- Email: [email protected]
Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with non-dialysis chronic kidney disease
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
YCLNU4047_proof ■ 6 November 2019 ■ 1/7
Clinical Nutrition xxx (xxxx) xxx
Contents lists available at ScienceDirect
Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Original article
Q4 Q3
Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with non-dialysis chronic kidney disease Yu-Li Lin a, b, Shu-Yuan Chen b, Yu-Hsien Lai a, Chih-Hsien Wang a, Chiu-Huang Kuo a, Hung-Hsiang Liou c, **, Bang-Gee Hsu a, d, * a
Division of Nephrology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, 97004, Taiwan Department of Public Health, Tzu Chi University, Hualien, 97004, Taiwan Division of Nephrology, Department of Internal Medicine, Hsin-Jen Hospital, New Taipei City, 24243, Taiwan d School of Medicine, Tzu Chi University, Hualien, 97004, Taiwan b c
a r t i c l e i n f o
s u m m a r y
Article history: Received 2 August 2019 Accepted 27 October 2019
Background & aims: Muscle wasting is highly prevalent in patients with chronic kidney disease (CKD). However, the assessment of skeletal muscle mass and strength in clinical settings is not commonly available. We aimed to evaluate the feasibility of serum creatinine/cystatin C (Cr/CysC) ratio in the assessment of muscle wasting. Methods: In 272 patients with CKD aged 66.5 ± 15.1 years, skeletal muscle mass and handgrip strength (HGS) were assessed. Skeletal muscle index (SMI) was calculated as skeletal muscle mass/height2. Low muscle mass was defined as SMI below the sex-specific 10th percentile of study population and low handgrip strength as less than 26 Kg for men and 18 Kg for women. Results: The Cr/CysC ratio was significantly lower in both the low SMI and low HGS groups. Moreover, the Cr/CysC ratio correlated with SMI (r ¼ .306, p < .001) and HGS (r ¼ .341, p < .001). After adjusting for confounding factors, age, sex, waist circumference, body fat mass, and Cr/CysC ratio were independently associated with SMI, whereas age, sex, diabetes, hemoglobin, estimated glomerular filtration rate, urine protein/creatinine ratio, SMI, and Cr/CysC ratio were independently associated with HGS. Conclusions: Cr/CysC ratio appears to be a promising surrogate marker for detecting muscle wasting in patients with CKD. Further studies are needed to extend our findings. © 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Keywords: Cystatin C Creatinine Muscle wasting Sarcopenia Chronic kidney disease
1. Introduction Chronic kidney disease (CKD), with an estimated prevalence of 11%e13% [1,2], is a major public health problem worldwide, especially in the aging population [3,4]. During the aging process, senescence is usually accompanied by a progressive loss of both skeletal muscle mass and function, which is also known as sarcopenia [5,6]. Furthermore, patients with CKD are also vulnerable to additional risks of muscle wasting. These exacerbating factors occur along the course of CKD, which include inflammation, acidosis,
* Corresponding author. Division of Nephrology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97004, Taiwan. ** Corresponding author. E-mail addresses: [email protected] (Y.-L. Lin), [email protected]. tw (S.-Y. Chen), [email protected] (Y.-H. Lai), [email protected] (C.-H. Wang), [email protected] (C.-H. Kuo), [email protected] (H.-H. Liou), [email protected] (B.-G. Hsu).
malnutrition, impaired insulin signaling, decreased sex or growth hormone, angiotensin II overexpression, and uremic toxins accumulation. Muscle wasting may not only result in frailty, falls, fractures, and poor quality of life but also enhance the risk of infection and even premature death [7e11]. Thus, early detection of muscle wasting is of paramount importance in CKD patients. Although magnetic resonance imaging, computed tomography, dual-energy x-ray absorptiometry, and bioimpedance analysis are usually recommended for assessing skeletal muscle mass, these measurements are not commonly applicable [9]. In clinical practice, reliable surrogate serum markers for prediction of muscle wasting in nondialysis CKD patients are unavailable currently. Serum creatinine, a 113-Da product of creatine phosphate from skeletal muscle, is a well-established predictor of renal function status and muscle mass in patients undergoing dialysis [12]. Another predictor, serum cystatin C, a 13-kD cysteine proteinase inhibitor expressed in all nucleated cells, is less affected by the volume of skeletal muscle mass and is recognized as a more reliable
https://doi.org/10.1016/j.clnu.2019.10.027 0261-5614/© 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 2/7
2
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
marker for renal function [13,14]. Loss of skeletal muscle mass during the wasting process is only accompanied by a decline in the serum creatinine level, but not in cystatin C. These observations indicate that serum creatinine/cystatin C (Cr/CysC) ratio, instead of either serum creatinine or cystatin C level, should be a more appropriate surrogate marker for detecting muscle wasting in patients with CKD. In fact, positive correlation between Cr/CysC ratio and skeletal muscle mass had emerged in study populations who were admitted to the intensive care unit (ICU), underwent a lung transplant, with amyotrophic lateral sclerosis or diabetes, and in the geriatric population without severe renal impairment [15e20]. In patients treated in ICU, Cr/CysC ratio was also regarded as a predictor for poor outcome [17,20]. However, the correlation between Cr/CysC ratio and skeletal muscle mass and muscle strength in patients with non-dialysis CKD remained unknown. Therefore, we aimed to explore and to compare the relationship of Cr/CysC ratio with both skeletal muscle mass and muscle strength in patients with various stages of CKD.
anthropometric measurements of body composition and HGS were performed by the same well-experienced operator. Fasting blood and urine samples were obtained from all participants. After centrifugation, serum samples were used for biochemical analysis within 1 h of collection. Blood urea nitrogen (BUN), serum creatinine, albumin, total cholesterol (TCH), lowdensity lipoprotein (LDL) levels, and urine protein/creatinine ratio (UPCR) were measured using an autoanalyzer (Siemens Advia 1800, Siemens Healthcare GmbH, Henkestr, Germany). Serum cystatin C levels were measured with a nephelometric Siemens immunoassay. We calculated the estimated glomerular filtration rate (eGFR) from both serum creatinine (eGFRcre) and cystatin C (eGFRcys), according to the Modification of Diet in Renal Disease and CKD-EPI Cystatin C equation, respectively [24,25]. Cr/CysC ratio is calculated as serum creatinine (mg/dL) divided by serum cystatin C (mg/L). The stages of CKD were defined based on the eGFRcys.
2. Materials and methods
To detect a correlation coefficient of about .3 between Cr/CysC ratio, SMI and HGS according to previous studies [19,20], with an alpha level of .05 and a power of 90%, a total of at least 112 patients should be enrolled in the study. Continuous variables were expressed either as the mean ± standard deviation or as the median and interquartile range, according to the data distribution from the KolmogoroveSmirnov test. These variables between the two groups were compared either by applying the Student's independent t-test or by the ManneWhitney U test. Categorical variables were expressed as absolute (n) and relative frequency (%) and analyzed by the chi-square test or Fisher's exact test. The linear trend of variables in different CKD stages was tested using a oneway analysis of variance (ANOVA) or the CochraneArmitage test for trend. Univariable correlations between variables were assessed by Spearman's correlation coefficient. Independent factors associated with SMI and HGS were analyzed by multiple stepwise linear regression. Finally, receiver operating characteristic curves were constructed to assess the diagnostic value of serum Cr/CysC ratio on low muscle mass and low muscle strength. The areas under curves, cut-offs, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were established. Statistical analysis was performed using SPSS software (version 19.0; SPSS Inc., Chicago, IL, USA). A P-value of less than .05 was considered statistically significant.
2.1. Setting and participants A single-center, cross-sectional study was conducted in outpatient clinics at a medical center in Hualien between April 2015 and February 2016. Patients with non-dialysis CKD and older than 20 years of age were recruited; while, patients who had malignancy, acute infection, gastrointestinal bleeding, amputated limbs, and were wheelchair-bound or bed-ridden were excluded. CKD was defined as a decrease of renal function or the presence of kidney damage for more than 3 months, according to the Kidney Disease Outcomes Quality Initiative guidelines [21]. Diabetes mellitus (DM) was defined based on history or anti-diabetic drug use, hypertension on history or with anti-hypertensive treatment, and hyperlipidemia on history or receiving lipid-lowering medication. The definition of cardiovascular (CV) disease included coronary artery disease, myocardial infarction, or congestive heart failure. All participants signed an informed consent approved by the Institutional Review Board of Tzu-Chi Hospital and all methods were performed in accordance with the relevant guidelines and regulations. 2.2. Measures Height and body weight were measured to the nearest halfcentimeter and half-kilogram in patients with light clothes and without shoes. Body mass index (BMI) was calculated as body weight (Kg) divided by height squared (m2). Waist circumference (WC) was measured at the shortest point between the lower rib margin and the iliac crest. Body skeletal and fat mass were assessed using a portable whole body bioelectrical impedance device (Tanita BC 706DB, Tanita Corporation, Tokyo, Japan). This measurement is noninvasive and highly reproducible. The skeletal muscle index (SMI) was calculated as skeletal muscle mass/height2 (Kg/m2). Patients were classified into low and normal skeletal muscle mass groups based on the sex-specific lowest 10th percentile of SMI within the study population [8,22]. Muscle strength was assessed by measuring handgrip strength (HGS) using a Jamar Plus Digital Hand Dynamometer (SI Instruments Pty Ltd, Hilton, Australia) with a precision of one kilogram (Kg) [9]. Patients were instructed to apply as much handgrip pressure as possible. This measurement was repeated three times with a rest period of 1 min for each hand, and the highest value was recorded for analysis. Low muscle strength was defined as an HGS less than 26 kg for men and 18 kg for women, according to the Asian Working Group for Sarcopenia (AWGS) criteria [23]. All
2.3. Data analysis
3. Results 3.1. Demographic and clinical characteristics of patients A total of 272 CKD patients, with a mean age of 66.5 ± 15.1 years, were included in this study. Demographic data and clinical characteristics of all participants are presented in Table 1. Among them, 155 (57.0%) were males, 117 (43%) patients had DM, 218 (80.1%) had hypertension, 167 (61.4%) had hyperlipidemia, and 41 (15.1%) had CV disease. Our female patients were younger, had lower WC, SMI, HGS, hemoglobin, and had higher body fat mass and serum TCH levels when compared with those in male patients. In addition, Cr/CysC ratio was significantly lower in our female patients. 3.2. Clinical characteristics of patients, stratified by different CKD stages All the data stratified by CKD stage are exhibited in Table 2. The distribution of CKD stages was 15.8% for stage 1 and 2, 39.7% for
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 3/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
3
Table 1 Demographic and clinical characteristics of 272 patients with CKD. Characteristics
All Patients (n ¼ 272)
Male (n ¼ 155)
Female (n ¼ 117)
p
Age (years) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
66.5 ± 15.1 26.1 ± 4.8 87.0 (80.0e94.0) 28.9 ± 9.1 17.3 ± 2.7 23.8 (17.5e31.5) 11.9 ± 2.0 4.1 (3.8e4.3) 159.0 (136.0e183.8) 87.0 (70.0e110.0) 29.0 (21.3e46.0) 1.7 (1.2e2.6) 36.5 (21.1e53.8) 1.74 (1.28e2.74) 35.1 (18.9e52.6) 1.00 (.83e1.15) 347.8 (99.6e1109.8)
68.5 ± 14.2 26.3 ± 4.2 89.0 (82.0e96.0) 24.2 ± 6.0 18.8 ± 2.3 29.4 (23.1e35.6) 12.3 ± 2.1 4.1 (3.9e4.2) 157.0 (135.0e177.0) 87.0 (70.0e107.0) 29.0 (20.0e46.0) 1.7 (1.3e2.7) 38.3 (22.2e54.8) 1.72 (1.30e2.68) 36.4 (20.2e54.5) 1.05 (.89e1.19) 304.8 (74.2e1050.1)
63.9 ± 15.8 25.9 ± 5.6 83.0 (76.0e93.0) 35.1 ± 8.7 15.5 ± 1.7 18.8 (14.9e22.6) 11.3 ± 1.6 4.1 (3.8e4.4) 166.0 (142.0e192.0) 87.0 (69.5e114.0) 29.0 (23.0e46.0) 1.6 (1.1e2.4) 33.4 (20.4e53.4) 1.81 (1.28e2.84) 32.2 (17.4e52.4) .87 (.78e1.07) 398.9 (156.9e1206.3)
.013* .536 <.001* <.001* <.001* <.001* <.001* .583 .031* .575 .623 .024* .199 .969 .466 <.001* .154
117 (43%) 218 (80.1%) 167 (61.4%) 41 (15.1%)
69 (44.5%) 127 (81.9%) 89 (57.4%) 26 (16.8%)
48 91 78 15
.565 .395 .121 .367
(41.0%) (77.8%) (66.7%) (12.8%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). CKD, chronic kidney disease; BMI, body mass index; WC, waist circumference; SMI, skeletal muscle index; HGS, handgrip strength; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant between male and female patients.
Table 2 Clinical characteristics of 272 patients, stratified by CKD stages. Characteristics
CKD stage 1e2 (n ¼ 43)
CKD stage 3 (n ¼ 108)
CKD stage 4 (n ¼ 75)
CKD stage 5 (n ¼ 46)
p for Trend
Age (years) Male (%) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
53.2 ± 16.1 25 (58.1%) 24.7 ± 4.3 80.9 ± 11.9 27.7 ± 8.5 16.7 ± 2.3 30.6 ± 10.5 13.2 ± 1.8 4.1 (4.0e4.4) 177.0 (148.0e201.0) 100.0 (82.0e122.0) 19.0 (16.0e24.0) 1.0 (.8e1.2) 73.9 (60.7e104.5) 1.05 (.87e1.12) 74.3 (63.0e90.9) 1.05 (.82e1.15) 258.4 (26.3e572.2)
67.9 ± 13.1 63 (58.3%) 27.2 ± 5.0 88.0 ± 11.7 30.5 ± 9.6 17.6 ± 2.5 26.4 ± 9.5 12.6 ± 1.6 4.1 (4.0e4.4) 161.0 (138.3e189.0) 88.0 (70.5e118.5) 24.0 (20.0e29.0) 1.4 (1.1e1.7) 49.8 (41.0e55.7) 1.46 (1.29e1.67) 44.1 (37.2e52.4) .95 (.83e1.10) 192.3 (66.6e569.0)
71.5 ± 12.3 42 (56.0%) 25.5 ± 4.8 86.3 ± 11.2 28.7 ± 8.5 17.1 ± 2.7 21.6 ± 7.6 11.4 ± 1.7 4.1 (4.0e4.3) 154.0 (130.0e174.0) 80.0 (66.0e99.0) 38.0 (30.0e48.0) 2.3 (1.9e2.7) 26.1 (21.9e33.0) 2.42 (2.17e2.81) 21.9 (18.2e25.6) .88 (.80e1.08) 409.2 (225.9e1112.7)
67.4 ± 16.0 25 (54.3%) 26.0 ± 4.6 86.7 ± 11.2 26.6 ± 9.0 17.9 ± 3.2 22.6 ± 9.8 9.8 ± 1.4 3.9 (3.7e4.1) 159.0 (133.8e184.2) 86.0 (63.8e104.8) 64.0 (54.0e90.0) 4.6 (3.7e6.4) 12.3 (8.1e16.6) 4.02 (3.55e4.54) 11.6 (10.0e13.4) 1.15 (.94e1.46) 1244.1 (564.9e2245.3)
<.001* .638 .449 .040* .388 .059 <.001* <.001* .014* .003* .003* <.001* <.001* <.001* <.001* <.001* <.001* <.001*
11 (25.6%) 33 (76.7%) 28 (65.1%) 3 (7.0%)
50 86 67 14
41 62 48 19
15 (32.6%) 37 (80.4%) 24 (52.2%) 5 (10.9%)
.391 .563 .287 .193
(46.3%) (79.6%) (62.0%) (13.0%)
(54.7%) (82.7%) (64.0%) (25.3%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). Staging of CKD is based on eGFRcysC. CKD, chronic kidney disease; BMI, body mass index; WC, waist circumference; SMI, skeletal muscle index; HGS, handgrip strength; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant.
stage 3, 27.6% for stage 4, and 16.9% for stage 5. Patients with advanced stages of CKD tended to be older, had lower eGFRcre and eGFRcys levels, higher serum Cr and cystatin C levels, and higher Cr/CysC ratio. Notably, HGS, but not SMI, significantly showed a trend of decline in patients with advanced-stage CKD (Table 2 and Fig. 1).
3.3. Clinical characteristics of patients according to normal or low SMI and normal or low HGS, respectively Among the 272 patients with CKD, 28 (10.3%) had low SMI, and 108 (39.7%) had low HGS. The comparison of the characteristics between patients with low SMI or low HGS and those
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 4/7
4
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
Fig. 1. Skeletal muscle index and handgrip strength of 272 patients, stratified by different CKD stages.
without are presented in Table 3. While serum creatinine levels revealed no difference between low and normal SMI group, Cr/ CysC ratio was significantly lower in low SMI group (p ¼ .022). In addition, patients with low SMI had lower BMI, WC, and body fat mass. When compared to patients with normal HGS, those with low HGS were older, had higher serum creatinine and cystatin C levels, and had lower eGFRcre, eGFEcys, and Cr/CysC ratio (p ¼ .003). Meanwhile, patients with low HGS also suffered from greater prevalent CV diseases. Notably, patients with low SMI and low HGS both presented an overestimated GFR by using serum creatinine, compared with those calculated by cystatin C.
3.4. The correlation between the Cr/CysC, SMI and HGS In Fig. 2, Cr/CysC ratio was both positively correlated with SMI (r ¼ .306, p < .001) and HGS (r ¼ .341, p < .001); while serum Cr was only positively correlated with SMI (r ¼ .203, p ¼ .001) and CysC negatively with HGS (r ¼ .262, p < .001). Multiple stepwise linear regression analysis of variables related to SMI and HGS are listed in Table 4. After adjusting for the confounding factors, age, sex, WC, body fat mass, and Cr/CysC ratio were independently associated with SMI, whereas age, sex, diabetes, hemoglobin, eGFRcys, UPCR, SMI, and Cr/CysC ratio were independently associated with HGS.
Table 3 Clinical characteristics of 272 patients with CKD according to normal or low SMI and normal or low HGS, respectively. Characteristics
SMI
HGS
Normal (n ¼ 244)
Low (n ¼ 28)
p
Normal (n ¼ 164)
Low (n ¼ 108)
p
Age (years) Male (%) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
66.7 ± 14.9 139 (57%) 26.7 (24.0e29.4) 88.1 ± 10.4 28.4 (23.5e35.4) 17.8 ± 2.5 24.2 (17.9e31.8) 11.9 ± 2.0 4.1 (3.8e4.3) 159.0 (137.3e183.8) 87.0 (70.0e111.0) 29.0 (22.0e46.0) 1.7 (1.2e2.6) 39.6 (22.2e54.0) 1.73 (1.29e2.74) 35.5 (18.8e52.4) 1.01 (.84e1.17) 347.8 (115.1e1158.9)
64.9 ± 17.3 16 (57%) 19.5 (16.9e20.5) 69.2 ± 8.6 22.3 (17.6e28.5) 13.8 ± 1.4 20.1 (15.2e29.5) 12.3 ± 2.0 4.1 (3.7e4.4) 159.0 (123.0e183.8) 88.5 (73.5e103.0) 26.5 (19.3e57.5) 1.7 (.9e2.6) 38.9 (23.9e63.4) 1.89 (1.13e2.71) 31.3 (20.2e61.9) .85 (.78e1.06) 347.8 (28.0e995.6)
.563 .986 <.001* <.001* <.001* <.001* .152 .240 .727 .581 .929 .581 .360 .339 .670 .677 .022* .477
62.5 (54.3e70.8) 99 (60.4%) 26.5 ± 4.9 87.0 (79.0e94.0) 27.7 (23.3e35.3) 17.5 ± 2.6 29.6 (23.2e35.5) 12.4 ± 2.0 4.1 (3.9e4.3) 161.5 (139.5e186.8) 88.0 (72.0e117.0) 27.0 (19.0e39.0) 1.5 (1.2e2.5) 45.8 (25.6e58.4) 1.57 (1.22e2.35) 41.5 (23.8e57.7) 1.02 (.86e1.19) 351.3 (74.8e1096.5)
76.0 (66.0e84.8) 56 (51.9%) 25.6 ± 4.7 87.0 (80.0e93.0) 28.4 (21.3e35.2) 17.0 ± 2.7 16.3 (13.7e20.6) 11.1 ± 1.6 4.0 (3.8e4.2) 154.0 (130.5e178.0) 86.5 (66.0e102.5) 35.0 (24.3e51.0) 1.9 (1.4e2.8) 30.6 (21.4e48.8) 2.19 (1.55e3.02) 24.6 (16.7e40.4) .89 (.80e1.10) 347.8 (123.0e1152.7)
<.001* .165 .128 .579 .898 .152 <.001* <.001* .020* .038* .057 .002* .013* <.001* <.001* <.001* .003* .644
108 (44.3%) 200 (82.0%) 149 (61.1%) 39 (16.0%)
9 (32.1%) 18 (64.3%) 18 (64.3%) 2 (7.1%)
.220 .026* .740 .216
65 (39.6%) 131 (79.9%) 105 (64.0%) 19 (11.6%)
52 87 62 22
.165 .891 .273 .048*
(48.1%) (80.6%) (57.4%) (20.4%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). Low muscle mass was defined based on sex-specific lowest 10th percentile of SMI in the study population. Low handgrip strength was defined as handgrip strength <26 kg for men and <18 kg for women. CKD, chronic kidney disease; SMI, skeletal muscle index; HGS, handgrip strength; BMI, body mass index; WC, waist circumference; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 5/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
5
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 Q5 Fig. 2. The correlation between the SMI, handgrip strength, and serum markers. 94 95 96 Table 4 acceptable power in male patients (AUC ¼ .710, 95% Multiple stepwise linear regression analysis of factors associated with SMI and HGS 97 CI ¼ .631e.780), but not in female patients (AUC ¼ .533, 95% among 272 patients with CKD. 98 CI ¼ .438e.626). Moreover, in all patients with CKD, the Cr/CysC 99 Variables В (95% CI) p ratio exhibited a high NPV. For the prediction of low HGS, the 100 discriminative power was .584 (95% CI ¼ .502e.662) in male paSMI 101 tients and .606 (95% CI ¼ .512e.695) in female patients. Age (years) .03 (.04, .02) <.001* 102 Female 1.42 (1.90, .93) <.001* WC (cm) .18 (.16, .20) <.001* 103 Body fat mass (%) .10 (.12, .07) <.001* 104 4. Discussion Cr/CysC .56 (.01, 1.11) .046* 105 HGS 106 Compared to that serum Cr was only positively correlated with Age (years) .23 (.29, .17) <.001* Female 6.75 (8.84, 4.65) <.001* 107 SMI and CysC only negatively with HGS in our 272 patients with Diabetes 1.55 (3.10, .01) .050* 108 various stages of CKD, Cr/CysC ratio was both positively correlated Hemoglobin (g/dL) 1.08 (.59, 1.57) <.001* 109 with SMI and HGS. After the multiple stepwise linear regression eGFRcys (mL/m/1.73m2) .04 (.01, .08) .042* 110 analysis, Cr/CysC ratio remained its significant association with UPCR (mg/mg) .56 (1.05, .08) .023* 111 SMI (kg/m2) .77 (.39, 1.15) <.001* both SMI and HGS. Cr/CysC 6.61 (3.67, 9.55) <.001* 112 The relationship between Cr/CysC ratio and sarcopenia had been 113 explored in various populations. Tetsuka et al. first observed a Adopted factors: age, gender, diabetes, CV disease, WC, body fat mass, albumin, eGFRcys and Cr/CysC for SMI; age, gender, diabetes, CV disease, hemoglobin, albu114 lower Cr/CysC ratio in patients with amyotrophic lateral sclerosis, min, SMI, eGFRcys, UPCR, and Cr/cysC for handgrip strength. 115 compared to healthy controls [15]. In a Japanese old-aged cohort 2 Adjusted R ¼ .784 for SMI and .586 for handgrip strength. 116 who without severe renal impairment, Cr/CysC ratio had been SMI, skeletal muscle index; HGS, handgrip strength; CKD, chronic kidney disease; 117 showed to be positively correlated with both muscle mass and 95% CI, 95% confidence interval; WC, waist circumference; Cr/CysC, serum creati118 nine/cystatin C ratio, eGFRcys, estimated glomerular filtration rate from serum physical function [19]. In patients with type 2 diabetes, decreased cystatin C; UPCR, urine protein/creatinine ratio. 119 Cr/CysC ratio is considered as a surrogate marker of sarcopenia [16]. *p < .05 was considered statistically significant. 120 Recently, Cr/CysC ratio was regarded as a predictor for malnutrition, 121 frailty and poor clinical outcomes in patients treated in ICU 122 [17,20,26]. However, to the best of our knowledge, this association We also analyzed the relationship between Cr/CysC ratio, SMI, 123 between Cr/CysC ratio and muscle wasting in CKD patients has and HGS, which was stratified by the stage of CKD (Fig. 3). Cr/CysC 124 never been reported yet. In our study, which included patients with ratio was positively correlated with HGS at all stages of CKD; 125 a wide range of CKD stages, a positive relationship between Cr/CysC however, it was positively correlated with SMI only in CKD stages 126 ratio and both muscle mass and muscle strength was confirmed. 1e3. Furthermore, this association between Cr/CysC ratio and SMI 127 Along the course of CKD progression, the positive correlation became weaker, as CKD progressed. 128 between Cr/CysC ratio and SMI was significant only in patients with The diagnostic values of Cr/CysC on low SMI and low HGS were 129 CKD stages 1e3. This phenomenon might be partially explained by shown in Table 5. For the prediction of low SMI, Cr/CysC had an 130 the variable status of muscle metabolism and creatine turnover rate Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 6/7
6
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
Fig. 3. The correlation between the Cr/CysC, SMI, and HGS in different CKD stages.
Table 5 Diagnostic value of Cr/CysC on low SMI and low handgrip strength, overall and stratified by gender.
Low SMI Overall Male Female Low handgrip strength Overall Male Female
Q1
AUC (95% CI)
Cut-off
Sen (%)
Spe (%)
PPV (%)
NPV (%)
.632 (.572e.690)* .710 (.631e.780)* .533 (.438e.626)
1.01 .84
81.3 66.7
64.0 58.1
20.6 15.4
96.7 93.8
.608 (.547e.666)* .584 (.502e.662)* .606 (.512e.695)*
.88 .91
37.5 73.1
81.8 49.2
53.8 53.5
69.8 69.6
Cr/CysC, serum creatinine/cystatin C ratio; SMI, skeletal muscle index; AUC, area under the curve; 95% CI, 95% confidence interval; Sen, sensitivity; Spe, specificity; PPV, positive predictive value; NPV, negative predictive value. *p < .05 was considered statistically significant.
in advanced CKD [27] and by inaccurate measurement of muscle mass when applying bioelectrical impedance analyzer that was confounded by edematous status in our advanced CKD patients [9]. However, due to the limited sample size in our advanced CKD patients, especially in CKD stage 5, large-scale studies are warranted to evaluate the association between Cr/CysC ratio and SMI. Nevertheless, the high NPV in both male and female patients indicated that Cr/CysC ratio may be a promising screening test for detecting low muscle mass in CKD patients. Comparing with low muscle mass, low muscle strength was usually observed to be more closely associated with high mortality [28,29]. However, the association between Cr/CysC ratio and muscle strength was rarely evaluated in previous studies. In our study, Cr/CysC ratio was not only found to be correlated with but also an independent predictor for muscle strength. This association remained unchanged after adjusting skeletal muscle mass, which indicates that it may also be regarded as a surrogate marker of muscle function. Notably, in patients with CKD stage 5, we observed that Cr/CysC ratio correlated with muscle strength, but not muscle mass. Since inflammation had been shown to be associated with elevated levels of cystatin C and reduced levels of creatinine [30], the lower Cr/CysC ratio in this stage may implicate a higher degree of inflammation, which is a well-known risk factor for muscle wasting [31] and muscle strength loss [32].
Interestingly, as CKD progressed, we observed a trend of decline in muscle strength significantly, but not in muscle mass. This phenomenon implied that muscle weakness does not only depend on the reduction in muscle mass itself. In our study, several metabolic factors other than SMI were independently associated with lower muscle strength, which included the presence of diabetes, lower hemoglobin and eGFR levels, and higher UPCR. Although sarcopenia was defined as the progressive loss of skeletal muscle mass that was accompanied by the loss of muscle strength [6,23,33], our study highlights a different clinical relevance of SMI and HGS in patients with non-dialysis CKD, which finding was also reported in hemodialysis patients [28,34]. To our knowledge, this is the first study to report the correlation of Cr/CysC ratio with either muscle mass or muscle strength in non-dialysis CKD patients. However, our study has several limitations. First, skeletal muscle mass was measured by a bioelectrical impedance analyzer, which may be affected by the hydration status in patients with CKD [9,35]. Second, the definition of low muscle mass was derived from less than the 10th percentile of skeletal muscle mass within the study population in each gender, rather than from a younger, healthy reference population. Third, the markers for inflammation, such as C-reactive protein and interleukin-6, were not measured in the study. Finally, our subjects were recruited from outpatient clinics and
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
YCLNU4047_proof ■ 6 November 2019 ■ 7/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
these results may not be generalized to CKD patients with severe muscle wasting. In conclusion, our study suggests that Cr/CysC ratio is a promising surrogate marker of muscle wasting and dysfunction. Largescale studies are warranted to establish the clinical utility of Cr/ CysC ratio in the assessment of muscle wasting in patients with CKD. Statement of authorship Conceptualization, Y.-L. L.; methodology, Y.-L. L. and S.-Y. C.; formal analysis, Y.-L. L. and S.-Y. C.; investigation, C.-H. W, Y.-H. L. and C.-H. K.; data curation, C.-H. W, Y.-H. L. and C.-H. K.; writingdoriginal draft preparation, Y.-L. L.; writingdreview and editing, H.-H. L. and B.-G. H.; supervision, H.-H. L. and B.-G. H. All authors reviewed the manuscript. Sources of funding support
Q2
This work was supported by a grant from the Buddhist Tzu Chi General Hospital, Hualien, Taiwan [TCRD105-04]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data availability The datasets analyzed during the current study are available from the corresponding author on reasonable request. Conflict of Interest The authors declare no competing interests. Acknowledgements The authors would like to thank Enago (www.enago.tw) for the English language review. References [1] Webster AC, Nagler EV, Morton RL, Masson P. Chronic kidney disease. The Lancet 2017;389:1238e52. [2] Hill NR, Fatoba ST, Oke JL, Hirst JA, O'Callaghan CA, Lasserson DS, et al. Global prevalence of chronic kidney disease e a systematic review and meta-analysis. PLoS One 2016;11:e0158765. [3] Wang J, Zhang L, Tang SC, Kashihara N, Kim YS, Togtokh A, et al. Disease burden and challenges of chronic kidney disease in North and East Asia. Kidney Int 2018;94:22e5. [4] Tonelli M, Riella M. Chronic kidney disease and the aging population. Braz J Nephrol 2014;36:1e5. [5] Rosenberg IH. Sarcopenia: origins and clinical relevance. J Nutr 1997;127: 990Se1S. [6] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: european consensus on definition and diagnosis: report of the european working group on sarcopenia in older people. Age Ageing 2010;39: 412e23. [7] Wang XH, Mitch WE. Mechanisms of muscle wasting in chronic kidney disease. Nat Rev Nephrol 2014;10:504e16. [8] Pereira RA, Cordeiro AC, Avesani CM, Carrero JJ, Lindholm B, Amparo FC, et al. Sarcopenia in chronic kidney disease on conservative therapy: prevalence and association with mortality. Nephrol Dial Transplant 2015;30:1718e25. [9] Carrero JJ, Johansen KL, Lindholm B, Stenvinkel P, Cuppari L, Avesani CM. Screening for muscle wasting and dysfunction in patients with chronic kidney disease. Kidney Int 2016;90:53e66. [10] Lin T-Y, Peng C-H, Hung S-C, Tarng D-C. Body composition is associated with clinical outcomes in patients with nonedialysis-dependent chronic kidney disease. Kidney Int 2018;93:733e40.
7
^a JOdA, Colugnati FAB, Mansur HN, [11] Souza VAd, Oliveira D, Barbosa SR, Corre et al. Sarcopenia in patients with chronic kidney disease not yet on dialysis: analysis of the prevalence and associated factors. PLoS One 2017;12: e0176230. [12] Patel SS, Molnar MZ, Tayek JA, Ix JH, Noori N, Benner D, et al. Serum creatinine as a marker of muscle mass in chronic kidney disease: results of a crosssectional study and review of literature. Journal of Cachexia, Sarcopenia and Muscle 2013;4:19e29. [13] Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis 2002;40:221e6. [14] Baxmann AC, Ahmed MS, Marques NC, Menon VB, Pereira AB, Kirsztajn GM, et al. Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. Clin J Am Soc Nephrol : CJASN. 2008;3: 348e54. [15] Syuichi T, Mitsuya M, Kunihiko I, Imaharu N. Creatinine/cystatin C ratio as a surrogate marker of residual muscle mass in amyotrophic lateral sclerosis. Neurol Clin Neurosci 2013;1:32e7. [16] Osaka T, Hamaguchi M, Hashimoto Y, Ushigome E, Tanaka M, Yamazaki M, et al. Decreased the creatinine to cystatin C ratio is a surrogate marker of sarcopenia in patients with type 2 diabetes. Diabetes Res Clin Pract 2018;139: 52e8. [17] Kashani KB, Frazee EN, Kukr alov a L, Sarvottam K, Herasevich V, Young PM, et al. Evaluating muscle mass by using markers of kidney function: development of the sarcopenia index. Crit Care Med 2017;45:e23e9. [18] Kianoush K, Kumar S, PN L, BE F, KC C. The sarcopenia index: a novel measure of muscle mass in lung transplant candidates. Clin Transplant 2018;32: e13182. [19] Kusunoki H, Tsuji S, Wada Y, Fukai M, Nagai K, Itoh M, et al. Relationship between sarcopenia and the serum creatinine/cystatin C ratio in Japanese rural community-dwelling older adults. JCSM Clin Rep 2018;3:e00057. [20] Barreto EF, Poyant JO, Coville HH, Dierkhising RA, Kennedy CC, Gajic O, et al. Validation of the sarcopenia index to assess muscle mass in the critically ill: a novel application of kidney function markers. Clin Nutr 2019;38:1362e7. [21] Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014;63:713e35. [22] Wang YW, Lin TY, Peng CH, Huang JL, Hung SC. Factors associated with decreased lean tissue index in patients with chronic kidney disease. Nutrients 2017;9:434. [23] Chen L-K, Liu L-K, Woo J, Assantachai P, Auyeung T-W, Bahyah KS, et al. Sarcopenia in asia: consensus report of the asian working group for sarcopenia. J Am Med Dir Assoc 2014;15:95e101. [24] Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012;367:20e9. [25] Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006;145:247e54. [26] Barreto EF, Kanderi T, DiCecco SR, Lopez-Ruiz A, Poyant JO, Mara KC, et al. Sarcopenia index is a simple objective screening tool for malnutrition in the critically ill. J Parenter Enteral Nutr 2019;43:780e8. [27] Wyss M, Kaddurah-Daouk R. Creatine and creatinine metabolism. Physiol Rev 2000;80:1107e213. ra ny P, Heimbürger O, [28] Isoyama N, Qureshi AR, Avesani CM, Lindholm B, Ba et al. Comparative associations of muscle mass and muscle strength with mortality in dialysis patients. Clin J Am Soc Nephrol : CJASN 2014;9:1720e8. [29] Kittiskulnam P, Chertow GM, Carrero JJ, Delgado C, Kaysen GA, Johansen KL. Clinical Investigation: sarcopenia and its individual criteria are associated, in part, with mortality among patients on hemodialysis. Kidney Int 2017;92: 238e47. [30] Stevens LA, Schmid CH, Greene T, Li L, Beck GJ, Joffe MM, et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int 2009;75:652e60. [31] Mak RH, Ikizler AT, Kovesdy CP, Raj DS, Stenvinkel P, Kalantar-Zadeh K. Wasting in chronic kidney disease. Journal of Cachexia, Sarcopenia and Muscle 2011;2:9e25. [32] Schaap LA, Pluijm SMF, Deeg DJH, Visser M. Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 2006;119:526. e9-.e17. [33] Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, et al. Sarcopenia with limited mobility: an international consensus. J Am Med Dir Assoc 2011;12:403e9. [34] Marcus RL, LaStayo PC, Ikizler TA, Wei G, Giri A, Chen X, et al. Low physical function in maintenance hemodialysis patients is independent of muscle mass and comorbidity. J Ren Nutr 2015;25:371e5. [35] El-Kateb S, Davenport A. Changes in intracellular water following hemodialysis treatment lead to changes in estimates of lean tissue using bioimpedance spectroscopy. Nutr Clin Pract 2016;31:375e7.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128
YCLNU4047_proof ■ 6 November 2019 ■ 1/7
Clinical Nutrition xxx (xxxx) xxx
Contents lists available at ScienceDirect
Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Original article
Q4 Q3
Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with non-dialysis chronic kidney disease Yu-Li Lin a, b, Shu-Yuan Chen b, Yu-Hsien Lai a, Chih-Hsien Wang a, Chiu-Huang Kuo a, Hung-Hsiang Liou c, **, Bang-Gee Hsu a, d, * a
Division of Nephrology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, 97004, Taiwan Department of Public Health, Tzu Chi University, Hualien, 97004, Taiwan Division of Nephrology, Department of Internal Medicine, Hsin-Jen Hospital, New Taipei City, 24243, Taiwan d School of Medicine, Tzu Chi University, Hualien, 97004, Taiwan b c
a r t i c l e i n f o
s u m m a r y
Article history: Received 2 August 2019 Accepted 27 October 2019
Background & aims: Muscle wasting is highly prevalent in patients with chronic kidney disease (CKD). However, the assessment of skeletal muscle mass and strength in clinical settings is not commonly available. We aimed to evaluate the feasibility of serum creatinine/cystatin C (Cr/CysC) ratio in the assessment of muscle wasting. Methods: In 272 patients with CKD aged 66.5 ± 15.1 years, skeletal muscle mass and handgrip strength (HGS) were assessed. Skeletal muscle index (SMI) was calculated as skeletal muscle mass/height2. Low muscle mass was defined as SMI below the sex-specific 10th percentile of study population and low handgrip strength as less than 26 Kg for men and 18 Kg for women. Results: The Cr/CysC ratio was significantly lower in both the low SMI and low HGS groups. Moreover, the Cr/CysC ratio correlated with SMI (r ¼ .306, p < .001) and HGS (r ¼ .341, p < .001). After adjusting for confounding factors, age, sex, waist circumference, body fat mass, and Cr/CysC ratio were independently associated with SMI, whereas age, sex, diabetes, hemoglobin, estimated glomerular filtration rate, urine protein/creatinine ratio, SMI, and Cr/CysC ratio were independently associated with HGS. Conclusions: Cr/CysC ratio appears to be a promising surrogate marker for detecting muscle wasting in patients with CKD. Further studies are needed to extend our findings. © 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Keywords: Cystatin C Creatinine Muscle wasting Sarcopenia Chronic kidney disease
1. Introduction Chronic kidney disease (CKD), with an estimated prevalence of 11%e13% [1,2], is a major public health problem worldwide, especially in the aging population [3,4]. During the aging process, senescence is usually accompanied by a progressive loss of both skeletal muscle mass and function, which is also known as sarcopenia [5,6]. Furthermore, patients with CKD are also vulnerable to additional risks of muscle wasting. These exacerbating factors occur along the course of CKD, which include inflammation, acidosis,
* Corresponding author. Division of Nephrology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97004, Taiwan. ** Corresponding author. E-mail addresses: [email protected] (Y.-L. Lin), [email protected]. tw (S.-Y. Chen), [email protected] (Y.-H. Lai), [email protected] (C.-H. Wang), [email protected] (C.-H. Kuo), [email protected] (H.-H. Liou), [email protected] (B.-G. Hsu).
malnutrition, impaired insulin signaling, decreased sex or growth hormone, angiotensin II overexpression, and uremic toxins accumulation. Muscle wasting may not only result in frailty, falls, fractures, and poor quality of life but also enhance the risk of infection and even premature death [7e11]. Thus, early detection of muscle wasting is of paramount importance in CKD patients. Although magnetic resonance imaging, computed tomography, dual-energy x-ray absorptiometry, and bioimpedance analysis are usually recommended for assessing skeletal muscle mass, these measurements are not commonly applicable [9]. In clinical practice, reliable surrogate serum markers for prediction of muscle wasting in nondialysis CKD patients are unavailable currently. Serum creatinine, a 113-Da product of creatine phosphate from skeletal muscle, is a well-established predictor of renal function status and muscle mass in patients undergoing dialysis [12]. Another predictor, serum cystatin C, a 13-kD cysteine proteinase inhibitor expressed in all nucleated cells, is less affected by the volume of skeletal muscle mass and is recognized as a more reliable
https://doi.org/10.1016/j.clnu.2019.10.027 0261-5614/© 2019 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 2/7
2
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
marker for renal function [13,14]. Loss of skeletal muscle mass during the wasting process is only accompanied by a decline in the serum creatinine level, but not in cystatin C. These observations indicate that serum creatinine/cystatin C (Cr/CysC) ratio, instead of either serum creatinine or cystatin C level, should be a more appropriate surrogate marker for detecting muscle wasting in patients with CKD. In fact, positive correlation between Cr/CysC ratio and skeletal muscle mass had emerged in study populations who were admitted to the intensive care unit (ICU), underwent a lung transplant, with amyotrophic lateral sclerosis or diabetes, and in the geriatric population without severe renal impairment [15e20]. In patients treated in ICU, Cr/CysC ratio was also regarded as a predictor for poor outcome [17,20]. However, the correlation between Cr/CysC ratio and skeletal muscle mass and muscle strength in patients with non-dialysis CKD remained unknown. Therefore, we aimed to explore and to compare the relationship of Cr/CysC ratio with both skeletal muscle mass and muscle strength in patients with various stages of CKD.
anthropometric measurements of body composition and HGS were performed by the same well-experienced operator. Fasting blood and urine samples were obtained from all participants. After centrifugation, serum samples were used for biochemical analysis within 1 h of collection. Blood urea nitrogen (BUN), serum creatinine, albumin, total cholesterol (TCH), lowdensity lipoprotein (LDL) levels, and urine protein/creatinine ratio (UPCR) were measured using an autoanalyzer (Siemens Advia 1800, Siemens Healthcare GmbH, Henkestr, Germany). Serum cystatin C levels were measured with a nephelometric Siemens immunoassay. We calculated the estimated glomerular filtration rate (eGFR) from both serum creatinine (eGFRcre) and cystatin C (eGFRcys), according to the Modification of Diet in Renal Disease and CKD-EPI Cystatin C equation, respectively [24,25]. Cr/CysC ratio is calculated as serum creatinine (mg/dL) divided by serum cystatin C (mg/L). The stages of CKD were defined based on the eGFRcys.
2. Materials and methods
To detect a correlation coefficient of about .3 between Cr/CysC ratio, SMI and HGS according to previous studies [19,20], with an alpha level of .05 and a power of 90%, a total of at least 112 patients should be enrolled in the study. Continuous variables were expressed either as the mean ± standard deviation or as the median and interquartile range, according to the data distribution from the KolmogoroveSmirnov test. These variables between the two groups were compared either by applying the Student's independent t-test or by the ManneWhitney U test. Categorical variables were expressed as absolute (n) and relative frequency (%) and analyzed by the chi-square test or Fisher's exact test. The linear trend of variables in different CKD stages was tested using a oneway analysis of variance (ANOVA) or the CochraneArmitage test for trend. Univariable correlations between variables were assessed by Spearman's correlation coefficient. Independent factors associated with SMI and HGS were analyzed by multiple stepwise linear regression. Finally, receiver operating characteristic curves were constructed to assess the diagnostic value of serum Cr/CysC ratio on low muscle mass and low muscle strength. The areas under curves, cut-offs, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were established. Statistical analysis was performed using SPSS software (version 19.0; SPSS Inc., Chicago, IL, USA). A P-value of less than .05 was considered statistically significant.
2.1. Setting and participants A single-center, cross-sectional study was conducted in outpatient clinics at a medical center in Hualien between April 2015 and February 2016. Patients with non-dialysis CKD and older than 20 years of age were recruited; while, patients who had malignancy, acute infection, gastrointestinal bleeding, amputated limbs, and were wheelchair-bound or bed-ridden were excluded. CKD was defined as a decrease of renal function or the presence of kidney damage for more than 3 months, according to the Kidney Disease Outcomes Quality Initiative guidelines [21]. Diabetes mellitus (DM) was defined based on history or anti-diabetic drug use, hypertension on history or with anti-hypertensive treatment, and hyperlipidemia on history or receiving lipid-lowering medication. The definition of cardiovascular (CV) disease included coronary artery disease, myocardial infarction, or congestive heart failure. All participants signed an informed consent approved by the Institutional Review Board of Tzu-Chi Hospital and all methods were performed in accordance with the relevant guidelines and regulations. 2.2. Measures Height and body weight were measured to the nearest halfcentimeter and half-kilogram in patients with light clothes and without shoes. Body mass index (BMI) was calculated as body weight (Kg) divided by height squared (m2). Waist circumference (WC) was measured at the shortest point between the lower rib margin and the iliac crest. Body skeletal and fat mass were assessed using a portable whole body bioelectrical impedance device (Tanita BC 706DB, Tanita Corporation, Tokyo, Japan). This measurement is noninvasive and highly reproducible. The skeletal muscle index (SMI) was calculated as skeletal muscle mass/height2 (Kg/m2). Patients were classified into low and normal skeletal muscle mass groups based on the sex-specific lowest 10th percentile of SMI within the study population [8,22]. Muscle strength was assessed by measuring handgrip strength (HGS) using a Jamar Plus Digital Hand Dynamometer (SI Instruments Pty Ltd, Hilton, Australia) with a precision of one kilogram (Kg) [9]. Patients were instructed to apply as much handgrip pressure as possible. This measurement was repeated three times with a rest period of 1 min for each hand, and the highest value was recorded for analysis. Low muscle strength was defined as an HGS less than 26 kg for men and 18 kg for women, according to the Asian Working Group for Sarcopenia (AWGS) criteria [23]. All
2.3. Data analysis
3. Results 3.1. Demographic and clinical characteristics of patients A total of 272 CKD patients, with a mean age of 66.5 ± 15.1 years, were included in this study. Demographic data and clinical characteristics of all participants are presented in Table 1. Among them, 155 (57.0%) were males, 117 (43%) patients had DM, 218 (80.1%) had hypertension, 167 (61.4%) had hyperlipidemia, and 41 (15.1%) had CV disease. Our female patients were younger, had lower WC, SMI, HGS, hemoglobin, and had higher body fat mass and serum TCH levels when compared with those in male patients. In addition, Cr/CysC ratio was significantly lower in our female patients. 3.2. Clinical characteristics of patients, stratified by different CKD stages All the data stratified by CKD stage are exhibited in Table 2. The distribution of CKD stages was 15.8% for stage 1 and 2, 39.7% for
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 3/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
3
Table 1 Demographic and clinical characteristics of 272 patients with CKD. Characteristics
All Patients (n ¼ 272)
Male (n ¼ 155)
Female (n ¼ 117)
p
Age (years) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
66.5 ± 15.1 26.1 ± 4.8 87.0 (80.0e94.0) 28.9 ± 9.1 17.3 ± 2.7 23.8 (17.5e31.5) 11.9 ± 2.0 4.1 (3.8e4.3) 159.0 (136.0e183.8) 87.0 (70.0e110.0) 29.0 (21.3e46.0) 1.7 (1.2e2.6) 36.5 (21.1e53.8) 1.74 (1.28e2.74) 35.1 (18.9e52.6) 1.00 (.83e1.15) 347.8 (99.6e1109.8)
68.5 ± 14.2 26.3 ± 4.2 89.0 (82.0e96.0) 24.2 ± 6.0 18.8 ± 2.3 29.4 (23.1e35.6) 12.3 ± 2.1 4.1 (3.9e4.2) 157.0 (135.0e177.0) 87.0 (70.0e107.0) 29.0 (20.0e46.0) 1.7 (1.3e2.7) 38.3 (22.2e54.8) 1.72 (1.30e2.68) 36.4 (20.2e54.5) 1.05 (.89e1.19) 304.8 (74.2e1050.1)
63.9 ± 15.8 25.9 ± 5.6 83.0 (76.0e93.0) 35.1 ± 8.7 15.5 ± 1.7 18.8 (14.9e22.6) 11.3 ± 1.6 4.1 (3.8e4.4) 166.0 (142.0e192.0) 87.0 (69.5e114.0) 29.0 (23.0e46.0) 1.6 (1.1e2.4) 33.4 (20.4e53.4) 1.81 (1.28e2.84) 32.2 (17.4e52.4) .87 (.78e1.07) 398.9 (156.9e1206.3)
.013* .536 <.001* <.001* <.001* <.001* <.001* .583 .031* .575 .623 .024* .199 .969 .466 <.001* .154
117 (43%) 218 (80.1%) 167 (61.4%) 41 (15.1%)
69 (44.5%) 127 (81.9%) 89 (57.4%) 26 (16.8%)
48 91 78 15
.565 .395 .121 .367
(41.0%) (77.8%) (66.7%) (12.8%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). CKD, chronic kidney disease; BMI, body mass index; WC, waist circumference; SMI, skeletal muscle index; HGS, handgrip strength; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant between male and female patients.
Table 2 Clinical characteristics of 272 patients, stratified by CKD stages. Characteristics
CKD stage 1e2 (n ¼ 43)
CKD stage 3 (n ¼ 108)
CKD stage 4 (n ¼ 75)
CKD stage 5 (n ¼ 46)
p for Trend
Age (years) Male (%) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
53.2 ± 16.1 25 (58.1%) 24.7 ± 4.3 80.9 ± 11.9 27.7 ± 8.5 16.7 ± 2.3 30.6 ± 10.5 13.2 ± 1.8 4.1 (4.0e4.4) 177.0 (148.0e201.0) 100.0 (82.0e122.0) 19.0 (16.0e24.0) 1.0 (.8e1.2) 73.9 (60.7e104.5) 1.05 (.87e1.12) 74.3 (63.0e90.9) 1.05 (.82e1.15) 258.4 (26.3e572.2)
67.9 ± 13.1 63 (58.3%) 27.2 ± 5.0 88.0 ± 11.7 30.5 ± 9.6 17.6 ± 2.5 26.4 ± 9.5 12.6 ± 1.6 4.1 (4.0e4.4) 161.0 (138.3e189.0) 88.0 (70.5e118.5) 24.0 (20.0e29.0) 1.4 (1.1e1.7) 49.8 (41.0e55.7) 1.46 (1.29e1.67) 44.1 (37.2e52.4) .95 (.83e1.10) 192.3 (66.6e569.0)
71.5 ± 12.3 42 (56.0%) 25.5 ± 4.8 86.3 ± 11.2 28.7 ± 8.5 17.1 ± 2.7 21.6 ± 7.6 11.4 ± 1.7 4.1 (4.0e4.3) 154.0 (130.0e174.0) 80.0 (66.0e99.0) 38.0 (30.0e48.0) 2.3 (1.9e2.7) 26.1 (21.9e33.0) 2.42 (2.17e2.81) 21.9 (18.2e25.6) .88 (.80e1.08) 409.2 (225.9e1112.7)
67.4 ± 16.0 25 (54.3%) 26.0 ± 4.6 86.7 ± 11.2 26.6 ± 9.0 17.9 ± 3.2 22.6 ± 9.8 9.8 ± 1.4 3.9 (3.7e4.1) 159.0 (133.8e184.2) 86.0 (63.8e104.8) 64.0 (54.0e90.0) 4.6 (3.7e6.4) 12.3 (8.1e16.6) 4.02 (3.55e4.54) 11.6 (10.0e13.4) 1.15 (.94e1.46) 1244.1 (564.9e2245.3)
<.001* .638 .449 .040* .388 .059 <.001* <.001* .014* .003* .003* <.001* <.001* <.001* <.001* <.001* <.001* <.001*
11 (25.6%) 33 (76.7%) 28 (65.1%) 3 (7.0%)
50 86 67 14
41 62 48 19
15 (32.6%) 37 (80.4%) 24 (52.2%) 5 (10.9%)
.391 .563 .287 .193
(46.3%) (79.6%) (62.0%) (13.0%)
(54.7%) (82.7%) (64.0%) (25.3%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). Staging of CKD is based on eGFRcysC. CKD, chronic kidney disease; BMI, body mass index; WC, waist circumference; SMI, skeletal muscle index; HGS, handgrip strength; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant.
stage 3, 27.6% for stage 4, and 16.9% for stage 5. Patients with advanced stages of CKD tended to be older, had lower eGFRcre and eGFRcys levels, higher serum Cr and cystatin C levels, and higher Cr/CysC ratio. Notably, HGS, but not SMI, significantly showed a trend of decline in patients with advanced-stage CKD (Table 2 and Fig. 1).
3.3. Clinical characteristics of patients according to normal or low SMI and normal or low HGS, respectively Among the 272 patients with CKD, 28 (10.3%) had low SMI, and 108 (39.7%) had low HGS. The comparison of the characteristics between patients with low SMI or low HGS and those
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 4/7
4
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
Fig. 1. Skeletal muscle index and handgrip strength of 272 patients, stratified by different CKD stages.
without are presented in Table 3. While serum creatinine levels revealed no difference between low and normal SMI group, Cr/ CysC ratio was significantly lower in low SMI group (p ¼ .022). In addition, patients with low SMI had lower BMI, WC, and body fat mass. When compared to patients with normal HGS, those with low HGS were older, had higher serum creatinine and cystatin C levels, and had lower eGFRcre, eGFEcys, and Cr/CysC ratio (p ¼ .003). Meanwhile, patients with low HGS also suffered from greater prevalent CV diseases. Notably, patients with low SMI and low HGS both presented an overestimated GFR by using serum creatinine, compared with those calculated by cystatin C.
3.4. The correlation between the Cr/CysC, SMI and HGS In Fig. 2, Cr/CysC ratio was both positively correlated with SMI (r ¼ .306, p < .001) and HGS (r ¼ .341, p < .001); while serum Cr was only positively correlated with SMI (r ¼ .203, p ¼ .001) and CysC negatively with HGS (r ¼ .262, p < .001). Multiple stepwise linear regression analysis of variables related to SMI and HGS are listed in Table 4. After adjusting for the confounding factors, age, sex, WC, body fat mass, and Cr/CysC ratio were independently associated with SMI, whereas age, sex, diabetes, hemoglobin, eGFRcys, UPCR, SMI, and Cr/CysC ratio were independently associated with HGS.
Table 3 Clinical characteristics of 272 patients with CKD according to normal or low SMI and normal or low HGS, respectively. Characteristics
SMI
HGS
Normal (n ¼ 244)
Low (n ¼ 28)
p
Normal (n ¼ 164)
Low (n ¼ 108)
p
Age (years) Male (%) BMI (kg/m2) WC (cm) Body fat mass (%) SMI (kg/m2) HGS (kg) Hemoglobin (g/dL) Albumin (g/dL) TCH (mg/dL) LDL (mg/dL) BUN (mg/dL) Creatinine (mg/dL) eGFRcre (mL/m/1.73m2) Cystatin C (mg/L) eGFRcys (mL/m/1.73m2) Cr/CysC UPCR (mg/g) Diseases Diabetes (%) Hypertension (%) Hyperlipidemia (%) CV disease (%)
66.7 ± 14.9 139 (57%) 26.7 (24.0e29.4) 88.1 ± 10.4 28.4 (23.5e35.4) 17.8 ± 2.5 24.2 (17.9e31.8) 11.9 ± 2.0 4.1 (3.8e4.3) 159.0 (137.3e183.8) 87.0 (70.0e111.0) 29.0 (22.0e46.0) 1.7 (1.2e2.6) 39.6 (22.2e54.0) 1.73 (1.29e2.74) 35.5 (18.8e52.4) 1.01 (.84e1.17) 347.8 (115.1e1158.9)
64.9 ± 17.3 16 (57%) 19.5 (16.9e20.5) 69.2 ± 8.6 22.3 (17.6e28.5) 13.8 ± 1.4 20.1 (15.2e29.5) 12.3 ± 2.0 4.1 (3.7e4.4) 159.0 (123.0e183.8) 88.5 (73.5e103.0) 26.5 (19.3e57.5) 1.7 (.9e2.6) 38.9 (23.9e63.4) 1.89 (1.13e2.71) 31.3 (20.2e61.9) .85 (.78e1.06) 347.8 (28.0e995.6)
.563 .986 <.001* <.001* <.001* <.001* .152 .240 .727 .581 .929 .581 .360 .339 .670 .677 .022* .477
62.5 (54.3e70.8) 99 (60.4%) 26.5 ± 4.9 87.0 (79.0e94.0) 27.7 (23.3e35.3) 17.5 ± 2.6 29.6 (23.2e35.5) 12.4 ± 2.0 4.1 (3.9e4.3) 161.5 (139.5e186.8) 88.0 (72.0e117.0) 27.0 (19.0e39.0) 1.5 (1.2e2.5) 45.8 (25.6e58.4) 1.57 (1.22e2.35) 41.5 (23.8e57.7) 1.02 (.86e1.19) 351.3 (74.8e1096.5)
76.0 (66.0e84.8) 56 (51.9%) 25.6 ± 4.7 87.0 (80.0e93.0) 28.4 (21.3e35.2) 17.0 ± 2.7 16.3 (13.7e20.6) 11.1 ± 1.6 4.0 (3.8e4.2) 154.0 (130.5e178.0) 86.5 (66.0e102.5) 35.0 (24.3e51.0) 1.9 (1.4e2.8) 30.6 (21.4e48.8) 2.19 (1.55e3.02) 24.6 (16.7e40.4) .89 (.80e1.10) 347.8 (123.0e1152.7)
<.001* .165 .128 .579 .898 .152 <.001* <.001* .020* .038* .057 .002* .013* <.001* <.001* <.001* .003* .644
108 (44.3%) 200 (82.0%) 149 (61.1%) 39 (16.0%)
9 (32.1%) 18 (64.3%) 18 (64.3%) 2 (7.1%)
.220 .026* .740 .216
65 (39.6%) 131 (79.9%) 105 (64.0%) 19 (11.6%)
52 87 62 22
.165 .891 .273 .048*
(48.1%) (80.6%) (57.4%) (20.4%)
Values for continuous variables are given as means ± standard deviations or medians and interquartile ranges. Categorical variables are expressed as numbers (%). Low muscle mass was defined based on sex-specific lowest 10th percentile of SMI in the study population. Low handgrip strength was defined as handgrip strength <26 kg for men and <18 kg for women. CKD, chronic kidney disease; SMI, skeletal muscle index; HGS, handgrip strength; BMI, body mass index; WC, waist circumference; TCH, total cholesterol; LDL, low-density lipoprotein; BUN, blood urea nitrogen; eGFRcre, estimated glomerular filtration rate from serum creatinine; eGFRcys, estimated glomerular filtration rate from serum cystatin C; Cr/CysC, serum creatinine/cystatin C ratio; UPCR, urine protein/creatinine ratio; CV disease, cardiovascular disease. *p < .05 was considered statistically significant.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 5/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
5
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 Q5 Fig. 2. The correlation between the SMI, handgrip strength, and serum markers. 94 95 96 Table 4 acceptable power in male patients (AUC ¼ .710, 95% Multiple stepwise linear regression analysis of factors associated with SMI and HGS 97 CI ¼ .631e.780), but not in female patients (AUC ¼ .533, 95% among 272 patients with CKD. 98 CI ¼ .438e.626). Moreover, in all patients with CKD, the Cr/CysC 99 Variables В (95% CI) p ratio exhibited a high NPV. For the prediction of low HGS, the 100 discriminative power was .584 (95% CI ¼ .502e.662) in male paSMI 101 tients and .606 (95% CI ¼ .512e.695) in female patients. Age (years) .03 (.04, .02) <.001* 102 Female 1.42 (1.90, .93) <.001* WC (cm) .18 (.16, .20) <.001* 103 Body fat mass (%) .10 (.12, .07) <.001* 104 4. Discussion Cr/CysC .56 (.01, 1.11) .046* 105 HGS 106 Compared to that serum Cr was only positively correlated with Age (years) .23 (.29, .17) <.001* Female 6.75 (8.84, 4.65) <.001* 107 SMI and CysC only negatively with HGS in our 272 patients with Diabetes 1.55 (3.10, .01) .050* 108 various stages of CKD, Cr/CysC ratio was both positively correlated Hemoglobin (g/dL) 1.08 (.59, 1.57) <.001* 109 with SMI and HGS. After the multiple stepwise linear regression eGFRcys (mL/m/1.73m2) .04 (.01, .08) .042* 110 analysis, Cr/CysC ratio remained its significant association with UPCR (mg/mg) .56 (1.05, .08) .023* 111 SMI (kg/m2) .77 (.39, 1.15) <.001* both SMI and HGS. Cr/CysC 6.61 (3.67, 9.55) <.001* 112 The relationship between Cr/CysC ratio and sarcopenia had been 113 explored in various populations. Tetsuka et al. first observed a Adopted factors: age, gender, diabetes, CV disease, WC, body fat mass, albumin, eGFRcys and Cr/CysC for SMI; age, gender, diabetes, CV disease, hemoglobin, albu114 lower Cr/CysC ratio in patients with amyotrophic lateral sclerosis, min, SMI, eGFRcys, UPCR, and Cr/cysC for handgrip strength. 115 compared to healthy controls [15]. In a Japanese old-aged cohort 2 Adjusted R ¼ .784 for SMI and .586 for handgrip strength. 116 who without severe renal impairment, Cr/CysC ratio had been SMI, skeletal muscle index; HGS, handgrip strength; CKD, chronic kidney disease; 117 showed to be positively correlated with both muscle mass and 95% CI, 95% confidence interval; WC, waist circumference; Cr/CysC, serum creati118 nine/cystatin C ratio, eGFRcys, estimated glomerular filtration rate from serum physical function [19]. In patients with type 2 diabetes, decreased cystatin C; UPCR, urine protein/creatinine ratio. 119 Cr/CysC ratio is considered as a surrogate marker of sarcopenia [16]. *p < .05 was considered statistically significant. 120 Recently, Cr/CysC ratio was regarded as a predictor for malnutrition, 121 frailty and poor clinical outcomes in patients treated in ICU 122 [17,20,26]. However, to the best of our knowledge, this association We also analyzed the relationship between Cr/CysC ratio, SMI, 123 between Cr/CysC ratio and muscle wasting in CKD patients has and HGS, which was stratified by the stage of CKD (Fig. 3). Cr/CysC 124 never been reported yet. In our study, which included patients with ratio was positively correlated with HGS at all stages of CKD; 125 a wide range of CKD stages, a positive relationship between Cr/CysC however, it was positively correlated with SMI only in CKD stages 126 ratio and both muscle mass and muscle strength was confirmed. 1e3. Furthermore, this association between Cr/CysC ratio and SMI 127 Along the course of CKD progression, the positive correlation became weaker, as CKD progressed. 128 between Cr/CysC ratio and SMI was significant only in patients with The diagnostic values of Cr/CysC on low SMI and low HGS were 129 CKD stages 1e3. This phenomenon might be partially explained by shown in Table 5. For the prediction of low SMI, Cr/CysC had an 130 the variable status of muscle metabolism and creatine turnover rate Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
YCLNU4047_proof ■ 6 November 2019 ■ 6/7
6
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
Fig. 3. The correlation between the Cr/CysC, SMI, and HGS in different CKD stages.
Table 5 Diagnostic value of Cr/CysC on low SMI and low handgrip strength, overall and stratified by gender.
Low SMI Overall Male Female Low handgrip strength Overall Male Female
Q1
AUC (95% CI)
Cut-off
Sen (%)
Spe (%)
PPV (%)
NPV (%)
.632 (.572e.690)* .710 (.631e.780)* .533 (.438e.626)
1.01 .84
81.3 66.7
64.0 58.1
20.6 15.4
96.7 93.8
.608 (.547e.666)* .584 (.502e.662)* .606 (.512e.695)*
.88 .91
37.5 73.1
81.8 49.2
53.8 53.5
69.8 69.6
Cr/CysC, serum creatinine/cystatin C ratio; SMI, skeletal muscle index; AUC, area under the curve; 95% CI, 95% confidence interval; Sen, sensitivity; Spe, specificity; PPV, positive predictive value; NPV, negative predictive value. *p < .05 was considered statistically significant.
in advanced CKD [27] and by inaccurate measurement of muscle mass when applying bioelectrical impedance analyzer that was confounded by edematous status in our advanced CKD patients [9]. However, due to the limited sample size in our advanced CKD patients, especially in CKD stage 5, large-scale studies are warranted to evaluate the association between Cr/CysC ratio and SMI. Nevertheless, the high NPV in both male and female patients indicated that Cr/CysC ratio may be a promising screening test for detecting low muscle mass in CKD patients. Comparing with low muscle mass, low muscle strength was usually observed to be more closely associated with high mortality [28,29]. However, the association between Cr/CysC ratio and muscle strength was rarely evaluated in previous studies. In our study, Cr/CysC ratio was not only found to be correlated with but also an independent predictor for muscle strength. This association remained unchanged after adjusting skeletal muscle mass, which indicates that it may also be regarded as a surrogate marker of muscle function. Notably, in patients with CKD stage 5, we observed that Cr/CysC ratio correlated with muscle strength, but not muscle mass. Since inflammation had been shown to be associated with elevated levels of cystatin C and reduced levels of creatinine [30], the lower Cr/CysC ratio in this stage may implicate a higher degree of inflammation, which is a well-known risk factor for muscle wasting [31] and muscle strength loss [32].
Interestingly, as CKD progressed, we observed a trend of decline in muscle strength significantly, but not in muscle mass. This phenomenon implied that muscle weakness does not only depend on the reduction in muscle mass itself. In our study, several metabolic factors other than SMI were independently associated with lower muscle strength, which included the presence of diabetes, lower hemoglobin and eGFR levels, and higher UPCR. Although sarcopenia was defined as the progressive loss of skeletal muscle mass that was accompanied by the loss of muscle strength [6,23,33], our study highlights a different clinical relevance of SMI and HGS in patients with non-dialysis CKD, which finding was also reported in hemodialysis patients [28,34]. To our knowledge, this is the first study to report the correlation of Cr/CysC ratio with either muscle mass or muscle strength in non-dialysis CKD patients. However, our study has several limitations. First, skeletal muscle mass was measured by a bioelectrical impedance analyzer, which may be affected by the hydration status in patients with CKD [9,35]. Second, the definition of low muscle mass was derived from less than the 10th percentile of skeletal muscle mass within the study population in each gender, rather than from a younger, healthy reference population. Third, the markers for inflammation, such as C-reactive protein and interleukin-6, were not measured in the study. Finally, our subjects were recruited from outpatient clinics and
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
YCLNU4047_proof ■ 6 November 2019 ■ 7/7
Y.-L. Lin et al. / Clinical Nutrition xxx (xxxx) xxx
these results may not be generalized to CKD patients with severe muscle wasting. In conclusion, our study suggests that Cr/CysC ratio is a promising surrogate marker of muscle wasting and dysfunction. Largescale studies are warranted to establish the clinical utility of Cr/ CysC ratio in the assessment of muscle wasting in patients with CKD. Statement of authorship Conceptualization, Y.-L. L.; methodology, Y.-L. L. and S.-Y. C.; formal analysis, Y.-L. L. and S.-Y. C.; investigation, C.-H. W, Y.-H. L. and C.-H. K.; data curation, C.-H. W, Y.-H. L. and C.-H. K.; writingdoriginal draft preparation, Y.-L. L.; writingdreview and editing, H.-H. L. and B.-G. H.; supervision, H.-H. L. and B.-G. H. All authors reviewed the manuscript. Sources of funding support
Q2
This work was supported by a grant from the Buddhist Tzu Chi General Hospital, Hualien, Taiwan [TCRD105-04]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data availability The datasets analyzed during the current study are available from the corresponding author on reasonable request. Conflict of Interest The authors declare no competing interests. Acknowledgements The authors would like to thank Enago (www.enago.tw) for the English language review. References [1] Webster AC, Nagler EV, Morton RL, Masson P. Chronic kidney disease. The Lancet 2017;389:1238e52. [2] Hill NR, Fatoba ST, Oke JL, Hirst JA, O'Callaghan CA, Lasserson DS, et al. Global prevalence of chronic kidney disease e a systematic review and meta-analysis. PLoS One 2016;11:e0158765. [3] Wang J, Zhang L, Tang SC, Kashihara N, Kim YS, Togtokh A, et al. Disease burden and challenges of chronic kidney disease in North and East Asia. Kidney Int 2018;94:22e5. [4] Tonelli M, Riella M. Chronic kidney disease and the aging population. Braz J Nephrol 2014;36:1e5. [5] Rosenberg IH. Sarcopenia: origins and clinical relevance. J Nutr 1997;127: 990Se1S. [6] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: european consensus on definition and diagnosis: report of the european working group on sarcopenia in older people. Age Ageing 2010;39: 412e23. [7] Wang XH, Mitch WE. Mechanisms of muscle wasting in chronic kidney disease. Nat Rev Nephrol 2014;10:504e16. [8] Pereira RA, Cordeiro AC, Avesani CM, Carrero JJ, Lindholm B, Amparo FC, et al. Sarcopenia in chronic kidney disease on conservative therapy: prevalence and association with mortality. Nephrol Dial Transplant 2015;30:1718e25. [9] Carrero JJ, Johansen KL, Lindholm B, Stenvinkel P, Cuppari L, Avesani CM. Screening for muscle wasting and dysfunction in patients with chronic kidney disease. Kidney Int 2016;90:53e66. [10] Lin T-Y, Peng C-H, Hung S-C, Tarng D-C. Body composition is associated with clinical outcomes in patients with nonedialysis-dependent chronic kidney disease. Kidney Int 2018;93:733e40.
7
^a JOdA, Colugnati FAB, Mansur HN, [11] Souza VAd, Oliveira D, Barbosa SR, Corre et al. Sarcopenia in patients with chronic kidney disease not yet on dialysis: analysis of the prevalence and associated factors. PLoS One 2017;12: e0176230. [12] Patel SS, Molnar MZ, Tayek JA, Ix JH, Noori N, Benner D, et al. Serum creatinine as a marker of muscle mass in chronic kidney disease: results of a crosssectional study and review of literature. Journal of Cachexia, Sarcopenia and Muscle 2013;4:19e29. [13] Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis 2002;40:221e6. [14] Baxmann AC, Ahmed MS, Marques NC, Menon VB, Pereira AB, Kirsztajn GM, et al. Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. Clin J Am Soc Nephrol : CJASN. 2008;3: 348e54. [15] Syuichi T, Mitsuya M, Kunihiko I, Imaharu N. Creatinine/cystatin C ratio as a surrogate marker of residual muscle mass in amyotrophic lateral sclerosis. Neurol Clin Neurosci 2013;1:32e7. [16] Osaka T, Hamaguchi M, Hashimoto Y, Ushigome E, Tanaka M, Yamazaki M, et al. Decreased the creatinine to cystatin C ratio is a surrogate marker of sarcopenia in patients with type 2 diabetes. Diabetes Res Clin Pract 2018;139: 52e8. [17] Kashani KB, Frazee EN, Kukr alov a L, Sarvottam K, Herasevich V, Young PM, et al. Evaluating muscle mass by using markers of kidney function: development of the sarcopenia index. Crit Care Med 2017;45:e23e9. [18] Kianoush K, Kumar S, PN L, BE F, KC C. The sarcopenia index: a novel measure of muscle mass in lung transplant candidates. Clin Transplant 2018;32: e13182. [19] Kusunoki H, Tsuji S, Wada Y, Fukai M, Nagai K, Itoh M, et al. Relationship between sarcopenia and the serum creatinine/cystatin C ratio in Japanese rural community-dwelling older adults. JCSM Clin Rep 2018;3:e00057. [20] Barreto EF, Poyant JO, Coville HH, Dierkhising RA, Kennedy CC, Gajic O, et al. Validation of the sarcopenia index to assess muscle mass in the critically ill: a novel application of kidney function markers. Clin Nutr 2019;38:1362e7. [21] Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014;63:713e35. [22] Wang YW, Lin TY, Peng CH, Huang JL, Hung SC. Factors associated with decreased lean tissue index in patients with chronic kidney disease. Nutrients 2017;9:434. [23] Chen L-K, Liu L-K, Woo J, Assantachai P, Auyeung T-W, Bahyah KS, et al. Sarcopenia in asia: consensus report of the asian working group for sarcopenia. J Am Med Dir Assoc 2014;15:95e101. [24] Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012;367:20e9. [25] Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006;145:247e54. [26] Barreto EF, Kanderi T, DiCecco SR, Lopez-Ruiz A, Poyant JO, Mara KC, et al. Sarcopenia index is a simple objective screening tool for malnutrition in the critically ill. J Parenter Enteral Nutr 2019;43:780e8. [27] Wyss M, Kaddurah-Daouk R. Creatine and creatinine metabolism. Physiol Rev 2000;80:1107e213. ra ny P, Heimbürger O, [28] Isoyama N, Qureshi AR, Avesani CM, Lindholm B, Ba et al. Comparative associations of muscle mass and muscle strength with mortality in dialysis patients. Clin J Am Soc Nephrol : CJASN 2014;9:1720e8. [29] Kittiskulnam P, Chertow GM, Carrero JJ, Delgado C, Kaysen GA, Johansen KL. Clinical Investigation: sarcopenia and its individual criteria are associated, in part, with mortality among patients on hemodialysis. Kidney Int 2017;92: 238e47. [30] Stevens LA, Schmid CH, Greene T, Li L, Beck GJ, Joffe MM, et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int 2009;75:652e60. [31] Mak RH, Ikizler AT, Kovesdy CP, Raj DS, Stenvinkel P, Kalantar-Zadeh K. Wasting in chronic kidney disease. Journal of Cachexia, Sarcopenia and Muscle 2011;2:9e25. [32] Schaap LA, Pluijm SMF, Deeg DJH, Visser M. Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 2006;119:526. e9-.e17. [33] Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, et al. Sarcopenia with limited mobility: an international consensus. J Am Med Dir Assoc 2011;12:403e9. [34] Marcus RL, LaStayo PC, Ikizler TA, Wei G, Giri A, Chen X, et al. Low physical function in maintenance hemodialysis patients is independent of muscle mass and comorbidity. J Ren Nutr 2015;25:371e5. [35] El-Kateb S, Davenport A. Changes in intracellular water following hemodialysis treatment lead to changes in estimates of lean tissue using bioimpedance spectroscopy. Nutr Clin Pract 2016;31:375e7.
Please cite this article as: Lin Y-L et al., Serum creatinine to cystatin C ratio predicts skeletal muscle mass and strength in patients with nondialysis chronic kidney disease, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.10.027
65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128