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Chronic kidney disease (CKD) is a major public health problem in Australia and throughout the world.
This article discusses how the estimated glomerular filtration rate (eGFR) automatically reported with biochemical tests is used as an assessment tool for CKD, why creatinine clearance calculated with the Cockcroft-Gault equation is the recommended estimate of GFR for use in drug dose calculations, and the limitations of Cockcroft-Gault to be considered. CKD is often present in the context of cardiovascular disease or diabetes but early CKD is often asymptomatic. Several tests are used for the detection of CKD including albuminuria, albumin: creatinine ratio, haematuria, blood pressure and serum creatinine.
Most Australian pathology laboratories now routinely report an estimated GFR in all biochemical test results that include serum creatinine. While the eGFR reported with all serum creatinine test results for those aged 18 years of age or over is a tool for CKD screening, it is not recommended for routine use in calculating dose reductions required for patients with CKD. The Australia Medicines Handbook (AMH) recommends that such reported eGFR values are not equivalent to CrCl (creatinine clearance) and should not be used for estimating drug dose reductions in renal impairment.
The Cockcroft-Gault equation (Figure 1) remains the most widely recognised equation for the calculation of creatinine clearance and its estimation of GFR. When using Cockcroft-Gault to estimate GFR for the purpose of dose reduction recommendations, it is important to remember the limitations of the equation and that certain clinical settings require careful interpretation of the result. Serum creatinine, and thus the calculated estimate of GFR, can be influenced by many factors. It is important to note that in overweight and obese patients, the ideal body weight must be used in the Cockcroft-Gault equation as using the patient’s actual weight will overestimate renal function and lead to possible overdosing. In summary, it is important to note that the eGFR reported with biochemical test results is an important indicator and screening tool for the early detection and diagnosis of CKD. The use of the Cockcroft-Gault equation to calculate CrCl and estimate GFR is relatively simple and reliable, provided that the limitations are considered when using the calculated data. Higher muscle mass is associated with better outcomes and longevity in patients with chronic disease states. In 118 hemodialysis patients, we found that the 3-month averaged serum creatinine concentration correlated well with DEXA-measured LBM. The accurate assessment of nutritional status and body composition is of paramount importance in providing nutritional care to patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD), as malnutrition and the protein–energy wasting syndrome are among the strongest risk factors for morbidity and mortality. The accurate assessment of nutritional status and body composition is instrumental in providing optimal care to patients with chronic disease states including those with CKD. In the past few years, emerging data have revived the old notion that serum creatinine level is a reliable and cost-effective surrogate marker of muscle mass in stable chronic dialysis patients in whom kidney function is minimal to nonexistent and who maintain stable dose of dialysis therapy [4, 7–12]. We studied hemodialysis patients who participated in the Nutritional and Inflammatory Evaluation in Dialysis (NIED) Study [14].
The reference test for assessment of body composition was DEXA performed with a Hologic Series Delphi-A Fan [23] Beam X-ray Bone Densitometer with software version 12.4 (Hologic, Bedford, MA, USA). There was no statistical difference between the total body water and creatinine kinetics techniques, but the bio-impedance values were systematically higher than those obtained by the kinetic technique. To examine the validity of the creatinine kinetic method for determining creatinine production by comparing it with the direct dialysate creatinine quantification method as a means to assess protein nutritional status of hemodialysis patients. To investigate determinants of 24-h creatinine excretion in urine and prospectively to investigate whether 24-h creatinine excretion in urine, as measure of muscle mass is associated with mortality and graft loss in renal transplant recipients.
Urinary creatinine excretion as measure of muscle mass is associated with mortality and graft loss after renal transplantation. There was no difference between LBM estimated by BIA and DEXA and both correlated well with SCr.
To examine associations of BMI, pretransplant SCr as a surrogate marker of muscle mass and changes in weight with mortality in a large national cohort of transplant-waitlisted dialysis patients. BMI should not be used by itself but in conjunction with SCr as a surrogate of LBM to improve its morbid-mortality predictive power. To analyze the association between predialysis SCr and change in SCr between midweek dialysis sessions and nutritional markers and mortality.
Predialysis creatinine and interdialytic change in creatinine are both strongly associated with proxies of nutritional status and mortality in hemodialysis patients and are highly correlated.
The above-referenced composite ranking score was also used in waitlisted dialysis patients to assess associations of serum creatinine with mortality [25]. Given the undeniable fact that serum creatinine co-varies closely with the skeletal muscle mass, its utility in estimating the glomerular filtration rate (eGFR) using such equations as the modification of diet in renal disease (MDRD) or Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) may not be an appropriate primary outcome measure when subjects exhibit weight variations during a given study [28]. In individuals whose kidney function is in steady state and still have urine output, the 24-h urinary creatinine concentration is usually a reliable surrogate of skeletal muscle mass, although it may also co-vary with the amount of dietary meat intake [13, 46].
Given a main origin of serum creatinine being skeletal muscle-based creatine, it has long been argued that ingestion of striated muscle in form of meat, chicken and fish can increase serum creatinine level [47].
Serum carnitine level is lower in vegetarians [52] and in patients on parenteral diet [53] than in omnivores, suggesting that serum carnitine is a potential marker of meat intake. The dipeptide beta-alanyl-histidine (carnosine) is present in muscle and nerve tissues in most vertebrates, although levels are low in most kinds of fish. Anserine (beta-alanyl-1-methyl-l-histidine), a dipeptide similar to carnitine and ophidine, is present in skeletal muscle from many types of vertebrate animals [55].
Serum creatinine is a reliable, cheap, and easily accessible marker of muscle mass in stable chronic dialysis patients. It is estimated that 10% of all adults presenting to a general practitioner in Australia have CKD while 80% have at least one risk factor for CKD. The clinician must therefore recognise and apply the active approach required to detect CKD in high risk patients including: those who are overweight or obese, have hypertension, have a familial history of CKD, are a smoker, or are of Aboriginal or Torres Straight Islander decent and 30 years of age or older.
An eGFR of 2 that is present for three months or more with or without other evidence of kidney damage (such as proteinuria), is diagnostic for CKD. This remains in line with most manufacturer’s dose reduction recommendations, which are largely based on data calculated using the Cockcroft-Gault equation and not eGFR values. It provides an instrument for better risk management in CKD with the aim of optimal disease management and best health outcomes. This calculation remains the most widely used and recognised for dose reduction considerations. Automatic eGFR reporting – its role in screening for kidney disease and drug-dosing decisions. Imaging studies such as dual-energy X-ray absorptiometry (DEXA) are among the gold standard methods for assessing body fat and lean body mass (LBM), approximately half of which is comprised of skeletal muscle mass.
The recent literature regarding serum creatinine as a surrogate of muscle mass is summarized, as is the literature concerning the use of other measures of muscle mass, such as plasma gelsolin and actin, and urinary creatinine excretion. We advance the hypothesis that in both health and disease, under steady state, serum creatinine can serve as a reliable muscle mass biomarker if appropriate adjustment for full or residual kidney function and dietary meat intake is undertaken. Body composition is typically divided into fat mass and fat-free mass also known as lean body mass (LMB).

Imaging studies such as dual-energy X-ray absorptiometry (DEXA) are among the gold standard methods for assessing body composition [1, 5, 6].
1 Schematic presentation of creatinine metabolism and the pathway of breakdown of creatine phosphate in the muscle (adapted from Heymsfield et al.
Measurements were performed as previously described [1, 5, 6] with participants wearing a hospital gown, with no metal snaps, and all artifacts removed. Patients in the main cohort were slightly older than the DEXA sub-cohort and included fewer men and African-Americans compared to the DEXA sub-cohort. Despite their variable results, most studies show that serum creatinine correlate well measures of muscle mass.
To assess the prevalence of malnutrition and to study the relationship between various nutritional parameters in CKD patients. HGS showed a strong correlation with DEXA measured LBM and low HGS was the factor with the strongest independent association with malnutrition. The creatinine kinetic model is a method to calculate the creatinine production rate using pre and postdialysis creatinine and was found to correlate with muscle mass estimated by Cr in dialysate and CT thigh muscle though there was some overestimation particularly in females perhaps due to no sex specific formulas or accurate volume of distribution calculation. To examine and compare the sex-specific mortality predictability of LBM and FM, assessed by the NIR interactance.
In men, the lowest quartile of FM was associated with an increased risk of death where higher FM, and not LBM was associated with greater survival. The excess FM relative to LBM was linearly associated with greater survival in all subjects. To examine the correlations of anthropometric and biochemical measures with DEXA-measured LBM in HD patients to determine which serves as a better surrogate for LBM. To study the outcome predictability of LBM estimated by MAMC and SCr and compare them with TSF. Decreased risk of death was observed in hemodialysis patients with higher MAMC, higher SCr and higher TSF. High MAMC are associated with greater survival in patients with low TSF and in patients with high TSF thickness, thus suggesting that muscle mass may possibly be more important than peripheral body fat mass in predicting survival in HD patients. To validate 3-month averaged pre-HD SCr as a marker for muscle mass in subgroup of 117 patients. Higher BMI (up to 45) and a higher SCr are each independently and incrementally associated with greater survival even after adjustment for nutritional status and inflammation. To study adjusted dry weight and SCr concentration and their changes over time as predictors of mortality in HD patients.
A gain in dry weight accompanied by a concurrent increase in muscle mass (SCr) is associated with the greatest survival, whereas weight loss accompanied by loss in muscle mass bears the highest mortality. To examine correlation between DEXA-measured LBM with SCr (3-month averaged), albumin, prealbumin, anthropometric measurements, nPNA and subjective assessment. LBM calculated by SCr, MAMC, and handgrip strength had the highest correlations with LBM calculated by DEXA and when validated by NIR interactance. To examine the relationship of pretransplant BMI and SCr and post-transplant patient and graft survival.
Patients with lower 3-month averaged pretransplant creatinine had higher risk of death after adjustment for inflammation and transplant data as well as higher risk of graft failure. Higher serum creatinine, as a surrogate of larger muscle mass, was independently and incrementally associated with greater survival in waitlisted dialysis patients even after extensive multivariate adjustment for available surrogates of nutritional status and inflammation.
Recently, lower urinary creatinine excretion rate has been shown to correlate with higher cardiovascular events and poorer survival in a cohort of people with coronary artery disease [3].
Hence, one cannot ignore the role of striated muscle ingestion, which is also rich in protein, in the forgoing discussion. Creatine is produced in the vertebrate body from amino acids l-arginine, glycine and l-methionine primarily in the kidney and liver. However, it is not clear that carnitine is a marker of meat intake in hemodialysis patients, in whom the supplementation of carnitine may or may not have an impact on the cardiovascular system [54]. Since dietary intake of nerve tissues is limited, carnosine might be a potential marker of muscle intake from animals, fish and shellfish [50, 55]. Human muscle does not contain anserine, which could therefore be a good candidate to measure meat intake in ESRD patients [56].
As 3-methyl-l-histidine can originate from endogenous muscle sources, it would be an unreliable marker of meat intake [59].There are currently no data regarding the role of these molecules as markers of meat intake in CKD or ESRD patients. Using serum creatinine as a surrogate marker of skeletal muscle mass, it has been proven that muscle mass is an important predictor of survival in dialysis patients. The authors of this manuscript certify that they comply with the ethical guidelines for authorship and publishing in the Journal of Cachexia, Sarcopenia and Muscle [64].
Comparison of skinfold thicknesses and bioelectrical impedance analysis with dual-energy X-ray absorptiometry for the assessment of body fat in patients on long-term haemodialysis therapy. Total-body skeletal muscle mass: development and cross-validation of anthropometric prediction models. However serum creatinine can be used to derive a value for creatinine clearance and an estimation of GFR and renal function. An eGFR of 2 is associated with increased risk of adverse renal, cardiovascular and other clinical outcomes, irrespective of age.
Elaborate imaging devices, however, are not commonly available in routine clinical practice and therefore easily accessible and cost-effective, but reliable muscle mass biomarkers are needed.
We have also reviewed the role of dietary meat intake in serum creatinine variability along with several biomarkers of dietary meat intake (creatine, carnitine, carnosine, ophidine, anserine, 3-methyl-l-histidine and 1-methylhistidine). Compared to body fat mass, which stores energy in the form of adipose tissue, LBM includes muscle and visceral proteins and consists predominantly of water, protein, glycogen and minerals.
However, this method requires an instrument that is not commonly available in clinical practice, and therefore other easily accessible, cost-effective and reliable markers of body composition are needed.
Under the steady-state and stable kidney function, creatinine is usually produced at a relatively constant rate by the body depending on the absolute amount of muscle mass [13].
Participants laid supine on the table and were centered in the scan field with arms at their sides, palms down and thighs separated. Table 2 illustrates differences based on plot-based analyses and provides the correlation test results between DEXA-measured LBM and the LBM derived from three previously described regression equations using serum creatinine, HGS and mid-arm muscle circumference (MAMC) [12].
Additionally, there has been a sizeable literature demonstrating that low LBM in the dialysis population is associated with increased mortality. A weight loss with gain of muscle mass confers higher survival than weight gain with loss of muscle mass. Additionally, patients with high muscle mass and low body weight reported the best survival. Plasma gelsolin binds to actin and may play a role in innate immunity neutralizing exogenous bacterial lipid mediators such as lipopolysaccharide and lipoteichoic acid [39, 40].

As to whether circulating myosin is a positive or negative correlate of muscle mass or whether any meaningful association exists remains to be seen in future studies. This is especially the case in view of our own previous publications that show that higher protein intake and better nutritional status is associated with higher serum creatinine levels and greater survival [48]. Similarly to other abovementioned markers, it is not known whether carnosine is a good marker of meat intake in ESRD patients.
We are not aware of any study about the use of these markers of meat intake in in the setting of renal dysfunction. While several new biomarkers have been proposed as surrogate markers of muscle mass, currently, there is not enough evidence to support the clinical use of these molecules for this purpose. This equation does not require the patient’s actual or ideal body weight to be known. One such marker is serum creatinine, derived from muscle-based creatine, which is inexpensive and ubiquitously available, and it can serve as a biomarker of skeletal muscle mass in human subjects. In people with water retaining states, such as CKD, it is also important to assess body water volume separately from the other components of LMB. Ideally, the measurements in a simple blood test combined with height, weight, and gender would be a convenient approach to estimate LBM including skeletal muscle mass and fat mass. Creatinine is filtered out of the blood by the glomeruli (and is excreted to smaller extent in the proximal tubules of the kidney). Legs were rotated inward 25° until their toes touched each other and then taped together to maintain this position. The concordant combination of the changes in these two body composition surrogates, if pointing in the same direction, maintained the same graded death predictability [25]. It was argued that weight loss associated reduction in skeletal muscle might have artificially increased eGFR in this study [30], although the investigators clarified that the weight loss in the intervention group did not co-vary with serum creatinine [30]. Similarly to stem cell transplant patients [41], critically ill surgical patients [42], major trauma [43] and septic patients [44], low plasma gelsolin is associated with increased mortality in hemodialysis patients [36]. As one instance of this, we have already reported that greater appetite is positively associated with survival in these hemodialysis patients [49]. By simultaneously measuring serum creatinine, another kidney filtration marker (such as Cystatin C) and a dietary meat intake marker, we should be able to develop equations that can reliably estimate total muscle mass in both healthy people and patients with chronic disease states. The LBM compartment therefore is heterogeneous and its measure is affected by fluctuations in water and electrolyte distribution, which are of a more dynamic nature in patients receiving renal replacement therapy [1]. Since there is little to no tubular reabsorption of creatinine, its renal clearance is often used to estimate glomerular filtration rate.
The body composition of 757 of these patients was measured using the portable NIR technique in the dialysis clinics, and 725 of the patients also had triceps skinfold thickness (TSF), mid-arm muscle circumference and serum creatinine measurements.
Scans were analyzed using the whole body fan beam method to determine lean mass, fat mass, bone mineral content and % total body fluid. They used a new method for calculating a composite ranking score, and confirmed that BMI (measured by 3-month averaged BMI) and serum creatinine levels (3-month averaged dialysis dose-adjusted serum creatinine concentrations) simultaneously predicted decreased mortality even after extensive multivariate adjustment (including for measures of nutritional status and inflammation) [9]. Assuming the plasma gelsolin level is a marker of muscle mass in hemodialysis patients, the results of these observations support previous findings that protein–energy wasting has a major role in the mortality of ESRD patients [18, 45].
It is important to note that many dialysis patients have minimal to no urine output, so that the urine creatinine cannot be measured in this group of patient. Greater appetite is most likely associated with greater ingestion of striated muscle, which can increase serum creatinine.
Our research groups is currently engaged in developing such approaches, given the importance of both quality and quantity of skeletal muscle mass and emerging pharmaceutical interventions to module and improve muscle status in health and disease.
Under stable kidney function, the serum or plasma concentration of serum creatinine can also reflect skeletal muscle mass, if its non-muscle-mass-dependent variations (such as due to renal filtration or meat intake) can be accurately accounted for. One out of every five of these patients, selected randomly underwent additional testing in the General Clinical Research Center (GCRC) on the Harbor-UCLA campus that included DEXA and other body composition measures. Figure 2 shows the association between LBM and serum creatinine based on the prediction models [12]. In a sub-cohort of patients in whom change could be examined, weight decline and serum creatinine decline in the setting of stable dialysis dose (indicating muscle mass loss) were both associated with increased mortality, whereas a rise in creatinine was associated with reduced mortality [9]. Hence, when serum creatinine is used as a surrogate of muscle mass, it is important that dietary meat intake can be accounted for. Recent studies suggest that higher muscle mass is associated with greater longevity in people with CKD and other chronic disease states [3, 4].
In people with stable kidney function and urine output, a 24-h urinary creatinine is usually a constant number based on skeletal muscle mass save variations due to meat intake [13]. Hence, 118 patients participated this pilot body composition substudy, which took place on the day after their routine hemodialysis treatment.
Figure 3 depicts cubic splines that illustrate the association between the DEXA-measured LBM and the LBM estimated by each of the three regression equations based on serum creatinine, MAMC and HGS. Concordant changes in these two body composition surrogates also predicted mortality, but analyses of discordant combinations indicated that creatinine (and thus presumably muscle mass) had a stronger impact on most patients in this cohort [9]. A recently published paper by Dragsted [50] has summarized the most important biomarkers of meat intake in healthy populations [50]. Serum creatine would therefore seem to be a promising marker for meat and fish intake, although correction for muscle mass measured by other techniques would be required for quantitative estimates [50]. We present and summarize the recent literature regarding serum creatinine as a surrogate marker of muscle mass, show new information supporting this contention (including the results of a pilot study that examines the correlation between serum creatinine and muscle in dialysis patients) and review the literature of other markers of muscle mass and the role of dietary meat intake in creatinine variability as well as other biomarkers of meat intake. The association with serum creatinine was strong, linear and with narrow confidence intervals.
They found that lower creatinine excretion as a measure of muscle mass was associated with mortality and graft loss after renal transplantation, independent of insulin resistance and its related factors [27].
However, we are unaware of any study examining creatine as a marker of meat intake in CKD or ESRD patients. In this latter study, serum creatinine, MAMC and HGS displayed the highest correlations with LBM. A true creatinine clearance would be needed to substantiate true changes in GFR in such studies that examine renal function as the main outcome measure.
The authors developed three regression equations based on serum creatinine, MAMC and HGS to estimate LBM [12].
In women, there was less bias with serum creatinine and MAMC compared to other methods [12]. Nevertheless, serum creatinine-based equation to estimate LBM was reliable and practical in this study.

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