Hemoconcentration of Creatinine Minimally Contributes to Changes in Creatinine during the Treatment of Decompensated Heart Failure : Kidney360

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Original Investigation: Acute Kidney Injury and ICU Nephrology

Hemoconcentration of Creatinine Minimally Contributes to Changes in Creatinine during the Treatment of Decompensated Heart Failure

Maulion, Christopher1; Chen, Sheldon2; Rao, Veena S.1; Ivey-Miranda, Juan B.1,3; Cox, Zachary L.4; Mahoney, Devin1; Coca, Steven G.5; Negoianu, Dan6; Asher, Jennifer L.7; Turner, Jeffrey M.8; Inker, Lesley A.9; Wilson, F. Perry10; Testani, Jeffrey M.1

Author Information
Kidney360 3(6):p 1003-1010, June 30, 2022. | DOI: 10.34067/KID.0007582021


Key Points 

  • Hemoconcentration is a minimal contributor to changes in serum creatinine during treatment of decompensated heart failure.
  • Changes in GFR is the primary driver of serum creatinine in treatment of decompensated heart failure.


Worsening serum creatinine is common during treatment of acute decompensated heart failure (ADHF). A possible contributor to creatinine increase is diuresis-induced changes in volume of distribution (VD) of creatinine as total body water (TBW) contracts around a fixed mass of creatinine. Our objective was to better understand the filtration and nonfiltration factors driving change in creatinine during ADHF.


Participants in the ROSE-AHF trial with baseline to 72-hour serum creatinine; net fluid output; and urinary KIM-1, NGAL, and NAG were included (n=270). Changes in VD were calculated by accounting for measured input and outputs from weight-based calculated TBW. Changes in observed creatinine (Crobserved) were compared with predicted changes in creatinine after accounting for alterations in VD and non–steady state conditions using a kinetic GFR equation (Cr72HR Kinetic).


When considering only change in VD, the median diuresis to elicit a ≥0.3 mg/dl rise in creatinine was −7526 ml (IQR, −5932 to −9149). After accounting for stable creatinine filtration during diuresis, a change in VD alone was insufficient to elicit a ≥0.3 mg/dl rise in creatinine. Larger estimated decreases in VD were paradoxically associated with improvement in Crobserved (r=−0.18, P=0.003). Overall, −3% of the change in eCr72HR Kinetic was attributable to the change in VD. A ≥0.3 mg/dl rise in eCr72HR Kinetic was not associated with worsening of KIM-1, NGAL, NAG, or postdischarge survival (P>0.05 for all).


During ADHF therapy, increases in serum creatinine are driven predominantly by changes in filtration, with minimal contribution from change in VD.

Visual Abstract



Fluctuations in serum creatinine are common in patients undergoing treatment for acute decompensated heart failure (ADHF) (1). Worsening renal function (WRF), as it is termed in the cardiovascular literature, is often considered a negative prognostic indicator (234–5). However, contemporary data have found that clinical context of WRF largely determines its prognostic effect (6). Notably, if WRF occurs in an otherwise beneficial clinical context, such as aggressive decongestion or titration of renin-angiotensin-aldosterone system antagonists, WRF can be associated with neutral or improved survival. In this context, these observations have challenged the notion that changes in creatinine are driven by meaningful kidney injury. Rather, they suggest that mechanisms such as functional/hemodynamic changes in glomerular filtration are dominant (7). Alternatively, nonfiltration-related factors may be at play, such as a rapid reduction of the volume of distribution (VD) of creatinine leading to hemoconcentration of creatinine as total body water (TBW) contracts around a fixed mass of creatinine. With this mechanism, an increase in creatinine would be unrelated to GFR and simply a marker of effective diuresis. This could explain the null associations between WRF with urinary tubular injury markers and prognosis.

Changes in VD and filtration during the treatment of ADHF can be isolated and accounted for mathematically. Rooted in the conservation of mass of creatinine, kinetic GFR (kGFR) equations provide a more dynamic method of estimating acutely changing renal filtration during rapid fluctuations in serum creatinine and the VD of creatinine (8,9). Our goal was to apply kGFR and other models of these component factors to an ADHF population that underwent aggressive diuresis to better understand the mechanism underlying the changes in creatinine during ADHF therapy.

Materials and Methods

The multicenter ROSE Acute Heart Failure Randomized Trial (ROSE-AHF) provides an ideal platform to study acute changes in renal function in the setting of aggressive diuresis. The rationale, design, and results of the trial were previously described (10,11). The study was composed of 360 patients with ADHF who had at least one symptom and one sign of volume overload. Patients were randomized to receive dopamine, nesiritide, or placebo, interventions that did not influence the primary end points of change in cystatin C or diuresis (11). Importantly, all patients received aggressive open-label diuretics equivalent to 2.5 times their daily home loop diuretic dose. Moreover, this dosing of furosemide comprised the randomized high-dose arm of the Diuretic Optimization Strategies Evaluation (DOSE) trial that significantly increased the incidence of WRF (12). A consort diagram is provided in Supplementary Figure 1. Of the 360 total patients included in the ROSE-AHF trial, we excluded patients with missing biomarker data and timed urine outputs, leaving 270 patients remaining for analysis. Data and other research materials for ROSE-AHF were obtained from the National Heart, Lung, and Blood Institute BioLINCC.

Modeling of Renal Function

Table 1 defines the study metrics of creatinine. Further discussion of the concept underlying kGFR and derivation of kGFR equations have been previously reviewed, and all equations used for this analysis are located in Supplemental Appendix 1 (8,9). An initial evaluation of the effects of VD was undertaken using a simple dilution equation. In this experiment, each of the ROSE-AHF patients had their TBW (the VD of creatinine) changed by the amount of net diuresis that occurred over 72 hours, without accounting for increased excretion as serum creatinine levels rose (13,14). Due to the absolute mass balance of creatinine, we can calculate the resulting concentration of creatinine through the following equation:[eCr]Instant VD=[Cr]0V0Vt

Table 1. - Definitions of calculated creatinine
Abbreviation Definition Interpretation
Cr observed Difference in the measured serum creatinine at 72 hours and baseline serum creatinine Patients with a Cr observed ≥0.3 mg/dl were considered to have “worsening renal function”
eCr Instant VD Calculated creatinine value comprising the product of baseline measured serum creatinine and the percent change in VD from baseline to 72 hours “Worst-case” effect of 72-hour change in TBW on serum creatinine assuming the 72-hour diuresis resulted in an instantaneous change in TBW contracting around the fixed mass of creatinine. Because it is calculated instantaneously, increased renal excretion of creatinine over the 72 hours is unaccounted for.
eCr 72HR VD Calculated similarly to eCr Instant VD but with an assumed stable creatinine production and renal elimination over 72 hours Estimates the effect of VD after accounting for the increased elimination of creatinine during that time when hemoconcentration of creatinine increases concentration, and thus the gradient for renal elimination, over the 72-hour period
eCr 72HR Kinetic Calculated serum creatinine at 72 hours incorporating both sequential changes in VD change in measured serum creatinine over the 72-hour study period Most sophisticated model to predict the 72-hour serum creatinine adjusting the GFR daily over 72 hours to the daily measured serum creatinine and daily change in VD
VD, volume of distribution; TBW, total body water.

Cr0 is the initial measured creatinine concentration. V0 represents the initial VD of creatinine, which was conservatively estimated to comprise 50% of the participant’s initial weight on presentation (lower assumed percentage body water would bias toward larger diuresis-induced changes, making these analyses more sensitive). Vt was calculated by subtracting the net intake and urine output over the 72-hour study period from V0. We performed sensitivity analysis, calculating creatinine’s VD as 60%–80% of initial weight. The above thought experiment reflects a worst-case, nonphysiologic process that does not account for increased renal excretion throughout the 72-hour period as creatinine concentration rises due to TBW contracting around the fixed mass of creatinine.

To isolate the effect of changes in volume while renal clearance is ongoing, the following equation was developed. Assuming the GFR stays constant at its initial value, the model calculates the expected creatinine concentration due to a change in VD occurring over 72 hours. This gradual volume change is more realistic than the instantaneous hemoconcentration above.[eCr]72HR VD=[Crobserved]0+[1(V0V0+ΔVΔtt)(1+GFRΔVΔt)](CreGenGFR+ΔVΔt[Crobserved]0)

Initial VD of creatinine is estimated as previously described and the VD at 72 hours was estimated by subtracting net output from the initial VD. A creatinine generation rate was calculated by multiplying the initial creatinine concentration at baseline with its corresponding eGFR, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation (15). This creatinine generation value was used to calculate the expected serum creatinine on the basis of a gradual and steady change in VD while the GFR remained stable.

Naturally, the eCrInstant VD and the eCr72HR VD are going to differ from the Crobserved. The actual measured creatinine at 72 hours is the result of the dynamic interplay between volume changes and GFR. Previously, the GFR was held constant at its initial value to calculate eCr72HR VD. In reality, the GFR can change over time. We ascertain this changed GFR from the Crobserved by applying a kGFR equation (8,16). The kGFR value was calculated using the Newton method (17).kGFRn+1=kGFRn+[Cr]0+[1(V0V0+ΔVΔtt)(1+kGFRnΔVΔt)](CreGenkGFRn+ΔVΔt[Cr]0)[Cr]t(V0V0+ΔVΔtt)(1+kGFRnΔVΔt)1ΔVΔtln(V0V0+ΔVΔtt)(CreGenkGFRn+ΔVΔt[Cr]0)+[1(V0V0+ΔVΔtt)(1+kGFRnΔVΔt)]CreGen(kGFRn+ΔVΔt)2

Initial volume, changes in VD, and creatinine generation were calculated similarly. Sequential changes in measured serum creatinine and volume over the 72-hour study period were used to calculate the corresponding kGFR. If this kGFR was allowed to achieve a new steady state, the future creatinine value can be calculated with a rearranged Modification of Diet in Renal Disease equation.[eCr]72HR Kinetic=(kGFRAge0.203175race, sex factor(s))11.154

Statistical Analyses

Baseline characteristics are presented with continuous variables presented as a mean±SD or median and interquartile range (IQR), with categoric variables presented as n (%). To maintain consistency with prior publications, WRF was defined as a ≥0.3 mg/dl increase in creatinine concentration from baseline to 72 hours. Patient characteristics were compared between those participants that developed WRF and those that did not. Linearity of the relationship between changes in creatinine derived from each model and net output was assessed by examining trends across deciles of net output over 72 hours. We performed rank-based correlation between the changes in calculated creatinine and net output and report them as the Spearman ρ. To estimate contribution to changes in calculated creatinine by VD alone, the estimated change in eCr72HR VD was subtracted from eCr72HR Kinetic. This was then expressed as a percentage of the change in eCr72 HR Kinetic. The independent t test or Mann–Whitney test was used to compare continuous variables between groups, as appropriate. Cox proportional hazard regression was used to examine survival between groups. Statistical analysis was performed with SPSS Statistics version 23 (IBM Corp, Armonk, NY), and statistical significance was defined as a two-tailed value of P<0.05 for all analyses.


Baseline characteristics of the study population are described in Table 2. This group closely mirrored the overall ROSE-AHF trial. Patients in this study population underwent an aggressive diuretic regimen, with a mean of 645±443 mg furosemide equivalents administered, resulting in a median (IQR) net fluid output of 4394 (2678–6426) ml over the 72-hour trial period. The mean change in Crobserved was 0.0±0.39 mg/dl from baseline to 72 hours, with 17% (47 of 270) of patients having a ≥0.3 mg/dl increase in Crobserved.

Table 2. - Baseline characteristics
Characteristics Overall Cohort (N=270) No WRFkinetic (N=202) WRFkinetic (N=68) P Value
 Age, yr, mean±SD 70±12 69±12 72±11 0.10
 Male sex, n (%) 200 (74) 149 (74) 51 (75) 0.66
 Race white, n (%) 208 (77) 153 (76) 55 (81) 0.42
Clinical history
 SBP, mm Hg, mean±SD 116±18 115±17 120±18 0.03
 Baseline weight, kg, mean±SD 94.5±24.9 92.8±24.1 99.7±26.5 0.05
 LVEF, %, median (IQR) 33 (21–52) 30 (20–54) 33 (25–46) 0.75
 DM type 2, n (%) 146 (54) 106 (53) 40 (59) 0.29
 ICD, n (%) 117 (43) 86 (43) 31 (46) 0.78
 Hyperlipidemia, n (%) 212 (79) 153 (76) 59 (87) 0.06
Laboratory values
 Baseline creatinine, mg/dl, mean±SD 1.73±0.53 1.69±0.49 1.83±0.63 0.10
 72-H creatinine change, mg/dl, mean±SD 0.00±0.39 −0.15±0.29 0.44±0.28 <0.001
 Baseline cystatin C, mg/dl, mean±SD 1.82±0.56 1.76±0.54 1.99±0.60 0.004
 Baseline GFR CKD-EPI, ml/min per 1.73 m2, mean±SD 42±14 43±14 39±13 0.04
 BUN, mg/dl, mean±SD 42±22 43±23 41±20 0.60
 NT-proBNP, pg/ml, median (IQR) 5258 (2331–10,120) 5215 (2455–9748) 6149 (1988–11,349) >0.99
 NGAL, ng/mg, median (IQR) 68.7 (13.6–503.7) 66.9 (13.2–538.0) 81.5 (21.4–412.8) 0.49
 NAG, mU/mg, median (IQR) 8.9 (5.1–17.1) 8.8 (5.2–17.7) 9.0 (4.7–16.9) 0.98
 KIM-1, pg/mg, median (IQR) 964.5 (334.1–3219.6) 886.6 (303.1–3226.0) 1032.4 (377.0–3726.0) 0.44
 Placebo, n (%) 89 (33) 66 (33) 23 (34) 0.99
 Dopamine, n (%) 91 (34) 67 (33) 24 (35)
 Nesiritide, n (%) 90 (33) 69 (34) 21 (31)
 72-H total IV furosemide equivalent, mg, mean±SD 645±443 641±446 665±436 0.70
 72-H net output, ml, median (IQR) −4394 (−2678 to −6426) −4688 (−2914 to −6956) −3638 (−2113 to −5488) 0.002
No WRFkinetic, participants with eCr72HR Kinetic <0.3 mg/dl; WRFkinetic, participants with eCr72HR Kinetic ≥0.3 mg/dl; SBP, systolic BP; LVEF, left ventricular ejection fraction; IQR, interquartile range; DM, diabetes mellitus; ICD, implantable cardioverter defibrillator; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; NT-proBNP, N-terminal prohormone brain natriuretic peptide; NGAL, neutrophil gelatinase-associated lipocalin; NAG, N-acetyl-β-d-glucosaminidase; KIM-1, kidney injury molecule 1; IV, intravenous; eCr72HR Kinetic, estimated change in creatinine accounting for both change in volume of distribution and non–steady state during creatinine measurement.

Isolating Contribution of Change in VD

Using a simple dilution equation to evaluate a “worst-case” situation in which the 72 hours of net fluid output of each patient was modeled as if it were an instantaneous diuresis, 19% (52 of 270) of the study population had sufficient diuresis to elicit a ≥0.3 mg/dl worsening of eCrInstant VD, purely on the basis of a change in VD. The median net fluid output required to elicit an increase of ≥0.3 mg/dl eCrInstant VD was 13% of the patient’s TBW, which translated to a median (IQR) −7526 (−5933 to −9150) ml of fluid loss. The trend in Crobserved across deciles of net output are shown in Figure 1A. Comparatively, the trend in calculated eCrInstant VD in this scenario across deciles of net output are shown in Figure 1B, which demonstrates rising eCrInstant VD with increasing net output. However, very few of the patients who were aggressively diuresed and predicted to have an increase in eCrInstant VD ≥0.3 mg/dl had an increase in Crobserved of ≥0.3 mg/dl (four of 52 patients). To the contrary, 69% (36 of 52) of these patients had an improvement in Crobserved over the 72-hour period. Sensitivity analyses varying the assumed VD of creatinine by percent of body weight showed a decreasing number of participants developing WRF with increasing assumed percentage of TBW (Supplemental Table 1).

Figure 1.:
Changes in baseline to 72-hour observed and calculated creatinine by deciles of net fluid output. ΔCr Observed, observed change in creatinine over the 72-hour treatment period in the ROSE Acute Heart Failure Randomized Trial; ΔeCr 72HR VD, estimated change in creatinine with 72 hours of diuresis assuming a constant steady GFR over those 72 hours; ΔeCr Instant VD, estimated change in creatinine that would occur if 72 hours of diuresis were to occur instantaneously with no filtration of creatinine as the serum concentration rose; ΔeCr 72HR Kinetic, estimated change in creatinine accounting for both change in volume of distribution and non–steady state during creatinine measurement.

Given that diuresis cannot happen instantaneously and thus creatinine production and excretion continue during the period of diuresis, we next modeled the expected volume-induced changes in creatinine assuming steady GFR and creatinine production, eCr72HR VD. Incorporating these factors, the magnitude of increase in creatinine was muted and now zero participants had a resulting calculated eCr72HR VD rise ≥0.3 mg/dl (Figure 1C) purely from a change in VD. Notably, there was an inverse correlation between eCr72HR VD and change in Crobserved (r=−0.18, P=0.003), indicating changes in renal filtration dominated the change in Crobserved. Findings were similar in sensitivity analyses varying the assumed VD of creatinine (Supplemental Table 1).

Accounting for Both Change in VD, Non–Steady State Conditions, and Change in GFR

The median (IQR) change in eCr72HR Kinetic was 0.05 (−0.17 to 0.30) mg/dl from baseline to 72 hours. On a population level, the mean eCr72HR Kinetic (1.84±0.76 mg/dl) was statistically significantly different from the 72-hour Crobserved (1.72±0.63 mg/dl; P<0.001). Similarly, the difference in mean 72-hour change in Crobserved (0.00±0.39 mg/dl) and eCr72H Kinetic (0.11±0.50 mg/dl) was statistically significantly different (P<0.001). The median (IQR) change in creatinine attributable to the change in VD was 3% (−21% to 15%). On the individual level, 25% (68 of 270) of patients had a ≥0.3 mg/dl increase in eCr72HR Kinetic, with 65% (44 of 68) also having a ≥0.3 mg/dl increase in Crobserved. Conversely, 94% (44 of 47) of patients with a ≥0.3 mg/dl increase in Crobserved also had an increase eCr72HR Kinetic. Trend in eCr72HR Kinetic across deciles of net output are shown in Figure 1D.

Association with Kidney Tubular Injury Markers and Survival

We previously reported an absence of meaningful association between change in Crobserved with N-acetyl-β-d-glucosaminidase, kidney injury molecule 1, and neutrophil gelatinase-associated lipocalin in the ROSE-AHF population (18). Including the influence of the change in VD on serum creatinine using the kGFR formula, we found a similar lack of association between tubular injury markers and ≥0.3 mg/dl increase in eCr72HR kinetic (P>0.05 for all; Figure 2). Over the 180-day follow-up period, a total of 52 deaths were observed, with no difference in survival in patients with or without a ≥0.3 mg/dl increase in eCr72HR Kinetic (hazard ratio, 0.87; 95% CI, 0.5 to 1.7; P=0.67).

Figure 2.:
No association observed between baseline and 72-hour urinary kidney injury biomarkers in patients with and without worsening renal function. KIM1, kidney injury molecule 1; NAG, N-acetyl-β-d-glucosaminidase; NGAL, neutrophil gelatinase-associated lipocalin; no WRF, participants with Cr 72HR Kinetic <0.3 mg/dl; WRF, participants with Cr 72HR Kinetic ≥0.3 mg/dl.


In this study, we evaluated the contribution of hemoconcentration of creatinine to the commonly observed worsening in serum creatinine during the aggressive diuresis of patients with heart failure (HF). Our first observation was that very large volumes of diuresis over a short interval of time are required to meaningfully change serum creatinine by this mechanism. Notably, even if the diuresis were to occur instantaneously (not allowing any additional filtration of creatinine as the levels rise), a median of 7.5 L of fluid removal was required to produce a 0.3 mg/dl change in creatinine. Even in this nonphysiologic, worst-case experiment, <20% of the population had a large enough fluid loss over 72 hours to potentially induce WRF. Accounting for continued creatinine production/filtration over the 72 hours, the change in VD alone was incapable of producing a ≥0.3 mg/dl increase in creatinine in any participant. After accounting for both changes in VD and changes in GFR with a kGFR equation, the change in GFR did not materially provide different information than the actual observed change in creatinine. This was true of both the association with urinary tubular injury markers, and the association with mortality. Notably, both the eCrKinetic and Crobserved correlated inversely with the volume of diuresis, indicating an improvement in glomerular filtration with effective decongestion outweighed any effect of hemoconcentration of creatinine. The above results would suggest that, in hospitalized patients with HF undergoing aggressive diuresis, the observed changes in serum creatinine are primarily driven by true changes in glomerular filtration, with minimal influence from hemoconcentration of creatinine.

The importance of changes in GFR in HF has been well recognized and intensely studied over several decades (4,1920–21). Recently, a relatively consistent signal has emerged that context for a change in creatinine heavily modifies the associated prognosis. In the setting of aggressive diuresis, hemoconcentration, or complete decongestion, a small-to-moderate magnitude increase in creatinine does not appear to portend an adverse prognosis (22,23). Furthermore, several studies have looked at the association between changes in serum creatinine and urinary tubular injury markers, suggesting these changes in creatinine are not, in fact, driven by true kidney injury (18,24). The above data thus indicated a benign cause for the changes in creatinine, with hemodynamic/functional changes in GFR and/or hemoconcentration of creatinine as the two plausible remaining candidate mechanisms. The current analyses strongly indicate that the increase in creatinine during diuresis of patients with ADHF is driven by a true change in GFR.

Aberrations in GFR have traditionally been thought to be predominantly hemodynamic and neurohormonal in origin. Notably, reduced renal perfusion, venous congestion, increased intra-abdominal pressure, neurohormonal activation, renin-angiotensin-aldosterone system antagonism, adverse renal effects of loop diuretics, and volume depletion have been highlighted as mechanisms driving cardiorenal interactions (14,252627–28). In mild-to-moderate levels of derangement, these factors would be expected to lead to hemodynamic changes in renal function without structural damage. As such, despite the lack of association with adverse outcomes, the assertion that significant hemodynamically induced changes in GFR are common in HF is not surprising.

One notable finding from this analysis was change in GFR estimated with a kGFR formula did not give meaningfully different information than observed changes in creatinine. Changes in creatinine are common in ADHF, with some series finding that more than half of patients have at least 20% improvement or worsening during treatment (23,29,30). As such, the assumption of steady state is commonly violated at time of ascertainment of creatinine and thus incorporating the slope of change would be expected to provide useful information. However, it is well described that most changes in creatinine during ADHF therapy are of relatively small magnitude and the sampling interval infrequent. Assuming the principles of the kGFR approach are correct, these findings would argue that, on a population level, violations of steady state assumptions are not large enough to make a clinically meaningful effect on GFR estimation.


The equations used in this study use mathematics to model complex physiology. Although the derivations and calculations are precise, certain limitations involving the inputs should be noted. Most important is the assumption of steady state in the calculation of the initial GFR using the CKD-EPI equation and, subsequently, creatinine generation rate, to which the other equations are grounded. In addition, TBW was estimated to comprise 50% of the total body weight of all patients in the study population. This assumption is mitigated by the fact that 50% likely represents an underestimation in the hypervolemic ADHF patient population. The net fluid balance was assumed to occur in a linear fashion throughout the body compartments over the 72-hour period. In reality, diuresis is often episodic and fluctuating. More accurate measurement of kGFR would require frequent sampling of serum creatinine and net output. Lastly, the effect of acute changes in creatinine generation, nonrenal creatinine elimination, and renal creatinine secretion are not accounted for in these analyses. Although the above limitations should caution the reader on quantitative interpretation of the results, it is unlikely these limitations would change the qualitative findings of the study, i.e., that hemoconcentration of creatinine plays a limited role in changes in creatinine.

Our data suggest that quantity and rate of diuresis required for serum creatinine to meaningfully increase primarily due to hemoconcentration in patients with ADHF are larger than typically encountered in clinical practice. The primary driver of changes in serum creatinine is likely to be a substantive change in GFR. Given the absence of association with tubular injury markers and mortality, these changes in GFR are likely hemodynamic/functional in nature. Additional research is required to better understand the underlying mechanisms.


J.L. Asher reports receiving research funding from Sequana Medical and having consultancy agreements with Translational Catalyst. S.G. Coca reports having consultancy agreements with Axon, Bayer, CHF Solutions, 3ive, Renalytix, Reprieve Cardiovascular, Takeda, and Vifor; serving on the editorial boards of CJASN, JASN, and Kidney International; serving as an associate editor for Kidney360; receiving research funding from ProKidney, Renalytix, Renal Research Institute (RRI), and XORTX; having ownership interest in pulseData and Renalytix; having patents and inventions with Renalytix; and serving as a scientific advisor for, or member of, Reprieve Cardiovascular and Renalytix. Z.L. Cox reports receiving research funding from AstraZeneca and Cumberland Emerging Technologies. L.A. Inker reports serving in an advisory or leadership role for the Alport’s Foundation, Diametrix, and Goldfinch; serving as a member of the American Society of Nephrology, National Kidney Disease Education Program, and National Kidney Foundation; having consultancy agreements with Diamtrix and Tricida; receiving research funding (for the institution) from the National Institutes of Health, National Kidney Foundation, Omeros, Reata Pharmaceuticals, and Travere; and having consulting agreements with Omeros and Tricida. J.B. Ivey-Miranda reports serving on a speakers bureau for AstraZeneca, Boehringer Ingelheim, Merck, Moksha8, and Novartis. V.S. Rao reports having patents or royalties with Corvidia Therapeutics and having consultancy agreements with Translational Catalyst. J.M. Testani reports receiving research funding from Abbott, Boehringer Ingelheim, Bristol Myers Squibb, FIRE1, 3ive Labs, Lexicon Pharmaceuticals, Merck, Otsuka, Reprieve, Sanofi, and Sequana Medical; having consultancy agreements with, and receiving honoraria from, AstraZeneca, Bayer, Boehringer Ingelheim, BD, Bristol Myers Squibb, Cardionomic, Edwards Life Sciences, FIRE1, 3ive Labs, Lexicon Pharmaceuticals, Lilly, MagentaMed, Merck, Novartis, Otsuka, Precardia, Regeneron, Relypsa, Reprieve, Sanofi, Sequana Medical, Windtree Therapeutics, and W.L. Gore; having patents or royalties with Corvidia, Reprieve, and Yale University; and having ownership interest in Reprieve and Sequana Medical. F.P. Wilson reports serving on the editorial boards for the American Journal of Kidney Disease and CJASN; receiving research funding from Amgen, Boehringer Ingelheim, Vifor, and Whoop; being the owner of Efference; having other interests in, or relationships with, Gaylord Health Care (on the board of directors) and Medscape (medical commentator); and having consultancy agreements with Translational Catalyst. All remaining authors have nothing to disclose.



See related editorial, “Does More Serum Creatinine Really Just Mean Less Volume?,” on pages .

Author Contributions

J.L. Asher, S. Chen, S.G. Coca, Z.L. Cox, L.A. Inker, D. Mahoney, C. Maulion, D. Negoianu, V.S. Rao, J.M. Testani, J.M. Turner, and F.P. Wilson reviewed and edited the manuscript; S. Chen and J.B. Ivey-Miranda were responsible for methodology; S. Chen, J.B. Ivey-Miranda, C. Maulion, and J.M. Testani were responsible for formal analysis; Z.L. Cox and J.M. Testani were responsible for visualization; J.B. Ivey-Miranda, C. Maulion, and V.S. Rao were responsible for data curation; C. Maulion wrote the original draft; C. Maulion and J.M. Testani conceptualized the study; and J.M. Testani provided supervision.

Data Sharing Statement

All data are included in the manuscript and/or supporting information.

Supplemental Material

This article contains supplemental material online at http://kidney360.asnjournals.org/lookup/suppl/doi:10.34067/KID.0007582021/-/DCSupplemental.

Supplemental Appendix 1.

Supplemental Table 1. Sensitivity analysis total body water.

Supplemental Figure 1. Consort diagram.


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acute kidney injury and ICU nephrology; creatinine; heart failure; hematologic diseases

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