissue oxygenation, enhanced compensatory neuroendocrine reflexes, and increasing fluid retention of the kidney that eventually cause a positive fluid balance These events can increase CLI levels consecutively.
For a patient after a major surgery whose physiologic state is similar to those in a shock status, the capillary leak and tissue edema are common. A previous research 19 , 20 has reported that CLI levels of patients tend to increase until a crucial turning point is observed on the third day of shock.
After the third day of shock, their microcirculatory blood flows begin to be normalized accompanied by the closure of capillary leak.
This can explain our findings that CLI levels began to decrease after the third day and that CLI level was highly correlated with ECW ratio on BIA.
Excessive increase of interstitial volume due to this capillary leak could lead to pulmonary edema and contribute to the occurrence of lung complications of fluid overload Although this study failed to analyze the direct relation with respiratory complication, the authors believe that an elevated ECW ratio and overhydration status on Day 3 after operation can cause a burden for respiratory functions.
Especially, patients after major abdominal surgeries are often vulnerable to respiratory distress because proper deep breathing and expectoration are very difficult due to surgical wound, pain, or residual effect of general anesthesia.
Therefore, we expect that an overhydration status of a patient as ECW ratio on postoperative day 3 more than 0. To verify this assumption, additional studies with large sized data collection and analysis are needed.
Despite these interesting outcomes, results of the current study should be interpreted with caution due to various limitations. Firstly, our data analysis had some bias due to its observational study design of a single center despite of our strict enrollment and exclusion criteria.
The patients with CRRT or ECMO treatment in Table 1 represented newly applied patients during postoperative period of ICU care. The patients receiving treatments such as ECMO and CRRT due to changes in condition caused by postoperative complications have different volume status in their body for fluid management compared to patients who do not receive these treatments.
To reduce the bias in BIA measurements on the volume status of this patient group, subsequent studies on large patient enrollment and subgroup analysis would be needed.
Most of the enrolled patients had elective surgery rather than emergency operation, and few patients needed the vaso-active drugs after surgery. Most patients with hemodynamic instability had undergone the emergency operation, and were able to recover with the fluid resuscitation.
When vaso-active drugs were required because it was difficult to recover from the hemodynamic condition only with fluid resuscitation, norepinephrine was used as the first-choice vaso-active drug according to the SSC guideline. It is difficult to completely rule out that the use and type of vaso-active drugs may act as a bias factor for BIA results.
According to the recent papers published so far 16 , 18 , there are several treatment principles for fluid treatment, but the amount of the fluid given and timing of the administration are debatable in the following study, it is necessary to prospectively apply different strategies of fluid management according to randomized designs and perform a subgroup analysis to determine whether there are any differences in clinical outcomes by measuring the BIA for each case.
Additionally, various factors of ICU environment such as ambient air, skin temperature, seating, and specific conductance of ICU bed that might affect BIA measurements could not be understood. Secondly, we did not perform subgroup analysis according to the type of shock or surgery mainly due to small numbers of participants.
Most of the enrolled patients of this study received abdominal surgery due to characteristics of our SICU. But, there were relatively few patients who underwent vascular surgery or trauma. The patients who had abdominal surgery had higher systemic inflammation, extensive organ injury, and tissue damage, and would be expected to have greater BIA changes with fluid management compared to the patients who underwent endovascular surgery or operation of extremities.
The small number of participants could be also a reason for failure to confirm the statistical significance of overhydration status in the prediction of occurrence of pulmonary complications. A well-designed prospective randomized study involving a large number of participants should be conducted in the near future to confirm results of the current study.
Thirdly, since a high ECW ratio means fluid overload as well as when the body cell mass is low, it is difficult to distinguish the two using only BIA data.
However, the results of this study are determined to be changes in the ECW ratio due to fluid overload, but it cannot be completely excluded that it may be related to malnutrition and low body cell mass in patients.
Moreover, in this study, the baseline BIA were not measured before surgery, but were measured immediately after entering the SICU after surgery at the time of enrollment, so it is difficult to compare the changes in BIA data before and after surgery.
In particular, in the patients who have underlying diseases such as chronic kidney disease, heart failure, and chronic obstructive pulmonary disease with poor cell membrane conditions, there may be limitations in interpreting the fluid overhydration status only with BIA data after surgery.
The phase angle of the BIA parameters is an indicator that reflects the health condition of cells or cell membranes and can be used as a nutritional indicator. There is no baseline phase angle data, so the use of the phase angles in comparing changes in the nutritional condition of patients before and after surgery is also limited, either.
Therefore, the results of baseline data before surgery should be included to overcome these limitations and ensure more clear comparisons in the near future study. Nevertheless, this study is meaningful in that it differs from existing studies.
It was a prospective cohort study conducted on patients after major operation. Also, in the current study, SICU patients in an acute phase were observed intensively.
BIA is a non-invasive method that is easy to operate and measure and it is expected to provide a foundation of the fluid management guideline in acute phase of ICU patients after major operations.
In conclusion, the use of BIA to estimate volume status is a feasible method that is easy, safe, and adaptable for critical patients in immobilization status after operations. Zhang, Z. Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.
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Task force of the European Society of Intensive Care Medicine. Download references. The authors would like to thank Kyung-Soo Kim Signal-processing researcher, InBody, Seoul, Republic of Korea for technical assistance. Department of Emergency Medicine, Seoul National University Bundang Hospital, 82, Gumi-Ro Beon-Gil, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, , Republic of Korea.
Department of Emergency Medicine, Seoul National University College of Medicine, Daehak-Ro, Jongno-Gu, Seoul, , Republic of Korea. You can also search for this author in PubMed Google Scholar.
JHL and YHJ designed the study and prepared the protocol. HJ, IP, JHL, DK, SB, and SK conducted experiments and acquired data. HJ, IP, and JHL analyzed data. HJ and IP drafted the manuscript. IP and JHL revised the manuscript. All authors read and approved the final manuscript.
Correspondence to Jae Hyuk Lee. All experiments were approved by the Institutional Animal Care and Use Committee of Seoul National University Bundang Hospital.
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Reprints and permissions. Jeong, H. et al. Feasibility study using longitudinal bioelectrical impedance analysis to evaluate body water status during fluid resuscitation in a swine sepsis model. ICMx 10 , 51 Download citation. Received : 27 September Accepted : 28 November Published : 06 December Anyone you share the following link with will be able to read this content:.
Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all SpringerOpen articles Search. Download PDF. Abstract Fluid resuscitation is crucial in the initial management of sepsis; however, little is known about the serial changes and overall distribution of fluids administered into the body.
Introduction Fluid resuscitation is crucial in the initial management of sepsis because it helps improve tissue hypoperfusion [ 1 ].
Materials and methods Study settings All experiments were approved by the Institutional Animal Care and Use Committee of Seoul National University Bundang Hospital protocol no. Animal preparation Twelve male three-way crossbred Yorkshire Berkshire Duroc, Cronex, Seoul, Republic of Korea pigs Bioelectrical impedance analysis InBody M20 Inbody Co.
Results A total of 12 pigs were monitored for up to 12 h after ESBL-producing E. Full size image. Discussion In this study, we identified that the trend of body water status, including its distribution, can be assessed using BIA. Abbreviations ECW: Extracellular water TBW: Total body water ESBL: Extended-spectrum β-lactamase E.
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cyprinorum L. was selected as a biological model in this study, because most individuals of this species lack scales, and their skin may be naked even at long intervals These scale-free locations on the fish's body were where non-invasive contact electrodes were placed while invasive needle electrodes were placed at locations where scales existed.
Living subjects for the study were obtained from a local population of Mirror Carp in a fish farm of Belgorod Region, Russia. The total sample for the study included 20 mature carp, with five studied per day. Each selected carp was initially immobilized by cranial concussion 36 then measured to the nearest millimetre for standard length L ; from the tip of the nose to the end of the caudal peduncle and width W ; at 4 body locations; see Fig.
The potential effects of time on BIA after death were considered to be minimized in this design Space on vertical line between paired on one side electrodes, including signal-emitting higher and signal-detecting lower electrodes, was kept constant 3 mm between closest edges for contact and 7.
Distances between each paired sets of electrodes i. For BIA procedures, fish were blot dried and placed on a nonconductive board. After attaching electrodes, parallel conductance module Y and serial phase angle ϕ readings for each fish were immediately obtained with 0. The needle electrodes were positioned to penetrate approximately 5 mm into each fish.
Whole-body readings were acquired from two dorsal anterior and posterior locations by the same contact electrodes and two ventral anterior and posterior locations by the same needle electrodes on the left side of each fish.
Dorsal electrode locations were proposed to be more related to moisture BIA models, while ventral electrode locations were proposed to be more related to lipid BIA models In the present study, readings from dorsal and ventral locations were statistically linked in analyses to obtain integrated BIA measurement effects i.
The two-surface models were proposed to incorporate greater amounts of information about the internal composition of a subject, which could improve their predictive ability.
Previously, the combination of dorsal and ventral BIA data in two-surface BIA models was found to be a more precise estimator of the percent of proximate moisture content of the body than the models developed from either dorsal or ventral data alone i.
To minimize potential errors in BIA measurements of fish, each experiment was controlled for correct electrode locations, procedure deviations, time after death, and temperature following prior study recommendations For the whole body, a multifrequency BIA 50, , and kHz was acquired, but only 50 kHz was used in the present study to match with the segmental BIA obtained only by 50 kHz current.
Thus, for segmental derivations, 8 pairs of electrodes i. While space on the vertical line between paired i. For each segmental and whole-body BIA assessments, parallel conductance module Y, siemens and serial phase angle ϕ, degrees measures were collected three times and further expressed as averages.
Room temperature was controlled during all BIA procedures to ensure that the examined fish had similar body temperatures. During BIA procedures, the mean SD room temperature was The comparison of classical uncorrected BIVA measures with resistivity corrected BIVA measures showed that the latter measures were more accurate in predicting only measures of nutrition status e.
Physicochemical analysis of cadavers is considered the most accurate approach to measuring human body composition to obtain reference or criterion points Age is considered one of main factors affecting hydration status in humans A healthy hydration status was also associated with biological osmo- and baro-reflex mechanisms sensing and maintaining homeostatic i.
In addition, absolute measures of hydration status were not recommended for the evaluation of water distribution between the extra- and intra-cellular spaces In the present study, fat percentage from the proximate body composition analysis was considered as a reference criterion point such that best fitting BIA models for hydration were independent of this probable confounding factor as a main source of metabolic water during fasting in some animals, and thus it functioned as an additional control for well-being of the sample Fat percentage was found to be weakly associated with uncorrected bioimpedance measures Therefore, best fitting models in prediction of variations of relative body compartments, such as water, proteins and minerals associated with differences in hydration status and fluctuations in hydration level, but not the prediction of variations of absolute or relative means of body compartments, such as fat mass and fat free mass, was the main target of the present study.
Another reason for the choice of relative proximate values in the present study was related to the consideration that since most BIA models included the total length of the body in their equations, their ability to accurately predict the absolute body components closely connected to body weight could simply be related to the adjustment of BIA measures for body length or length squared Generalized Linear Mixed Models GLMM were used to derive predictive relationships of bioimpedance and morphological measures with proximate measures of body compartments.
Whole-body BIA models with two surface one-side derivation schema i. Complete independence of BIA measures was assumed across subject blocks with each BIA derivation.
According to the Akaike Information Criterion AIC , diagonal covariance type was the best fitting structure for the repeated measurements. Robust method was used for computing the parameter estimates covariance matrix to protect against a probable violation of the model assumptions.
A previous study proposed that segmental bioimpedance indices can be used not only for predicting segment composition but also for estimates of whole body composition from the sum of segmental composition estimates Moreover, selected demarcation that exclude materially representative amounts of tissue with extra-cellular ECW and intra-cellular ICW water contents could not be provided for any of the individual localized body segments in order to represent the whole-body hydration level accounting for water and electrolytes.
This is especially relevant for transferring findings from such animals as fish to humans having numerous differences in their anatomical constructions. Thus, in the present study, the terms segmental and local were used interchangeably to represent body places or body portions, but not the whole-body, in predicting components affecting hydration level of the total fish body.
This contrasts with similar terms usually applicable to the human body to differentiate anatomical body portions i. In testing the study hypotheses, the difficulty was not related to obtaining significant correlations of bioelectrical impedance to hydration status measures but rather to specifying its different relationship to different hydration-related compartments water, dissolved proteins, electrolytes because of an expected high degree of intercorrelation between them in healthy individuals.
Thus, any impedance parameter that was found to be correlated with one of the hydration-related compartments e.
water would be expected to correlate almost equally well with the other compartments affecting hydration, such as dissolved proteins and non-osseous minerals i.
A second-order AIC with a correction for small sample sizes was used to rank significant models of the relation of BIA data to proximate composition for selecting the most parsimonious ones i.
Significant negative effects on total body water or moisture percentage assessed by proximate composition analysis were found for both in series and in parallel obtained segmental BIA measures: resistance and reactance with and without adjustment to widths of segments, the reactance-to-resistance ratio, and various total impedance measures calculated by different equations Supplementary Table S2.
According to AIC, addition of body weight as a covariate did not improve the predictive ability of the models, but prediction of total body moisture percentage was improved if the segmental BIA models also included body length Supplementary Table S3.
According to AIC, the best fitting models were a segmental BIA model of a serially obtained reactance with the effect adjusted for body length and a model of a more complex equation involving the product of serially obtained reactance and resistance adjusted for total impedance with the final effect adjusted for body length.
The best fitting models for water-related effects from Supplementary Tables S2 and S3 were presented in Table 2. Thus, the quantity of water assessed segmentally or locally by reactance or a more complex bioimpedance-related equation could better represent the percent of body moisture or body hydration status after accounting for its distribution along the whole length of a particular body.
Significant positive effects on body protein percentage assessed by proximate composition analysis were found for in parallel obtained segmental BIA measures: reactance and total impedance, as well as a serially obtained segmental BIA measure: resistance, all adjusted for widths of segments Supplementary Table S2.
According to AIC, the prediction of body protein by these simple models did not improve if they also included body length or weight Supplementary Table S3.
Significant interaction effects of the adjusted in parallel and serially obtained reactance and resistance were also found for body protein, but according to AIC, the models were poorer fit compared to the simple models Supplementary Table S3. The same was found when body length was added to the interaction models.
According to AIC, the best fitting models were simple segmental BIA models of serially obtained resistance unadjusted only approached significance in GLMM and adjusted for widths of body segments was significant in GLMM.
Two other simple segmental BIA indicators, in parallel obtained reactance unadjusted only approached significance in GLMM and adjusted for widths of body segments was significant in GLMM were close in model fit Supplementary Table S2.
The best fitting models for protein-related effects from Supplementary Table S2 were presented in Table 2. Serially obtained segmental BIA reactance and resistance, both adjusted for widths of segments and included in the same model, indicated significant negative and positive simple effects, respectively, on protein content.
The same models with in parallel obtained segmental BIA reactance and resistance indicated significant effects in the opposite direction, specifically positive and negative simple effects, respectively, on protein content.
Thus, quantity of proteins assessed locally or segmentally by serially obtained resistance the best fitting or in parallel obtained reactance a less fitting can represent the body protein with and without adjustment for widths of locally assessed segments and without accounting for the whole length or weight of the particular body as an individual trait.
Significant negative effects on body ash percentage assessed by proximate composition analysis were found for serially obtained BIA measures: phase angle, reactance-to-resistance ratio, reactance adjusted for widths of segments, a product of reactance and resistance adjusted for widths of segments and with additional adjustment for total impedance, as well as for an in parallel obtained BIA measure: resistance adjusted for widths of segments Supplementary Table S2.
According to AIC, the prediction of body ash was improved if the simple BIA models also included body length or weight best fitting models as covariates Supplementary Table S3. Significant effects on body ash percentage were also found for various in serial and in parallel obtained BIA indicators when the indicators were added to models together Supplementary Table S2.
Serially obtained BIA reactance and resistance both included in the same model indicated significant opposite negative and positive simple effects, respectively, on ash content, while the same models with in parallel obtained BIA reactance and resistance indicated significant positive and negative simple effects, respectively, on ash content.
However, the models had poorer fit compared to simple models, according to AIC. An improvement in fit closer to simple models was found when body length or body weight most fitting models was additionally included in these complex models.
According to AIC, the best fitting models were a serially obtained reactance-to-resistance ratio with and without the effect adjusted for body weight. These models for ash-related effects from Supplementary Tables S2 and S3 were presented in Table 2.
Thus, a relative quantity of ash assessed by the reactance-to-resistance ratio locally or segmentally can represent the total body ash after accounting for weight as a proxy of its distribution in the whole body.
Including body weight in the model improved the model fitting and its effect size but made the model non-significant. Significant negative effects on body protein percentage assessed by proximate composition analysis were found for an in parallel obtained whole-body BIA resistance adjusted for the distance between electrodes, serially obtained whole-body BIA phase angle, reactance-to-resistance ratio, and reactance with and without adjustment for the distance between the electrodes, as well as more complex whole-body BIA indicators: products of serially obtained reactance and resistance with and without adjustment for the distance between the electrodes, with additional adjustment for the serially obtained total impedance Supplementary Table S5.
Including body weight in the model only slightly improved the model fitting but decreased its effect size. Significant negative effects on total body ash percentage assessed by proximate composition analysis were found for an in parallel obtained whole-body BIA resistance with and without adjustment for the distance between electrodes, serially obtained whole-body BIA phase angle, reactance-to-resistance ratio, reactance with and without adjustment for the distance between electrodes, resistance with adjustment for distance between electrodes, as well as more complex whole-body BIA models: two with a product of serially obtained reactance and resistance with adjustment for the total impedance with and without additional adjustment of each measure in the equations for the distance between electrodes and one involving the serially obtained total impedance with adjustment for distance between electrodes Supplementary Table S5.
Including body weight in the model only slightly improved the model fitting but decreased its effect size and made the model non-significant. Supplementary Tables S1 and S4 present predicting effects of all segmental and whole-body BIA measures on body weight, width, and length.
In parallel obtained resistance of whole-body BIA adjusted to distance i. Body weight and widths of segments were not significantly related to percent of body moisture water , protein, ash, and fat. Body length was only significantly related to percent of body ash Supplementary Tables S2 and S5.
For the present study, fish was selected as a biological model to validate BIA equations in predicting proximate body components associated with hydration status such as water, proteins including dissolved colloid fraction, and minerals including non-osseous fraction and associated with nutrition status such as fat, all obtained directly by physicochemical methods.
Only these direct measures adjusted for inter-individual differences in weight i. These BIA equations were approved in the study with respect to the principal predictive values of impedance and its resistance and reactance components, as well as their various ratios and products assessed in series or in parallel, using whole-body and segmental BIA schemas that should be common across different biological species, but without inclusion of specific regression constants that should differ between different biological species The length of body, distance between electrodes, and weight as additional parameters of individual differences, or individual traits, were assessed for their impact in improvement of the predictive value of the BIA measures.
This confirmed the reliability of the design of the present study including the BIA measurement procedure and the lethal physicochemical method for the proximate composition analysis.
Moreover, the study showed that models containing BIA measures obtained from segmental impedance readings could also predict these proximate measures of body composition.
However, best fitting models predicting the body compartments were different for BIA measures from segmental versus whole-body BIA readings. The main difference was related to different electrical compensation schemes used to obtained BIA measures for inclusion in prediction models: serial for segmental and parallel for the whole-body BIA readings.
In contrast, in the segmental BIA schema, the equations combining measures of resistance and reactance e. Length of body as an additional parameter of individual differences, or the individual trait, was found to improve the predictive value of the total water percentage by the segmental or local BIA if it was added in the regression formula.
With respect to between-subject variation in the body hydration status, the association of body moisture decrease with an increase in both serially obtained resistance and reactance bioimpedance measures indicated that the dehydration was probably related to or was interpreted as a mechanism of water transfer from ECW water decrease to ICW water increase.
Since reactance Xc is related to the dielectric properties, it is assumed that ICW should linearly and positively be correlated with the reactance Xc , while resistance R should linearly and negatively be correlated with ECW In addition, this purported ECW to ICW distribution shift was confirmed by a significant relationship of lower body moisture with a higher value for the product of the resistance and reactance adjusted for total bioimpedance.
However, best fitting models related to higher reactance to resistance ratio and higher absolute reactance could indicate a predominant effect of absolute ICW increase i. Indeed, ICW has a higher resistivity than ECW primarily due to the high concentration of dissolved protein i.
Both in parallel and in series obtained resistance and reactance in both whole-body and segmental schemas were similarly related to body moisture proposing that they detected a hydration status of a similar origin. In the segmental BIA obtained in series schema, the protein content decrease was better predicted by a decrease of a resistance measure i.
This proposes a distinct origin of these compartments and their correspondence to hydration status detected by serially and parallelly obtained electrical compensation schemas. For example, ICW has a higher specific resistance than ECW primarily due to the high concentration of dissolved protein, which dramatically impedes ion movement associated with water resistivities regulated by non-osseous minerals presented in fluids as electrolytes: mainly chloride for ECW and mainly potassium for ICW Serially detected protein and minerals predominantly in the segmental models could indicate the decrease in body fluids with an increase in concentrations of electrolytes and dissolved proteins as in hyper-osmolal dehydration that was expected in the current design.
Parallelly detected protein and minerals predominantly in the whole-body models could indicate the decrease in body fluids with a decrease in concentrations of electrolytes and dissolved proteins mimicking eu-osmolal dehydration that was not expected in the current design.
Thus, the parallel schema might assess percent of electrolytes and dissolved proteins that were concentrated intracellularly. This corresponds to the proposal that bioimpedance measured at 50 kHz current obtained by a serial schema primarily reflects the ECW space, but a parallel bioimpedance model is more sensitive to changes in ICW Thus, the use of two in series and in parallel electrical compensation schemas could allow for measuring the osmolality hyper-, hypo- or iso-osmolality of different origin associated with dissolved protein or electrolytes , but not the hydration status hyper-, hypo- or iso-hydration separately in the ECW and ICW compartments by bioimpedance measures using the single 50 kHz frequency of electrical current.
This also confirms previous findings suggesting that electrolyte balance influences BIA measurements independently of fluid changes 12 , Both segmental and whole-body BIA readings in response to the single 50 kHz frequency did not predict the fat or lipid compartment of the body composition.
Additionally, most whole-body BIA models included the total length of the body in their equations, and their ability to accurately predict the body components may simply be related to the adjustment of BIA measures for body length or length squared Moreover, compared with models developed using only width i.
The present study did not include an assessment of the relative contribution of each segment in ventral and dorsal surfaces i.
The validity of BIA models also invariably relies on the amount of contrast in the proximate composition of the studied samples that was not specially manipulated in the present study. To adequately assess the ability of the BIA models to predict body compartments associated with hydration and osmolality status, future study should include a wider range of physiological states within a particular population and information on each of these states with cross-sectional e.
Since BIA works very similarly for a wide range of vertebrates from humans to fish 20 , the latter was used in this study as a model for the comparison of different BIA measures and equations to predict between-subject variance in proximate body measures of hydration status i.
This approach bypasses shortcomings of most non-lethal or in-vivo reference methods applied in human subjects affecting the precision of the related body compartment models. Moreover, their prediction by different equations corrected or uncorrected for body weight and length was probably related to different distribution of the hydration components between ICW and ECW spaces affecting not only their hydration, but separately also their osmolality status.
Some of the current findings showed that the application of both in series and in parallel electrical compensation schemas for BIA measurement at 50 kHz frequency of electrical current could guarantee that ECW differences do not corrupt the ICW and vice versa in assumed osmolality status assessment electrolyte balance coupled with dissolved protein level affecting, respectively, osmotic and oncotic pressures , but probably were not important for hydration status water balance assessment as two separate and relatively independent targets of the homeostatic regulation.
However, findings of indirect bioimpedance-derived measures of hydration and osmolality homeostasis obtained in fish should be transferred to humans after optimizing applicability of respective equations to bioimpedance measures obtained at different segmental and local anatomical portions of the human body Moreover, validity of these BIA models should be confirmed while controlling for potential confounding factors before implementation of the best techniques for the mathematical treatment of BIA data in practice.
Formulas for predicting absolute values for these body compartments in the assessment of nutrition status will require adjustment for regression constants that should differ between animal e. Wotton, K. Prevalence, risk factors and strategies to prevent dehydration in older adults.
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BIA body water balance monitoring watwr for visiting nature. You are using monihoring browser version monitoirng limited support Immune-boosting habits CSS. To obtain the best experience, we recommend balancee use a more up to date browser or turn Subcutaneous fat reduction surgery Onion marketing strategies mode in Internet Explorer. In the BIAA, to ensure continued support, we are displaying the site without styles and JavaScript. We determined the relationship between changes in bioelectrical impedance analysis BIA parameters and response of critically ill patients to fluid therapy during early postoperative period. Associations between BIA values indicating volume status of postoperative patient and clinical outcomes were also evaluated. From May to Aprilpatients who were admitted to the surgical intensive care unit SICU of our institution at more than 48 h after surgery were enrolled.
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