- Email: [email protected]
Estimating 24-Hour Urinary Sodium Excretion From Spot Urine Samples in Chronic Kidney Disease Patients
ORIGINAL RESEARCH
Estimating 24-Hour Urinary Sodium Excretion From Spot Urine Samples in Chronic Kidney Disease Patients Jiachang Hu, PhD,*,†,‡,§,{ Yimei Wang, PhD,*,†,‡,§,{ Nana Song, PhD,*,†,‡,§,{ Xiaoyan Zhang, PhD,*,†,‡,§,{ Jie Teng, PhD,*,†,‡,§,{ Jianzhou Zou, PhD,*,†,‡,§,{ and Xiaoqiang Ding, PhD*,†,‡,§,{ Objective: Spot urine sodium and associated estimating equations provide a suitable alternative assessment of 24-hour sodium excretion in many large-scale studies, but not in chronic kidney disease (CKD) patients with decreased renal function. Herein, we aimed to develop a novel predictive equation. Design and Methods: We retrospectively enrolled all CKD patients at Stage 1-4 who received spot and 24-hour urinary analysis in our single center from January 1, 2014 to December 31, 2017. Multiple linear regression analysis generated a predictive equation for estimating 24-hour sodium excretion from spot urine samples in the derivation cohort admitted from 2014 to 2015, and then we assessed this predictive equation in a validation cohort admitted from 2016 to 2017. Results: All 5,235 patients were finally analyzed and divided into derivation (n 5 2,460) and validation (n 5 2,775) cohort according to the admission date. We generated a predictive equation and defined it as ‘‘CKDSALT’’ equation because it was used for the estimation of salt intake in CKD patients. When we measured sodium excretion as the gold standard, we compared this novel validation with other 3 equations: Kawasaki, INTERSALT, and Tanaka. The Bland-Altman plots indicated that the CKDSALT equation showed the lowest bias with limits of agreement (bias 5 21.25 mmol, 95% confidence interval 2121.3 to 123.8), and the best performance in any subgroup analysis: male and female, old and young, different levels of body mass index, various levels of estimated glomerular filtration rate, and 24-hour urine volume. The CKDSALT equation also had the highest Pearson (0.745) and intraclass correlation coefficient (0.853, 95% confidence interval 0.841-0.863) in all validation cohort and the above subgroups. Conclusion: Spot urine method by CKDSALT equation may be promising for estimating 24-hour urinary sodium excretion in CKD patients with normal renal function and patients with decreased estimated glomerular filtration rate. Ó 2019 by the National Kidney Foundation, Inc. All rights reserved.
Introduction
C *
Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China. † Shanghai Medical Center of Kidney, Shanghai, People’s Republic of China. ‡ Shanghai Institute of Kidney and Dialysis, Shanghai, People’s Republic of China. § Shanghai Key Laboratory of Kidney and Blood Purification, Shanghai, People’s Republic of China. { Hemodialysis Quality Control Center of Shanghai, Shanghai, People’s Republic of China. Jiachang Hu and Yimei Wang contributed equally to this work. Support: This work was supported by Shanghai Public Health Improvement Action Plan (grant no. 15GWZK0502), the National Natural Science Foundation of China (grant no. 81430015), and the Project of Science and Technology Commission of Shanghai Municipality (grant no. 17140902300). Financial Disclosure: The authors declare that they have no competing interests. Address correspondence to Xiaoqiang Ding, PhD, Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai 200032, People’s Republic of China. E-mail: [email protected] Ó 2019 by the National Kidney Foundation, Inc. All rights reserved. 1051-2276/$36.00 https://doi.org/10.1053/j.jrn.2019.02.002
Journal of Renal Nutrition, Vol -, No - (-), 2019: pp 1-11
HRONIC KIDNEY DISEASE (CKD) is now a serious global health burden and an independent risk factor for cardiovascular disease (CVD) and mortality.1 Blood pressure in CKD patients is more sensitive to high sodium intake than persons with normal kidney function due to a diminished sodium excretion.2 Higher sodium intake has been reported to be associated with higher blood pressure,3 increased risk of CVD, stroke, and death4,5 in community-level cohort studies. Recently, in CKD patients, higher sodium intake also increased the risk of CVD6 and accelerated the development of CKD.7 The sodium excretion using 24-hour urine is the most reliable among all methods to assess diet sodium intake in many epidemiological and clinical studies.3,6 Although the actual measurement of 24-hour urinary sodium excretion with repeated tests to determine the sodium intake would be ideal, such an approach is impractical for largescale surveys.8 Collecting a 24-hour urine specimen is difficult and inconvenient for patients and increases the 1
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HU ET AL
analytical variability. Therefore, several recent epidemiological cohort studies4,5,8 used spot urine to estimate 24hour sodium excretion as a surrogate for intake. However, available equations that estimate dietary sodium intake from spot urine sodium measurements, such as Kawasaki,9 INTERSALT,10 and Tanaka,11 have a substantial bias, poor precision, and poor accuracy when applied to patients with moderate to severe CKD.12 Therefore, a more accurate equation is needed to assess the 24-hour urinary sodium excretion from spot urine in CKD patients. Herein, we retrospectively collected 4-year data about the spot and 24-hour urinary analysis of CKD patients admitted in a single center and aimed to develop a predictive equation for estimating 24-hour sodium excretion from spot urine samples in CKD patients with various levels of renal function and assessed its validation.
Methods Participants The study population comprised all CKD patients at Stage 1-4 admitted to the Division of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China—a tertiary hospital—from January 1, 2014 to December 31, 2017. Participants were eligible for the study if estimated glomerular filtration rate (eGFR) $15 mL/minute/ 1.73 m2, according to the Chronic Kidney Disease Epidemiology Collaboration criteria.13 Exclusion criteria included the following: (1) younger than 18 years; (2) patients who have received renal replacement therapy, including hemodialysis, peritoneal dialysis, or kidney transplantation; (3) eGFR ,15 mL/minute/1.73 m2, corresponding to Stage 5 CKD; and (4) those without spot and 24-hour urinary analysis. All data were collected from our electronic medical records database. All the spot and 24-hour urinary analysis during hospitalization were recorded. Other data included demographics, primary kidney diseases, comorbidities, and laboratory values. This study was approved by the ethics committee of Zhongshan Hospital, Fudan University (B2018-175). As this was an observational survey, the requirement for informed consent was waived. Protocol and Data Collection Study participants were requested to collect morning fasting urine samples as spot urine and 24-hour urine specimens. They were provided with containers to collect urine samples including a plastic tube (10 mL) for the spot urine and a plastic bucket (4 L) for the 24-hour urine sample, and detailed written instructions on how to collect the specimens. On the next morning, the spot urine was collected in a separate tube. The 24-hour urine was collected into the plastic bucket without any omission. If the duration of collection was not between 24 hours, participants were instructed to recollect the urine samples. Spot and 24hour urine specimens were sent to our central laboratory
and measured by electrolyte analyzer IMS972Plus (Xi Cai Heng Medical Electronics, China), using the ionselective electrode method.
Statistical Analysis SPSS version 24.0 (SPSS Inc., Chicago, IL) was used for most analyses. A P-value ,.05 was considered statistically significant. All continuous variables were expressed as median (interquartile range, IQR). These data were analyzed using the unpaired t-test, or MannWhitney U-test, depending on the variable distribution. Categorical data were presented as percentages, and between-group differences assessed with the chisquared test. Two models of multiple linear regression with the Enter method were constructed to generate a gender-specific equation. In Model 1, age, body mass index, 24-hour urine volume, urine sodium, urea, and creatinine in spot urine were included as the dependent variables, while measured 24-hour urine sodium excretion as the independent variable. For the non-normal distribution with a wide range, several variables were natural log(ln)-transformed in Model 2, including urine sodium, urea, and creatinine in spot urine and measured 24-hour sodium excretion. We examined the medians and IQR for measured 24hour urinary sodium excretion and predicted 24-hour urinary sodium excretion using the Kawasaki,9 INTERSALT,10 Tanaka,11 and CKDSALT equations. BlandAltman plots were calculated using GraphPad Prism 7.0 (GraphPad Software, CA) to quantify the correlation and the agreement between measured and estimated 24-hour sodium excretion from equations. Paired t-tests were used to assess the statistical significance of differences in predicted-measured 24-hour excretion. Data are represented graphically as Bland-Altman plots with mean bias and limits of agreement at 95% confidence interval (CI). Here, the differences between the 2 paired measurements were plotted against the mean of the 2 measurements. We also qualified the correlations between estimated values and measured values using Pearson’s correlation coefficients. The intraclass correlation coefficient (ICC), using the ‘‘2-way mixed single measure test (absolute agreement),’’ was determined with SPSS version 24.0. An ICC between 0.600 and 0.749 was considered ‘‘fair,’’ ,0.600 ‘‘low,’’ $0.750 ‘‘good,’’ whereas a value $0.900 was considered ‘‘excellent.’’14 The validation of these 4 equations was also assessed in the subgroups which were divided by gender, age, body mass index (BMI), eGFR, and 24-hour urine volume.
Results In total, we enrolled 12,072 hospitalized patients with kidney disease. After excluding patients receiving renal replacement therapies (n 5 3,839), Stage 5 CKD (n 5 1,847), and those without urinary analysis (n 5 1,151), all 5,235 Stage 1-4 CKD patients were
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ESTIMATING URINARY SODIUM EXCRETION IN CKD
Figure 1. Flowchart of the study.
included in the final analysis. Data about the spot and 24hour urinalysis were available for all patients. The study participants were then divided into derivation (n 5 2,460) and validation (n 5 2,775) cohort according to the admission date (January 1, 2014 to December 31, 2015 versus January 1, 2016 to December 31, 2017, respectively). The flowchart is shown in Figure 1.
Baseline Characteristics Baseline characteristics of the study population are listed in Table 1. The median age of the entire cohort was 54.0 years, and 56.1% were male. Glomerulonephritis induced by nonautoimmune (55.3%) and autoimmune diseases (11.1%) followed by diabetic nephropathy (7.7%) was the most common primary diagnoses. The most frequent
Table 1. Baseline Characteristics of the Derivation and Validation Cohort Variables Male, n (%) Age (y), median (IQR) BMI (kg/m2), median (IQR) Primary kidney disease, n (%) Glomerulonephritis Systemic autoimmune diseases Diabetic nephropathy Urinary tract infection Hypertensive nephropathy Obstructive nephropathy Interstitial nephritis Others Comorbidities, n (%) Hypertension Diabetes mellitus Hyperuricemia Dyslipidemia Cardiovascular disease Heart failure Clinical parameters, median (IQR) eGFR (mL/min/1.73 m2) Hemoglobin (g/L) Albumin (g/L) Sodium (mmol/L)* Potassium (mmol/L)
Entire cohort (n 5 5,235)
Derivation (n 5 2,460)
Validation (n 5 2,775)
P-Value
2,939 (56.1) 54 (40-65) 24.2 (21.8-26.7)
1,335 (54.3) 53 (39-65) 24.1 (21.8-26.5)
1,604 (57.8) 55 (41-65) 24.2 (21.9-26.8)
2,896 (55.3) 582 (11.1)
1,335 (54.3) 280 (11.4)
1,561 (563.) 302 (10.9)
401 (7.7) 269 (5.1) 139 (2.7) 154 (2.9) 55 (1.1) 739 (14.1)
188 (7.6) 139 (5.7) 72 (2.9) 71 (2.9) 25 (1.0) 350 (14.2)
213 (7.7) 130 (4.7) 67 (2.4) 83 (53.9) 30 (1.1) 389 (14.0)
3,138 (59.9) 1,157 (22.1) 611 (11.7) 430 (8.2) 249 (4.8) 179 (3.4)
1,468 (59.7) 508 (20.7) 243 (9.9) 185 (7.5) 92 (3.7) 93 (3.8)
1,670 (60.2) 649 (23.4) 368 (13.3) 245 (8.8) 157 (5.7) 86 (3.1)
.710 .017 ,.001 .085 .001 .176
56.7 (33.9-91.3) 122.0 (108.0-136.0) 36.0 (30.0-40.0) 142.0 (140.0-144.0) 4.1 (3.8-4.4)
57.5 (33.8-92.6) 123.0 (108.0-136.0) 35.0 (29.0-39.0) 142.0 (140.0-144.0) 4.1 (3.8-4.4)
56.1 (33.9-90.6) 122.0 (108.0-136.0) 37.0 (30.0-40.0) 142.0 (140.0-143.0) 4.0 (3.8-4.3)
.236 .777 ,.001 ,.001 .022
BMI, body mass index; eGFR, estimated glomerular filtration rate; IQR, interquartile range. *Tested by Mann-Whitney U-test; other continuous variables were tested by unpaired t-test.
.010 .029 .992 .658
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Table 2. Spot and 24-H Urinary Analysis of the Derivation and Validation Cohort Variables, Median (IQR) Spot urinary analysis Sodium (mmol/L) Potassium (mmol/L) Chloride (mmol/L) Calcium (mmol/L) Phosphorus (mmol/L) Magnesium (mmol/L) Albumin (mg/L)* Creatinine (mmol/L) Urea (mmol/L)* Uric acid (mmol/L) 24-H urinary analysis Total urine volume (L)* Sodium (mmol) Potassium (mmol) Chloride (mmol) Calcium (mmol)* Phosphorus (mmol) Magnesium (mmol)* Protein quantitation (g) Albumin (mg)* Creatinine (mmol) Urea (mmol)* Uric acid (mmol)
Entire Cohort (n 5 5,235)
Derivation Cohort (n 5 2,460)
Validation Cohort (n 5 2,775)
93.1 (66.0-120.5) 22.0 (15.6-31.4) 75.9 (51.3-103.3) 1.12 (0.47-2.31) 11.1 (7.2-17.9) 2.0 (1.4-2.8) 612.4 (127.1-1,782.5) 6,833.3 (4,616.0-10,841.0) 190.2 (136.5-270.2) 1,723.0 (1,146.5-2,637.6)
94.3 (67.9-121.6) 21.8 (15.5-31.3) 77.3 (52.4-104.4) 1.05 (0.45-2.27) 11.0 (7.1-17.4) 2.0 (1.4-2.8) 651.3 (128.9-1,830.0) 6,970.0 (4,588.0-11,131.3) 187.9 (134.4-259.6) 1,732.6 (1,139.1-2,610.7)
92.2 (64.2-119.2) 22.2 (15.7-31.6) 74.3 (50.6-102.7) 1.17 (0.49-2.34) 11.2 (7.2-18.5) 2.1 (1.4-2.9) 572.1 (124.6-1,773.2) 6,733.0 (4,654.0-10,717.0) 193.6 (138.9-276.9) 1,719.0 (1,152.9-2,646.0)
.039 .595 .039 .401 .435 .030 .132 .517 .004 .692
2.0 (1.5-2.5) 148.0 (103.8-201.0) 35.3 (26.6-46.6) 121.0 (83.0-170.0) 1.95 (0.96-3.52) 13.8 (9.7-18.9) 3.0 (2.2-4.0) 1.37 (0.52-3.42) 1,060.7 (275.2-2,906.6) 9,752.0 (7,635.0-12,386.0) 281.0 (215.4-360.3) 2,481.0 (1,830.5-3,292.5)
2.0 (1.5-2.5) 155.0 (111.0-205.0) 35.9 (27.4-47.4) 126.0 (88.0-174.0) 1.90 (0.90-3.51) 14.1 (9.9-18.8) 3.0 (2.2-4.0) 1.46 (0.51-3.67) 1,146.5 (313.8-3,133.7) 9,838.5 (7,834.0-12,485.8) 281.4 (220.5-359.8) 2,550.0 (1,894.8-3,326.3)
2.0 (1.5-2.5) 142.0 (98.0-197.0) 34.8 (25.8-45.8) 115.0 (78.0-166.0) 1.98 (1.01-3.53) 13.5 (9.6-18.9) 3.0 (2.2-4.1) 1.30 (0.52-3.28) 956.6 (257.5-2,732.6) 9,644.0 (7,470.0-12,266.0) 280.8 (212.3-361.2) 2,402.0 (1,760.0-3,257.0)
.001 ,.001 .017 .007 .411 .431 .092 .200 .001 .005 .638 .001
P-Value
IQR, interquartile range. *Tested by Mann-Whitney U-test; other continuous variables were tested by unpaired t-test.
comorbidity was hypertension (59.9%), diabetes mellitus (22.1%), and hyperuricemia (11.7%), while CVD and heart failure accounted for 4.8% and 3.4% of the included patients, respectively. The median (IQR) of eGFR at admission was 56.7 (33.9-91.3) mL/minute/1.73 m2. The validation cohort was older and had more percentages of men, diabetes mellitus, hyperuricemia, and CVD than the derivation cohort. The validation cohort had higher albumin and lower serum sodium and potassium levels than the derivation cohort. There were no significant differences in the primary diagnosis of kidney diseases, eGFR, and hemoglobin levels at admission.
The Predictive Equation of 24-Hour Sodium Excretion From Spot Urine Analysis As shown in Table 2, the median (IQR) of the spot urine sodium concentration in the entire cohort was 93.1 (66.0120.5) mmol/L. The total urine volume was 2.0 (1.5-2.5) L, and the 24-hour sodium excretion was 148.0 (103.8201.0) mmol/24 hours. Table 2 also showed other results of urine analysis and the comparisons of the derivation and validation cohort. In Table 3, we conducted 2 models of multiple linear regression with Enter method to generate the predictive equation. In Model 1, we only did not find the associations of age in the male and female group and spot urine urea in the female group with measured 24-hour urine sodium excretion. According to the result of Model 1, the predictive equations were generated as:
Estimated 24-hour sodium excretion for male 5 1.270 3 BMI 2 0.079 3 age 1 69.673 3 24-hour urine volume 1 0.681 3 spot urine sodium 1 0.050 3 spot urine urea 2 0.002 3 spot urine creatinine 2 57.755. Estimated 24-hour sodium excretion for female 5 2.660 3 BMI 2 0.015 3 age 1 66.520 3 24-hour urine volume 1 0.670 3 spot urine sodium 1 0.031 3 spot urine urea 2 0.002 3 spot urine creatinine 2 103.361. For the non-normal distribution with wide ranges, several variables were natural log(ln)-transformed in Model 2, including urine sodium, urea, and creatinine in spot urine and measured 24-hour sodium excretion. We found that most of the included dependent variables had significant associations with the independent variable except for the age in the male group. Therefore, we built other equations: Ln (estimated 24-hour sodium excretion for male) 5 2.917 2 0.001 3 age 1 0.012 3 BMI 1 0.392 3 24-hour urine volume 1 0.437 3 Ln (spot urine sodium) 1 0.078 3 Ln (spot urine urea) 2 0.145 3 Ln (spot urine creatinine). Ln (estimated 24-hour sodium excretion for female) 5 2.943 2 0.002 3 age 1 0.019 3 BMI 1 0.433 3 24-hour urine volume 1 0.378 3 Ln (spot urine sodium) 1 0.075 3 Ln (spot urine urea) 2 0.154 3 Ln (spot urine creatinine).
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ESTIMATING URINARY SODIUM EXCRETION IN CKD Table 3. Generation of the Equation for Estimating 24-H Sodium Excretion From Spot Urine by Multiple Linear Regression Male Model Model 1
Model 2
Variables
B
Standard Error
Constant Age (y) Body mass index (kg/m2) 24-H urine volume (L) Spot urine sodium (mmol/L) Spot urine urea (mmol/L) Spot urine creatinine (mmol/L) Constant Age (y) Body mass index (kg/m2) 24-H urine volume (L) Ln (spot urine sodium) (mmol/L) Ln (spot urine urea) (mmol/L) Ln (spot urine creatinine) (mmol/L)
257.755 20.079 1.270 69.673 0.681 0.050 20.002 2.917 20.001 0.012 0.392 0.437 0.078 20.145
13.147 0.108 0.393 2.266 0.038 0.022 0.000 0.213 0.001 0.002 0.014 0.020 0.033 0.029
Finally, we compared the validation of the above equations using ICC coefficients and found that Model 2 equation had better performance to estimate 24-hour sodium excretion than Model 1, with the ICC (95% CI) 0.853 (0.841-0.863) versus 0.839 (0.827-0.851), respectively. Therefore, we only used Model 2 equation to compare the validation with other 3 previous equations in the following analysis. Because this equation was designed for the estimated 24-hour salt intakes in CKD patients, we named this equation as ‘‘CKDSALT’’ equation.
Assessment of Bias Between Predicted and Measured 24-Hour Sodium Excretion As illustrated in Tables 4 and 5, the degree of bias was significantly smaller with the CKDSALT (bias 5 1.25 mmol, 95% CI 2121.3 to 123.8, P . .05) and Tanaka (bias 5 20.003 mmol, 95% CI 2154.8 to 154.7, P . .05), compared with Kawasaki (bias 5 46.26 mmol, 95% CI 2114.4 to 207.0, P , .05) and INTERSALT (bias 5 220.44 mmol, 95% CI 2178.8 to 137.9, P , .05). Bland-Altman plots showed an overestimation of Kawasaki and underestimation of INTERSALT equation (Fig. 2). Although both Tanaka and CKDSALT equations showed small bias (P . .05), CKDSALT had a narrower CI than Tanaka. Pearson’s correlation coefficient between measured and estimated 24hour urinary sodium was the highest in CKDSALT (r 5 0.745) than Kawasaki, Tanaka, and INTERSALT (r 5 0.511, 0.482, and 0.443, respectively) (Table 6). Correlations Between Estimated and Measured Sodium Excretion As shown in Table 7, the estimated sodium excretions by Kawasaki, INTERSALT, and Tanaka were low-to-fair correlated with measured sodium excretion (0.4710.603). CKDSALT got the highest ICC (0.853, 95% CI 0.841-0.863) among the 4 equations, which reached the ‘‘good’’ degree. In Figure 3, the scatter plots showed that
Female t
P-Value
24.393 20.734 3.229 30.743 17.750 2.341 24.825 13.714 21.735 4.846 28.245 22.156 2.339 25.048
,.001 .463 .001 ,.001 ,.001 .019 ,.001 ,.001 .083 ,.001 ,.001 ,.001 .019 ,.001
B
Standard Error
t
P-Value
2103.361 20.015 2.660 66.520 0.671 0.031 20.002 2.943 20.002 0.019 0.433 0.378 0.075 20.154
12.804 0.106 0.437 2.333 0.040 0.024 0.000 0.228 0.001 0.003 0.016 0.020 0.036 0.032
28.073 20.145 6.086 28.511 16.925 1.299 23.285 12.932 22.496 6.202 26.445 18.525 2.067 24.789
,.001 .884 ,.001 ,.001 ,.001 .194 .001 ,.001 .013 ,.001 ,.001 ,.001 .039 ,.001
the CKDSALTalso got the highest R2 (0.5547) than Kawasaki (0.2615), Tanaka (0.2323), and INTERSALT (0.1963).
Validation of the Predicting Sodium Excretion in Subgroups To further assess the application of this novel predicting equation, the subjects were divided into several subgroups according to gender, age, BMI, eGFR, and 24-hour urine volume. The estimated sodium excretions by CKDSALT equation were more close to the measured sodium excretion (P . .05) than other 3 equations, in male and female, older and young, every level of BMI and eGFR. CKDSALT equation got the highest Pearson’s correlation coefficients (0.509-0.638) and ICC (0.574-0.767) compared with other 3 equations in every level of 24hour urine volume subgroups, although it overestimated sodium excretion when 24-hour urine volume was $3.0 L (bias 5 29.20 mmol).
Discussion In the present study, we retrospectively enrolled 5,235 hospitalized CKD patients at Stage 1-4 in a large, tertiary hospital in East China. Multiple linear regression analysis generated a predictive equation, named as ‘‘CKDSALT,’’ for estimating 24-hour sodium excretion from spot urinary analysis in derivation cohort, which was assessed in the validation cohort. When we measured sodium excretion as the gold standard, we compared its validation with other 3 equations: Kawasaki, INTERSALT, and Tanaka. The CKDSALT equation showed the lowest bias with limits of agreement in Bland-Altman plots, had the highest Pearson’s correlation and ICC coefficients among the 4r formulas. The CKDSALT equation also showed the best performance in various subgroups, including male and female, old and young, different levels of BMI, eGFR, and 24-hour urine volume.
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Table 4. Medians and Interquartile Range of Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
Estimated, Median (IQR)
Measured, Median (IQR)
Kawasaki
INTERSALT
Tanaka
CKDSALT
142.0 (98.0-197.0)
196.0 (155.5-244.1)
136.2 (109.3-167.2)
156.0 (128.8-184.3)*
144.3 (110.0-189.8)*
155.0 (107.0-216.0) 124.0 (86.20-177.0)
211.9 (168.0-258.8) 181.6 (145.8-222.2)
162.4 (141.9-180.1) 108.3 (92.3-122.3)
159.3 (131.9-188.0) 151.5 (125.5-178.1)
159.4 (121.6-203.9)* 127.4 (98.4-163.6)*
133.0 (94.0-183.0) 146.0 (100.0-202.0)
201.5 (162.6-244.2) 196.3 (153.1-244.0)
136.6 (93.9-169.9) 136.1 (113.0-1365.8)
163.3 (138.3-192.1) 153.0 (126.5-181.5)
132.8 (103.5-177.2)* 148.3 (113.2-193.6)*
159.0 (113.0-217.0) 132.0 (90.3-185.0)
211.6 (169.2-256.1) 191.1 (148.6-235.6)
156.9 (124.1-180.8) 126.4 (104.2-155.6)
164.7 (138.1-193.0) 150.7 (124.6-178.2)
159.5 (125.3-205.9)* 135.2 (103.4-176.9)*
99.0 (65.5-150.0)
171.7 (130.4-204.0)
101.6 (83.5-123.0)*
134.6 (110.6-157.4)
108.6 (81.9-140.5)*
132.0 (92.0-187.0) 147.0 (98.5-211.0) 150.0 (106.0-207.0) 147.0 (95.0-196.0) 140.0 (100.0-192.0)
180.0 (145.1-222.3) 191.2 (150.5-235.5) 204.7 (163.8-253.5) 203.1 (153.7-244.0) 219.2 (179.1-263.4)
117.5 (101.6-136.2) 136.2 (106.8-164.8) 148.8 (112.5-174.2) 147.7 (117.2-173.2) 154.9 (125.5-174.0)*
148.0 (123.0-175.1)* 150.2 (123.5-178.4) 158.2 (131.9-187.6)* 157.7 (128.7-187.1)* 170.0 (145.0-195.1)
136.8 (104.9-173.9)* 149.6 (113.3-198.4)* 156.7 (115.8-202.5)* 146.2 (109.9-190.4)* 141.3 (109.3-187.3)*
234.0 (171.0-338.5) 163.0 (120.0-213.0) 115.0 (81.0-155.0) 56.0 (35.0-82.0)
233.7 (186.5-280.6) 204.7 (165.0-249.7) 185.5 (145.2-228.2) 168.4 (117.0-219.6)
155.3 (126.5-178.0) 138.5 (113.3-167.9) 129.7 (104.0-161.8) 123.7 (85.2-163.4)
174.7 (148.7-203.0) 161.6 (135.8-187.9) 147.3 (122.4-175.4) 138.4 (104.4-164.8)
264.3 (220.4-318.9) 168.1 (141.6-197.8)* 115.4 (94.6-137.4) 78.6 (58.6-99.4)
BMI, body mass index; eGFR, estimated glomerular filtration rate; IQR, interquartile range. *P . .05, when the estimated and measured sodium excretions were tested by paired t-test.
Table 5. Bias With Limits of Agreement Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Bias (LoA) Patients (n, %)
Kawasaki
INTERSALT
All (2,755, 100) 46.26 (2114.4 to 207.0) 220.44 (2178.8 to 137.9) Gender Male (1,604, 57.8) 43.79 (2136.7 to 224.2) 214.28 (2193.1 to 164.5) Female (1,171, 42.2) 49.65 (279.0 to 178.3) 228.87 (2152.0 to 94.3) Age (y) $65 (755, 27.2) 61.07 (291.9 to 21.4.0) 212.94 (2160.6 to 134.7) 18-64 (2,020, 72.8) 40.72 (2121.5 to 202.9) 223.24 (185.1-138.6) BMI (kg/m2) $25 (1,161, 41.8) 40.65 (2138.1 to 219.1) 224.39 (2203.8 to 155.0) 18.5-24.9 (1,480, 53.3) 48.98 (299.3 to 197.2) 218.40 (2161.7 to 124.9) ,18.5 (134, 4.8) 64.85 (248.83 to 178.5) 28.61 (2120.8 to 103.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 40.84 (2106.0 to 187.7) 227.85 (2175.3 to 119.6) 60-89 (561, 20.2) 29.97 (2146.6 to 206.6) 231.12 (2211.8 to 149.6) 45-59 (439, 15.8) 43.82 (2122.8 to 210.4) 222.78 (2180.6 to 135.1) 30-44 (517, 18.6) 47.09 (2114.9 to 209.1) 213.08 (2167.8 to 141.7) 15-29 (549, 19.8) 70.89 (272.5 to 214.2) 25.35 (2150.2 to 139.5) 24-H urine volume (L) $3.0 (340, 12.3) 225.15 (2269.6 to 219.3) 2113.90 (2350.2 to 122.5) 2.0-2.9 (1,152, 41.5) 39.39 (296.0 to 174.7) 232.62 (2158.5 to 93.3) 1.0-1.9 (1,140, 41.1) 66.79 (255.2 to 188.8) 9.60 (291.2 to 110.4) ,1.0 (143, 5.2) 107.20 (227.12 to 241.4) 59.35 (231.1 to 149.8)
Tanaka
CKDSALT
20.03 (2154.8 to 154.7)
1.25 (2121.3 to 123.8)
212.58 (2185.1 to 159.9) 17.17 (2101.3 to 135.6)
1.14 (2135.5 to 137.8) 1.41 (298.7 to 101.5)
19.36 (2122.7 to 161.4) 27.27 (2164.2 to 149.6)
1.87 (291.8 to 95.6) 1.02 (2130.7 to 132.8)
210.16 (2184.4 to 164.1) 5.50 (2134.0 to 145.0) 26.65 (275.8 to 129.1)
0.11 (2142.3 to 142.5) 1.89 (2105.0 to 108.8) 4.15 (292.2 to 100.5)
2.17 (2136.3 to 140.7) 20.29 (2125.9 to 125.3) 214.99 (2196.1 to 166.1) 0.93 (2164.1 to 165.9) 26.43 (2165.8 to 153.0) 3.26 (2113.8 to 120.3) 0.64 (2152.1 to 153.4) 1.20 (297.6 to 100.0) 16.69 (2119.1 to 152.5) 1.72 (285.0 to 88.5) 288.05 (2326.7 to 150.6) 29.20 (2201 to 259.4) 29.53 (2132.1 to 113.0) 21.79 (2109.7 to 106.1) 24.87 (275.34 to 125.1) 25.92 (290.0 to 78.2) 73.29 (224.5 to 171.0) 15.30 (258.0 to 88.6)
BMI, body mass index; eGFR, estimated glomerular filtration rate; LoA, limits of agreement.
ESTIMATING URINARY SODIUM EXCRETION IN CKD
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Figure 2. Bland-Altman plots of measured 24-hour urine sodium excretion versus estimated 24-hour urine sodium excretion by Kawasaki (A), INTERSALT (B), Tanaka (C), and CKDSALT (D) equations. The difference between measured and estimated 24hour urine sodium excretion was all estimated values minus the measured values. The mid-dashed line was the mean bias, while the upper and lower dashed lines were the upper and lower limits, respectively.
The collection of 24-hour urine is considered to be the most reliable method to evaluate individual salt intake. However, the complete and accurate collection is always tricky and inconvenient, especially in large-scale studies. Spot urine specimens may be a useful, low-burden, lowcost alternative to 24-hour urine collections for estimation of population sodium intakes.10 The most popular predicting equations of sodium excretion from the spot urine analysis are Kawasaki,9 INTERSALT,10 and Tanaka,11 which have been fully evaluated in many studies, but with a poor agreement between estimated and observed sodium excretion. Polonia et al.15 analyzed 2,399 individuals aged 1896 years representatives of a western population and found that formulas produced mean biases were 21277 mg for Kawasaki, 569 mg for INTERSALT, and 11 mg for Tanaka, and ICCs were 0.303, 0.457, and 0.340, which met the ‘‘low’’ degree. Another study16 revealed that INTERSALT equations (bias 5 2165 mg for morning spot urine) might provide the least biased information about the population mean sodium intakes among US adults aged 18-39 years among the 4 formulas. These equations were also assessed in Chinese adults but were proved to underestimate 24-
hour sodium excretion.17 Furthermore, the validation of these equations in CKD patients has not been estimated. Therefore, a more accurate method is needed to evaluate sodium excretion from spot urine in the general Chinese population as well as CKD patients. Herein, we generated this CKDSALT equation to estimating 24-hour sodium excretion from spot urinary analysis. There were several reasons for the difficulty in predicting 24-hour sodium excretion from spot urine in CKD patients. A common problem exists in all predicting formulas using spot urine, that is, the urinary sodium excretion over 24 hours is not constant but instead varies around the intake, which leads to the inaccuracy of spot urine to estimate salt intake.18 Especially, predicting 24hour sodium excretion using spot urine in CKD patients may be more complex than the general population, because of the influences of the administrations of diuretics, different levels of eGFR, 24-hour urine volume, and changed the rhythm of sodium excretion. Another critical issue is that the level of urine creatinine, which has been used in many predicting formulas, has a strong association with the decreased renal function and its
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Table 6. Pearson Correlation Coefficients Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Kawasaki Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
INTERSALT
Tanaka
CKDSALT
Coefficient
P-Value
Coefficient
P-Value
Coefficient
P-Value
Coefficient
P-Value
0.511
,.001
0.443
,.001
0.482
,.001
0.745
,.001
0.484 0.496
,.001 ,.001
0.417 0.420
,.001 ,.001
0.469 0.495
,.001 ,.001
0.746 0.691
,.001 ,.001
0.461 0.531
,.001 ,.001
0.398 0.469
,.001 ,.001
0.448 0.510
,.001 ,.001
0.810 0.726
,.001 ,.001
0.486 0.498 0.600
,.001 ,.001 ,.001
0.388 0.419 0.493
,.001 ,.001 ,.001
0.446 0.470 0.606
,.001 ,.001 ,.001
0.727 0.749 0.667
,.001 ,.001 ,.001
0.569 0.523 0.455 0.480 0.554
,.001 ,.001 ,.001 ,.001 ,.001
0.457 0.476 0.441 0.445 0.441
,.001 ,.001 ,.001 ,.001 ,.001
0.545 0.466 0.425 0.468 0.541
,.001 ,.001 ,.001 ,.001 ,.001
0.672 0.707 0.755 0.821 0.845
,.001 ,.001 ,.001 ,.001 ,.001
0.412 0.510 0.496 0.399
,.001 ,.001 ,.001 ,.001
0.436 0.434 0.467 0.452
,.001 ,.001 ,.001 ,.001
0.381 0.485 0.447 0.384
,.001 ,.001 ,.001 ,.001
0.638 0.633 0.652 0.509
,.001 ,.001 ,.001 ,.001
BMI, body mass index; eGFR, estimated glomerular filtration rate.
ranges may be fairly wide in CKD patients. Therefore, when conducting multiple linear regression, not only gender, age, spot urine sodium, and creatinine levels but
also 24-hour urine volume and spot urine urea were concluded as dependent variables to increase the accuracy of the predicting equation. That may be difficult and
Table 7. Intraclass Correlation Coefficients Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine ICC (95% CI) Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
Kawasaki
INTERSALT
Tanaka
CKDSALT
0.603 (0.379-0.727)
0.471 (0.411-0.523)
0.553 (0.518-0.585)
0.853 (0.841-0.863)
0.591 (0.428-0.696) 0.552 (0.165-0.730)
0.374 (0.309-0.433) 0.373 (0.224-0.486)
0.520 (0.470-0.566) 0.590 (0.515-0.651)
0.854 (0.839-0.868) 0.811 (0.788-0.831)
0.509 (0.109-0.700) 0.635 (0.466-0.736)
0.503 (0.425-0.570) 0.457 (0.383-0.519)
0.524 (0.436-0.596) 0.567 (0.527-0.603)
0.892 (0.875-0.906) 0.840 (0.826-0.854)
0.596 (0.449-0.694) 0.578 (0.283-0.707) 0.572 (20.119 to 0.804)
0.391 (0.305-0.465) 0.456 (0.384-0.518) 0.537 (0.351-0.670)
0.501 (0.440-0.556) 0.556 (0.508-0.599) 0.650 (0.420-0.777)
0.842 (0.823-0.859) 0.853 (0.837-0.867) 0.778 (0.688-0.842)
0.668 (0.458-0.779) 0.628 (0.527-0.703) 0.555 (0.347-0.683) 0.572 (0.330-0.709) 0.556 (20.015 to 0.770)
0.435 (0.310-0.533) 0.455 (0.332-0.552) 0.473 (0.354-0.569) 0.489 (0.392-0.570) 0.490 (0.398-0.569)
0.624 (0.565-0.676) 0.489 (0.396-0.567) 0.493 (0.389-0.579) 0.545 (0.459-0.617) 0.603 (0.521-0.670)
0.795 (0.763-0.823) 0.827 (0.795-0.853) 0.856 (0.826-0.880) 0.896 (0.877-0.913) 0.913 (0.898-0.927)
0.544 (0.433-0.632) 0.611 (0.379-0.737) 0.471 (20.104 to 0.715) 0.238 (20.167 to 0.531)
0.226 (20.067 to 0.435) 0.463 (0.279-0.589) 0.599 (0.544-0.647) 0.383 (20.184 to 0.673)
0.302 (0.025-0.490) 0.589 (0.536-0.635) 0.565 (0.374-0.683) 0.283 (20.179 to 0.581)
0.767 (0.703-0.816) 0.714 (0.679-0.745) 0.710 (0.673-0.743) 0.574 (0.375-0.705)
BMI, body mass index; CI, confidence interval; eGFR, estimated glomerular filtration rate; ICC, intraclass correlation.
ESTIMATING URINARY SODIUM EXCRETION IN CKD
9
Figure 3. Scatter plots measured 24-hour urine sodium excretion versus estimated 24-hour urine sodium excretion by Kawasaki (A), INTERSALT (B), Tanaka (C), and CKDSALT (D) equations. The real line was the linear regression lines of the scatters in the spots. The dashed lines were the 95% confidence interval lines.
impractical to collect 24-hour urine specimens and record 24-hour urine volume in large-scale studies, and all the previous estimating equations did not contain the variable of 24-hour urine volume. In fact, it is unnecessary to provide 24-hour urine volume as a variable to estimate 24hour urinary sodium excretion from spot urine in general population but necessary for CKD patients. Furthermore, it is feasible to record each urine volume and calculate the sum of 24-hour urine volume to increase the accuracy of the CKDSALT equation in CKD patients, but the urine samples are not necessary to be collected, which is less costly and more convenient than collecting and testing 24-hour urine samples. Both urine urea and sodium excretions are associated with volume status and kidney injury, and the fractional excretion of sodium and urea has been used as indicators of acute kidney injury.19,20 Our present study also showed the association of urine urea and sodium excretion in the multiple linear regression. Therefore, we finally added the above 2 dependent variables in the conduction of CKDSALT equation. However, for the wide range of some variables and nonlinear relationship, several variables were natural logarithmic (ln) transformed in Model 2,
such as urine sodium, urea, and creatinine in spot urine, and measured 24-hour sodium excretion. We finally found that Model 2 equation had better performance to estimate 24-hour sodium excretion than Model 1 equation from crude multiple linear regression, with the ICC (95%CI) 0.853 (0.841-0.863) versus 0.839 (0.8270.851), respectively. Kawasaki equation got the least biased bias among the 3 methods in Chinese17 and diverse population studies.21 But in our study, the most significant bias was observed in the Kawasaki equation, which was derived based on data for the second-morning urine, and less accurate when estimating sodium excretion from the first voiding of urine. We used the first voiding of urine to evaluate the equations mainly because the patients are accustomed to collect the first-morning urine, and it is difficult to collect second-morning urine samples from CKD patients. Bland-Altman plots showed an overestimation of Kawasaki equation in CKD patients in our study (bias 5 46.26 mmol, 95% CI 2114.4 to 207.0, P , .05), which was consistent with the result with another survey to assess the validation of Kawasaki equation in CKD patients. It was suggested that the night-
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time sodium excretion was higher than the daytime one in a CKD population,22 and so nocturnal polyuria due to natriuresis during the night may affect the estimation performed by Kawasaki equation in CKD patients. Using a single spot urine, INTERSALT equations may provide the least biased information about the population mean sodium intake among young US adults,16 but in the Chinese population, mean bias for the INTERSALT method was 22797 mg/day and was the highest of the 3 methods.17 We found that the INTERSALT equation underestimated the sodium excretion from BlandAltman plots in CKD patients (bias 5 220.44 mmol, 95% CI 2178.8 to 137.9, P , .05). The INTERSALT equation uses actual creatinine, rather than estimated 24-hour creatinine, which is expected to become an issue in older age groups with decreased renal function.23 Furthermore, it includes potassium intake, which may be inappropriate in populations with various dietary patterns and renal function. Except for the CKDSALT equation, Tanaka equation provided the least bias among these 3 equations (bias 5 20.003 mmol). It has been proved to be an accurate formula to estimate sodium excretion from the first-morning urine in CKD patients.24 However, the Pearson and ICC coefficients were only 0.482 and 0.553, and it still had high bias in the following patients: old (bias 5 19.36 mmol), male (underestimation), female (overestimation), BMI ,18.5 kg/m2 (bias 5 26.65 mmol), low eGFR (1529 mL/minute/1.73 m2, bias 5 16.69 mmol), and 24hour urine volume $3.0 L or ,2.0 L. In the present study, the CKDSALT equation had the best performance among the 4 formulas in all validation methods, including Bland-Altman plots, Pearson, and ICC coefficients, not only in CKD patients with normal renal function but also patients with decreased eGFR and 24-hour urine volume.
Study Limitations However, several limitations should be noted. First, this predictive equation needs to record each urine volume and calculate the sum of 24-hour urine volume, which may lead to more participant burden than just collecting spot urine samples. However, it is difficult to increase the accuracy from spot urine without 24-hour urine volume. It needs to be further explored whether the estimated 24-hour urine volume could be used in the equation. Second, even the measured 24-hour sodium excretion may not accurately evaluate individual salt intake in CKD patients with decreased renal function. Right now, there are no related reports pertaining to the association of salt intake with 24-hour urine sodium excretion when eGFR decreases. Third, the validation of the CKDSALTequation in patients without CKD
and international population needs to be thoroughly tested in future research.
Practical Application Spot urine method is acceptable for estimating 24hour urinary sodium excretion in Stage 1-4 CKD patients. The CKDSALT equation provides the least biased estimates of 24-hour sodium excretion not only in CKD patients with normal renal function but also patients with decreased eGFR and 24-hour urine volume.
References 1. Hill NR, Fatoba ST, Oke JL, et al. Global prevalence of chronic kidney disease—a systematic review and meta-analysis. PLoS One. 2016;11:e0158765. 2. Johnson RJ, Herrera-Acosta J, Schreiner GF, Rodriguez-Iturbe B. Subtle acquired renal injury as a mechanism of salt-sensitive hypertension. N Engl J Med. 2002;346:913-923. 3. Jackson SL, Cogswell ME, Zhao L, et al. Association between urinary sodium and potassium excretion and blood pressure among adults in the United States: National Health and Nutrition Examination Survey, 2014. Circulation. 2018;137:237-246. 4. O’Donnell M, Mente A, Rangarajan S, et al. Urinary sodium and potassium excretion, mortality, and cardiovascular events. N Engl J Med. 2014;371:612-623. 5. Mente A, O’Donnell M, Rangarajan S, et al. Urinary sodium excretion, blood pressure, cardiovascular disease, and mortality: a community-level prospective epidemiological cohort study. Lancet. 2018;392:496-506. 6. Mills KT, Chen J, Yang W, et al. Sodium excretion and the risk of cardiovascular disease in patients with chronic kidney disease. JAMA. 2016;315:2200-2210. 7. Yoon CY, Noh J, Lee J, et al. High and low sodium intakes are associated with incident chronic kidney disease in patients with normal renal function and hypertension. Kidney Int. 2018;93:921-931. 8. Mente A, O’Donnell MJ, Rangarajan S, et al. Association of urinary sodium and potassium excretion with blood pressure. N Engl J Med. 2014;371: 601-611. 9. Kawasaki T, Itoh K, Uezono K, Sasaki H. A simple method for estimating 24 h urinary sodium and potassium excretion from second morning voiding urine specimen in adults. Clin Exp Pharmacol Physiol. 1993;20: 7-14. 10. Brown IJ, Dyer AR, Chan Q, et al. Estimating 24-hour urinary sodium excretion from casual urinary sodium concentrations in Western populations: the INTERSALT study. Am J Epidemiol. 2013;177: 1180-1192. 11. Tanaka T, Okamura T, Miura K, et al. A simple method to estimate populational 24-h urinary sodium and potassium excretion using a casual urine specimen. J Hum Hypertens. 2002;16:97-103. 12. Dougher CE, Rifkin DE, Anderson CA, et al. Spot urine sodium measurements do not accurately estimate dietary sodium intake in chronic kidney disease. Am J Clin Nutr. 2016;104:298-305. 13. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604-612. 14. Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess. 1994;6:284. 15. Polonia J, Lobo MF, Martins L, Pinto F, Nazare J. Estimation of populational 24-h urinary sodium and potassium excretion from spot urine samples: evaluation of four formulas in a large national representative population. J Hypertens. 2017;35:477-486.
ESTIMATING URINARY SODIUM EXCRETION IN CKD 16. Cogswell ME, Wang CY, Chen TC, et al. Validity of predictive equations for 24-h urinary sodium excretion in adults aged 18-39 y. Am J Clin Nutr. 2013;98:1502-1513. 17. Peng Y, Li W, Wang Y, et al. Validation and assessment of three methods to estimate 24-h urinary sodium excretion from spot urine samples in Chinese adults. PLoS One. 2016;11:e0149655. 18. Lerchl K, Rakova N, Dahlmann A, et al. Agreement between 24-hour salt ingestion and sodium excretion in a controlled environment. Hypertension. 2015;66:850-857. 19. Pepin MN, Bouchard J, Legault L, Ethier J. Diagnostic performance of fractional excretion of urea and fractional excretion of sodium in the evaluations of patients with acute kidney injury with or without diuretic treatment. Am J Kidney Dis. 2007;50:566-573. 20. Vanmassenhove J, Glorieux G, Hoste E, Dhondt A, Vanholder R, Van Biesen W. Urinary output and fractional excretion of sodium and urea as in-
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dicators of transient versus intrinsic acute kidney injury during early sepsis. Crit Care. 2013;17:R234. 21. Mente A, O’Donnell MJ, Dagenais G, et al. Validation and comparison of three formulae to estimate sodium and potassium excretion from a single morning fasting urine compared to 24-h measures in 11 countries. J Hypertens. 2014;32:1005-1014. discussion 1015. 22. Fukuda M, Motokawa M, Miyagi S, et al. Polynocturia in chronic kidney disease is related to natriuresis rather than to water diuresis. Nephrol Dial Transpl. 2006;21:2172-2177. 23. Hallan SI, Dahl K, Oien CM, et al. Screening strategies for chronic kidney disease in the general population: follow-up of cross sectional health survey. BMJ. 2006;333:1047. 24. Imai E, Yasuda Y, Horio M, et al. Validation of the equations for estimating daily sodium excretion from spot urine in patients with chronic kidney disease. Clin Exp Nephrol. 2011;15:861-867.
Estimating 24-Hour Urinary Sodium Excretion From Spot Urine Samples in Chronic Kidney Disease Patients Jiachang Hu, PhD,*,†,‡,§,{ Yimei Wang, PhD,*,†,‡,§,{ Nana Song, PhD,*,†,‡,§,{ Xiaoyan Zhang, PhD,*,†,‡,§,{ Jie Teng, PhD,*,†,‡,§,{ Jianzhou Zou, PhD,*,†,‡,§,{ and Xiaoqiang Ding, PhD*,†,‡,§,{ Objective: Spot urine sodium and associated estimating equations provide a suitable alternative assessment of 24-hour sodium excretion in many large-scale studies, but not in chronic kidney disease (CKD) patients with decreased renal function. Herein, we aimed to develop a novel predictive equation. Design and Methods: We retrospectively enrolled all CKD patients at Stage 1-4 who received spot and 24-hour urinary analysis in our single center from January 1, 2014 to December 31, 2017. Multiple linear regression analysis generated a predictive equation for estimating 24-hour sodium excretion from spot urine samples in the derivation cohort admitted from 2014 to 2015, and then we assessed this predictive equation in a validation cohort admitted from 2016 to 2017. Results: All 5,235 patients were finally analyzed and divided into derivation (n 5 2,460) and validation (n 5 2,775) cohort according to the admission date. We generated a predictive equation and defined it as ‘‘CKDSALT’’ equation because it was used for the estimation of salt intake in CKD patients. When we measured sodium excretion as the gold standard, we compared this novel validation with other 3 equations: Kawasaki, INTERSALT, and Tanaka. The Bland-Altman plots indicated that the CKDSALT equation showed the lowest bias with limits of agreement (bias 5 21.25 mmol, 95% confidence interval 2121.3 to 123.8), and the best performance in any subgroup analysis: male and female, old and young, different levels of body mass index, various levels of estimated glomerular filtration rate, and 24-hour urine volume. The CKDSALT equation also had the highest Pearson (0.745) and intraclass correlation coefficient (0.853, 95% confidence interval 0.841-0.863) in all validation cohort and the above subgroups. Conclusion: Spot urine method by CKDSALT equation may be promising for estimating 24-hour urinary sodium excretion in CKD patients with normal renal function and patients with decreased estimated glomerular filtration rate. Ó 2019 by the National Kidney Foundation, Inc. All rights reserved.
Introduction
C *
Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China. † Shanghai Medical Center of Kidney, Shanghai, People’s Republic of China. ‡ Shanghai Institute of Kidney and Dialysis, Shanghai, People’s Republic of China. § Shanghai Key Laboratory of Kidney and Blood Purification, Shanghai, People’s Republic of China. { Hemodialysis Quality Control Center of Shanghai, Shanghai, People’s Republic of China. Jiachang Hu and Yimei Wang contributed equally to this work. Support: This work was supported by Shanghai Public Health Improvement Action Plan (grant no. 15GWZK0502), the National Natural Science Foundation of China (grant no. 81430015), and the Project of Science and Technology Commission of Shanghai Municipality (grant no. 17140902300). Financial Disclosure: The authors declare that they have no competing interests. Address correspondence to Xiaoqiang Ding, PhD, Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai 200032, People’s Republic of China. E-mail: [email protected] Ó 2019 by the National Kidney Foundation, Inc. All rights reserved. 1051-2276/$36.00 https://doi.org/10.1053/j.jrn.2019.02.002
Journal of Renal Nutrition, Vol -, No - (-), 2019: pp 1-11
HRONIC KIDNEY DISEASE (CKD) is now a serious global health burden and an independent risk factor for cardiovascular disease (CVD) and mortality.1 Blood pressure in CKD patients is more sensitive to high sodium intake than persons with normal kidney function due to a diminished sodium excretion.2 Higher sodium intake has been reported to be associated with higher blood pressure,3 increased risk of CVD, stroke, and death4,5 in community-level cohort studies. Recently, in CKD patients, higher sodium intake also increased the risk of CVD6 and accelerated the development of CKD.7 The sodium excretion using 24-hour urine is the most reliable among all methods to assess diet sodium intake in many epidemiological and clinical studies.3,6 Although the actual measurement of 24-hour urinary sodium excretion with repeated tests to determine the sodium intake would be ideal, such an approach is impractical for largescale surveys.8 Collecting a 24-hour urine specimen is difficult and inconvenient for patients and increases the 1
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analytical variability. Therefore, several recent epidemiological cohort studies4,5,8 used spot urine to estimate 24hour sodium excretion as a surrogate for intake. However, available equations that estimate dietary sodium intake from spot urine sodium measurements, such as Kawasaki,9 INTERSALT,10 and Tanaka,11 have a substantial bias, poor precision, and poor accuracy when applied to patients with moderate to severe CKD.12 Therefore, a more accurate equation is needed to assess the 24-hour urinary sodium excretion from spot urine in CKD patients. Herein, we retrospectively collected 4-year data about the spot and 24-hour urinary analysis of CKD patients admitted in a single center and aimed to develop a predictive equation for estimating 24-hour sodium excretion from spot urine samples in CKD patients with various levels of renal function and assessed its validation.
Methods Participants The study population comprised all CKD patients at Stage 1-4 admitted to the Division of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China—a tertiary hospital—from January 1, 2014 to December 31, 2017. Participants were eligible for the study if estimated glomerular filtration rate (eGFR) $15 mL/minute/ 1.73 m2, according to the Chronic Kidney Disease Epidemiology Collaboration criteria.13 Exclusion criteria included the following: (1) younger than 18 years; (2) patients who have received renal replacement therapy, including hemodialysis, peritoneal dialysis, or kidney transplantation; (3) eGFR ,15 mL/minute/1.73 m2, corresponding to Stage 5 CKD; and (4) those without spot and 24-hour urinary analysis. All data were collected from our electronic medical records database. All the spot and 24-hour urinary analysis during hospitalization were recorded. Other data included demographics, primary kidney diseases, comorbidities, and laboratory values. This study was approved by the ethics committee of Zhongshan Hospital, Fudan University (B2018-175). As this was an observational survey, the requirement for informed consent was waived. Protocol and Data Collection Study participants were requested to collect morning fasting urine samples as spot urine and 24-hour urine specimens. They were provided with containers to collect urine samples including a plastic tube (10 mL) for the spot urine and a plastic bucket (4 L) for the 24-hour urine sample, and detailed written instructions on how to collect the specimens. On the next morning, the spot urine was collected in a separate tube. The 24-hour urine was collected into the plastic bucket without any omission. If the duration of collection was not between 24 hours, participants were instructed to recollect the urine samples. Spot and 24hour urine specimens were sent to our central laboratory
and measured by electrolyte analyzer IMS972Plus (Xi Cai Heng Medical Electronics, China), using the ionselective electrode method.
Statistical Analysis SPSS version 24.0 (SPSS Inc., Chicago, IL) was used for most analyses. A P-value ,.05 was considered statistically significant. All continuous variables were expressed as median (interquartile range, IQR). These data were analyzed using the unpaired t-test, or MannWhitney U-test, depending on the variable distribution. Categorical data were presented as percentages, and between-group differences assessed with the chisquared test. Two models of multiple linear regression with the Enter method were constructed to generate a gender-specific equation. In Model 1, age, body mass index, 24-hour urine volume, urine sodium, urea, and creatinine in spot urine were included as the dependent variables, while measured 24-hour urine sodium excretion as the independent variable. For the non-normal distribution with a wide range, several variables were natural log(ln)-transformed in Model 2, including urine sodium, urea, and creatinine in spot urine and measured 24-hour sodium excretion. We examined the medians and IQR for measured 24hour urinary sodium excretion and predicted 24-hour urinary sodium excretion using the Kawasaki,9 INTERSALT,10 Tanaka,11 and CKDSALT equations. BlandAltman plots were calculated using GraphPad Prism 7.0 (GraphPad Software, CA) to quantify the correlation and the agreement between measured and estimated 24-hour sodium excretion from equations. Paired t-tests were used to assess the statistical significance of differences in predicted-measured 24-hour excretion. Data are represented graphically as Bland-Altman plots with mean bias and limits of agreement at 95% confidence interval (CI). Here, the differences between the 2 paired measurements were plotted against the mean of the 2 measurements. We also qualified the correlations between estimated values and measured values using Pearson’s correlation coefficients. The intraclass correlation coefficient (ICC), using the ‘‘2-way mixed single measure test (absolute agreement),’’ was determined with SPSS version 24.0. An ICC between 0.600 and 0.749 was considered ‘‘fair,’’ ,0.600 ‘‘low,’’ $0.750 ‘‘good,’’ whereas a value $0.900 was considered ‘‘excellent.’’14 The validation of these 4 equations was also assessed in the subgroups which were divided by gender, age, body mass index (BMI), eGFR, and 24-hour urine volume.
Results In total, we enrolled 12,072 hospitalized patients with kidney disease. After excluding patients receiving renal replacement therapies (n 5 3,839), Stage 5 CKD (n 5 1,847), and those without urinary analysis (n 5 1,151), all 5,235 Stage 1-4 CKD patients were
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ESTIMATING URINARY SODIUM EXCRETION IN CKD
Figure 1. Flowchart of the study.
included in the final analysis. Data about the spot and 24hour urinalysis were available for all patients. The study participants were then divided into derivation (n 5 2,460) and validation (n 5 2,775) cohort according to the admission date (January 1, 2014 to December 31, 2015 versus January 1, 2016 to December 31, 2017, respectively). The flowchart is shown in Figure 1.
Baseline Characteristics Baseline characteristics of the study population are listed in Table 1. The median age of the entire cohort was 54.0 years, and 56.1% were male. Glomerulonephritis induced by nonautoimmune (55.3%) and autoimmune diseases (11.1%) followed by diabetic nephropathy (7.7%) was the most common primary diagnoses. The most frequent
Table 1. Baseline Characteristics of the Derivation and Validation Cohort Variables Male, n (%) Age (y), median (IQR) BMI (kg/m2), median (IQR) Primary kidney disease, n (%) Glomerulonephritis Systemic autoimmune diseases Diabetic nephropathy Urinary tract infection Hypertensive nephropathy Obstructive nephropathy Interstitial nephritis Others Comorbidities, n (%) Hypertension Diabetes mellitus Hyperuricemia Dyslipidemia Cardiovascular disease Heart failure Clinical parameters, median (IQR) eGFR (mL/min/1.73 m2) Hemoglobin (g/L) Albumin (g/L) Sodium (mmol/L)* Potassium (mmol/L)
Entire cohort (n 5 5,235)
Derivation (n 5 2,460)
Validation (n 5 2,775)
P-Value
2,939 (56.1) 54 (40-65) 24.2 (21.8-26.7)
1,335 (54.3) 53 (39-65) 24.1 (21.8-26.5)
1,604 (57.8) 55 (41-65) 24.2 (21.9-26.8)
2,896 (55.3) 582 (11.1)
1,335 (54.3) 280 (11.4)
1,561 (563.) 302 (10.9)
401 (7.7) 269 (5.1) 139 (2.7) 154 (2.9) 55 (1.1) 739 (14.1)
188 (7.6) 139 (5.7) 72 (2.9) 71 (2.9) 25 (1.0) 350 (14.2)
213 (7.7) 130 (4.7) 67 (2.4) 83 (53.9) 30 (1.1) 389 (14.0)
3,138 (59.9) 1,157 (22.1) 611 (11.7) 430 (8.2) 249 (4.8) 179 (3.4)
1,468 (59.7) 508 (20.7) 243 (9.9) 185 (7.5) 92 (3.7) 93 (3.8)
1,670 (60.2) 649 (23.4) 368 (13.3) 245 (8.8) 157 (5.7) 86 (3.1)
.710 .017 ,.001 .085 .001 .176
56.7 (33.9-91.3) 122.0 (108.0-136.0) 36.0 (30.0-40.0) 142.0 (140.0-144.0) 4.1 (3.8-4.4)
57.5 (33.8-92.6) 123.0 (108.0-136.0) 35.0 (29.0-39.0) 142.0 (140.0-144.0) 4.1 (3.8-4.4)
56.1 (33.9-90.6) 122.0 (108.0-136.0) 37.0 (30.0-40.0) 142.0 (140.0-143.0) 4.0 (3.8-4.3)
.236 .777 ,.001 ,.001 .022
BMI, body mass index; eGFR, estimated glomerular filtration rate; IQR, interquartile range. *Tested by Mann-Whitney U-test; other continuous variables were tested by unpaired t-test.
.010 .029 .992 .658
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HU ET AL
Table 2. Spot and 24-H Urinary Analysis of the Derivation and Validation Cohort Variables, Median (IQR) Spot urinary analysis Sodium (mmol/L) Potassium (mmol/L) Chloride (mmol/L) Calcium (mmol/L) Phosphorus (mmol/L) Magnesium (mmol/L) Albumin (mg/L)* Creatinine (mmol/L) Urea (mmol/L)* Uric acid (mmol/L) 24-H urinary analysis Total urine volume (L)* Sodium (mmol) Potassium (mmol) Chloride (mmol) Calcium (mmol)* Phosphorus (mmol) Magnesium (mmol)* Protein quantitation (g) Albumin (mg)* Creatinine (mmol) Urea (mmol)* Uric acid (mmol)
Entire Cohort (n 5 5,235)
Derivation Cohort (n 5 2,460)
Validation Cohort (n 5 2,775)
93.1 (66.0-120.5) 22.0 (15.6-31.4) 75.9 (51.3-103.3) 1.12 (0.47-2.31) 11.1 (7.2-17.9) 2.0 (1.4-2.8) 612.4 (127.1-1,782.5) 6,833.3 (4,616.0-10,841.0) 190.2 (136.5-270.2) 1,723.0 (1,146.5-2,637.6)
94.3 (67.9-121.6) 21.8 (15.5-31.3) 77.3 (52.4-104.4) 1.05 (0.45-2.27) 11.0 (7.1-17.4) 2.0 (1.4-2.8) 651.3 (128.9-1,830.0) 6,970.0 (4,588.0-11,131.3) 187.9 (134.4-259.6) 1,732.6 (1,139.1-2,610.7)
92.2 (64.2-119.2) 22.2 (15.7-31.6) 74.3 (50.6-102.7) 1.17 (0.49-2.34) 11.2 (7.2-18.5) 2.1 (1.4-2.9) 572.1 (124.6-1,773.2) 6,733.0 (4,654.0-10,717.0) 193.6 (138.9-276.9) 1,719.0 (1,152.9-2,646.0)
.039 .595 .039 .401 .435 .030 .132 .517 .004 .692
2.0 (1.5-2.5) 148.0 (103.8-201.0) 35.3 (26.6-46.6) 121.0 (83.0-170.0) 1.95 (0.96-3.52) 13.8 (9.7-18.9) 3.0 (2.2-4.0) 1.37 (0.52-3.42) 1,060.7 (275.2-2,906.6) 9,752.0 (7,635.0-12,386.0) 281.0 (215.4-360.3) 2,481.0 (1,830.5-3,292.5)
2.0 (1.5-2.5) 155.0 (111.0-205.0) 35.9 (27.4-47.4) 126.0 (88.0-174.0) 1.90 (0.90-3.51) 14.1 (9.9-18.8) 3.0 (2.2-4.0) 1.46 (0.51-3.67) 1,146.5 (313.8-3,133.7) 9,838.5 (7,834.0-12,485.8) 281.4 (220.5-359.8) 2,550.0 (1,894.8-3,326.3)
2.0 (1.5-2.5) 142.0 (98.0-197.0) 34.8 (25.8-45.8) 115.0 (78.0-166.0) 1.98 (1.01-3.53) 13.5 (9.6-18.9) 3.0 (2.2-4.1) 1.30 (0.52-3.28) 956.6 (257.5-2,732.6) 9,644.0 (7,470.0-12,266.0) 280.8 (212.3-361.2) 2,402.0 (1,760.0-3,257.0)
.001 ,.001 .017 .007 .411 .431 .092 .200 .001 .005 .638 .001
P-Value
IQR, interquartile range. *Tested by Mann-Whitney U-test; other continuous variables were tested by unpaired t-test.
comorbidity was hypertension (59.9%), diabetes mellitus (22.1%), and hyperuricemia (11.7%), while CVD and heart failure accounted for 4.8% and 3.4% of the included patients, respectively. The median (IQR) of eGFR at admission was 56.7 (33.9-91.3) mL/minute/1.73 m2. The validation cohort was older and had more percentages of men, diabetes mellitus, hyperuricemia, and CVD than the derivation cohort. The validation cohort had higher albumin and lower serum sodium and potassium levels than the derivation cohort. There were no significant differences in the primary diagnosis of kidney diseases, eGFR, and hemoglobin levels at admission.
The Predictive Equation of 24-Hour Sodium Excretion From Spot Urine Analysis As shown in Table 2, the median (IQR) of the spot urine sodium concentration in the entire cohort was 93.1 (66.0120.5) mmol/L. The total urine volume was 2.0 (1.5-2.5) L, and the 24-hour sodium excretion was 148.0 (103.8201.0) mmol/24 hours. Table 2 also showed other results of urine analysis and the comparisons of the derivation and validation cohort. In Table 3, we conducted 2 models of multiple linear regression with Enter method to generate the predictive equation. In Model 1, we only did not find the associations of age in the male and female group and spot urine urea in the female group with measured 24-hour urine sodium excretion. According to the result of Model 1, the predictive equations were generated as:
Estimated 24-hour sodium excretion for male 5 1.270 3 BMI 2 0.079 3 age 1 69.673 3 24-hour urine volume 1 0.681 3 spot urine sodium 1 0.050 3 spot urine urea 2 0.002 3 spot urine creatinine 2 57.755. Estimated 24-hour sodium excretion for female 5 2.660 3 BMI 2 0.015 3 age 1 66.520 3 24-hour urine volume 1 0.670 3 spot urine sodium 1 0.031 3 spot urine urea 2 0.002 3 spot urine creatinine 2 103.361. For the non-normal distribution with wide ranges, several variables were natural log(ln)-transformed in Model 2, including urine sodium, urea, and creatinine in spot urine and measured 24-hour sodium excretion. We found that most of the included dependent variables had significant associations with the independent variable except for the age in the male group. Therefore, we built other equations: Ln (estimated 24-hour sodium excretion for male) 5 2.917 2 0.001 3 age 1 0.012 3 BMI 1 0.392 3 24-hour urine volume 1 0.437 3 Ln (spot urine sodium) 1 0.078 3 Ln (spot urine urea) 2 0.145 3 Ln (spot urine creatinine). Ln (estimated 24-hour sodium excretion for female) 5 2.943 2 0.002 3 age 1 0.019 3 BMI 1 0.433 3 24-hour urine volume 1 0.378 3 Ln (spot urine sodium) 1 0.075 3 Ln (spot urine urea) 2 0.154 3 Ln (spot urine creatinine).
5
ESTIMATING URINARY SODIUM EXCRETION IN CKD Table 3. Generation of the Equation for Estimating 24-H Sodium Excretion From Spot Urine by Multiple Linear Regression Male Model Model 1
Model 2
Variables
B
Standard Error
Constant Age (y) Body mass index (kg/m2) 24-H urine volume (L) Spot urine sodium (mmol/L) Spot urine urea (mmol/L) Spot urine creatinine (mmol/L) Constant Age (y) Body mass index (kg/m2) 24-H urine volume (L) Ln (spot urine sodium) (mmol/L) Ln (spot urine urea) (mmol/L) Ln (spot urine creatinine) (mmol/L)
257.755 20.079 1.270 69.673 0.681 0.050 20.002 2.917 20.001 0.012 0.392 0.437 0.078 20.145
13.147 0.108 0.393 2.266 0.038 0.022 0.000 0.213 0.001 0.002 0.014 0.020 0.033 0.029
Finally, we compared the validation of the above equations using ICC coefficients and found that Model 2 equation had better performance to estimate 24-hour sodium excretion than Model 1, with the ICC (95% CI) 0.853 (0.841-0.863) versus 0.839 (0.827-0.851), respectively. Therefore, we only used Model 2 equation to compare the validation with other 3 previous equations in the following analysis. Because this equation was designed for the estimated 24-hour salt intakes in CKD patients, we named this equation as ‘‘CKDSALT’’ equation.
Assessment of Bias Between Predicted and Measured 24-Hour Sodium Excretion As illustrated in Tables 4 and 5, the degree of bias was significantly smaller with the CKDSALT (bias 5 1.25 mmol, 95% CI 2121.3 to 123.8, P . .05) and Tanaka (bias 5 20.003 mmol, 95% CI 2154.8 to 154.7, P . .05), compared with Kawasaki (bias 5 46.26 mmol, 95% CI 2114.4 to 207.0, P , .05) and INTERSALT (bias 5 220.44 mmol, 95% CI 2178.8 to 137.9, P , .05). Bland-Altman plots showed an overestimation of Kawasaki and underestimation of INTERSALT equation (Fig. 2). Although both Tanaka and CKDSALT equations showed small bias (P . .05), CKDSALT had a narrower CI than Tanaka. Pearson’s correlation coefficient between measured and estimated 24hour urinary sodium was the highest in CKDSALT (r 5 0.745) than Kawasaki, Tanaka, and INTERSALT (r 5 0.511, 0.482, and 0.443, respectively) (Table 6). Correlations Between Estimated and Measured Sodium Excretion As shown in Table 7, the estimated sodium excretions by Kawasaki, INTERSALT, and Tanaka were low-to-fair correlated with measured sodium excretion (0.4710.603). CKDSALT got the highest ICC (0.853, 95% CI 0.841-0.863) among the 4 equations, which reached the ‘‘good’’ degree. In Figure 3, the scatter plots showed that
Female t
P-Value
24.393 20.734 3.229 30.743 17.750 2.341 24.825 13.714 21.735 4.846 28.245 22.156 2.339 25.048
,.001 .463 .001 ,.001 ,.001 .019 ,.001 ,.001 .083 ,.001 ,.001 ,.001 .019 ,.001
B
Standard Error
t
P-Value
2103.361 20.015 2.660 66.520 0.671 0.031 20.002 2.943 20.002 0.019 0.433 0.378 0.075 20.154
12.804 0.106 0.437 2.333 0.040 0.024 0.000 0.228 0.001 0.003 0.016 0.020 0.036 0.032
28.073 20.145 6.086 28.511 16.925 1.299 23.285 12.932 22.496 6.202 26.445 18.525 2.067 24.789
,.001 .884 ,.001 ,.001 ,.001 .194 .001 ,.001 .013 ,.001 ,.001 ,.001 .039 ,.001
the CKDSALTalso got the highest R2 (0.5547) than Kawasaki (0.2615), Tanaka (0.2323), and INTERSALT (0.1963).
Validation of the Predicting Sodium Excretion in Subgroups To further assess the application of this novel predicting equation, the subjects were divided into several subgroups according to gender, age, BMI, eGFR, and 24-hour urine volume. The estimated sodium excretions by CKDSALT equation were more close to the measured sodium excretion (P . .05) than other 3 equations, in male and female, older and young, every level of BMI and eGFR. CKDSALT equation got the highest Pearson’s correlation coefficients (0.509-0.638) and ICC (0.574-0.767) compared with other 3 equations in every level of 24hour urine volume subgroups, although it overestimated sodium excretion when 24-hour urine volume was $3.0 L (bias 5 29.20 mmol).
Discussion In the present study, we retrospectively enrolled 5,235 hospitalized CKD patients at Stage 1-4 in a large, tertiary hospital in East China. Multiple linear regression analysis generated a predictive equation, named as ‘‘CKDSALT,’’ for estimating 24-hour sodium excretion from spot urinary analysis in derivation cohort, which was assessed in the validation cohort. When we measured sodium excretion as the gold standard, we compared its validation with other 3 equations: Kawasaki, INTERSALT, and Tanaka. The CKDSALT equation showed the lowest bias with limits of agreement in Bland-Altman plots, had the highest Pearson’s correlation and ICC coefficients among the 4r formulas. The CKDSALT equation also showed the best performance in various subgroups, including male and female, old and young, different levels of BMI, eGFR, and 24-hour urine volume.
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HU ET AL
Table 4. Medians and Interquartile Range of Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
Estimated, Median (IQR)
Measured, Median (IQR)
Kawasaki
INTERSALT
Tanaka
CKDSALT
142.0 (98.0-197.0)
196.0 (155.5-244.1)
136.2 (109.3-167.2)
156.0 (128.8-184.3)*
144.3 (110.0-189.8)*
155.0 (107.0-216.0) 124.0 (86.20-177.0)
211.9 (168.0-258.8) 181.6 (145.8-222.2)
162.4 (141.9-180.1) 108.3 (92.3-122.3)
159.3 (131.9-188.0) 151.5 (125.5-178.1)
159.4 (121.6-203.9)* 127.4 (98.4-163.6)*
133.0 (94.0-183.0) 146.0 (100.0-202.0)
201.5 (162.6-244.2) 196.3 (153.1-244.0)
136.6 (93.9-169.9) 136.1 (113.0-1365.8)
163.3 (138.3-192.1) 153.0 (126.5-181.5)
132.8 (103.5-177.2)* 148.3 (113.2-193.6)*
159.0 (113.0-217.0) 132.0 (90.3-185.0)
211.6 (169.2-256.1) 191.1 (148.6-235.6)
156.9 (124.1-180.8) 126.4 (104.2-155.6)
164.7 (138.1-193.0) 150.7 (124.6-178.2)
159.5 (125.3-205.9)* 135.2 (103.4-176.9)*
99.0 (65.5-150.0)
171.7 (130.4-204.0)
101.6 (83.5-123.0)*
134.6 (110.6-157.4)
108.6 (81.9-140.5)*
132.0 (92.0-187.0) 147.0 (98.5-211.0) 150.0 (106.0-207.0) 147.0 (95.0-196.0) 140.0 (100.0-192.0)
180.0 (145.1-222.3) 191.2 (150.5-235.5) 204.7 (163.8-253.5) 203.1 (153.7-244.0) 219.2 (179.1-263.4)
117.5 (101.6-136.2) 136.2 (106.8-164.8) 148.8 (112.5-174.2) 147.7 (117.2-173.2) 154.9 (125.5-174.0)*
148.0 (123.0-175.1)* 150.2 (123.5-178.4) 158.2 (131.9-187.6)* 157.7 (128.7-187.1)* 170.0 (145.0-195.1)
136.8 (104.9-173.9)* 149.6 (113.3-198.4)* 156.7 (115.8-202.5)* 146.2 (109.9-190.4)* 141.3 (109.3-187.3)*
234.0 (171.0-338.5) 163.0 (120.0-213.0) 115.0 (81.0-155.0) 56.0 (35.0-82.0)
233.7 (186.5-280.6) 204.7 (165.0-249.7) 185.5 (145.2-228.2) 168.4 (117.0-219.6)
155.3 (126.5-178.0) 138.5 (113.3-167.9) 129.7 (104.0-161.8) 123.7 (85.2-163.4)
174.7 (148.7-203.0) 161.6 (135.8-187.9) 147.3 (122.4-175.4) 138.4 (104.4-164.8)
264.3 (220.4-318.9) 168.1 (141.6-197.8)* 115.4 (94.6-137.4) 78.6 (58.6-99.4)
BMI, body mass index; eGFR, estimated glomerular filtration rate; IQR, interquartile range. *P . .05, when the estimated and measured sodium excretions were tested by paired t-test.
Table 5. Bias With Limits of Agreement Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Bias (LoA) Patients (n, %)
Kawasaki
INTERSALT
All (2,755, 100) 46.26 (2114.4 to 207.0) 220.44 (2178.8 to 137.9) Gender Male (1,604, 57.8) 43.79 (2136.7 to 224.2) 214.28 (2193.1 to 164.5) Female (1,171, 42.2) 49.65 (279.0 to 178.3) 228.87 (2152.0 to 94.3) Age (y) $65 (755, 27.2) 61.07 (291.9 to 21.4.0) 212.94 (2160.6 to 134.7) 18-64 (2,020, 72.8) 40.72 (2121.5 to 202.9) 223.24 (185.1-138.6) BMI (kg/m2) $25 (1,161, 41.8) 40.65 (2138.1 to 219.1) 224.39 (2203.8 to 155.0) 18.5-24.9 (1,480, 53.3) 48.98 (299.3 to 197.2) 218.40 (2161.7 to 124.9) ,18.5 (134, 4.8) 64.85 (248.83 to 178.5) 28.61 (2120.8 to 103.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 40.84 (2106.0 to 187.7) 227.85 (2175.3 to 119.6) 60-89 (561, 20.2) 29.97 (2146.6 to 206.6) 231.12 (2211.8 to 149.6) 45-59 (439, 15.8) 43.82 (2122.8 to 210.4) 222.78 (2180.6 to 135.1) 30-44 (517, 18.6) 47.09 (2114.9 to 209.1) 213.08 (2167.8 to 141.7) 15-29 (549, 19.8) 70.89 (272.5 to 214.2) 25.35 (2150.2 to 139.5) 24-H urine volume (L) $3.0 (340, 12.3) 225.15 (2269.6 to 219.3) 2113.90 (2350.2 to 122.5) 2.0-2.9 (1,152, 41.5) 39.39 (296.0 to 174.7) 232.62 (2158.5 to 93.3) 1.0-1.9 (1,140, 41.1) 66.79 (255.2 to 188.8) 9.60 (291.2 to 110.4) ,1.0 (143, 5.2) 107.20 (227.12 to 241.4) 59.35 (231.1 to 149.8)
Tanaka
CKDSALT
20.03 (2154.8 to 154.7)
1.25 (2121.3 to 123.8)
212.58 (2185.1 to 159.9) 17.17 (2101.3 to 135.6)
1.14 (2135.5 to 137.8) 1.41 (298.7 to 101.5)
19.36 (2122.7 to 161.4) 27.27 (2164.2 to 149.6)
1.87 (291.8 to 95.6) 1.02 (2130.7 to 132.8)
210.16 (2184.4 to 164.1) 5.50 (2134.0 to 145.0) 26.65 (275.8 to 129.1)
0.11 (2142.3 to 142.5) 1.89 (2105.0 to 108.8) 4.15 (292.2 to 100.5)
2.17 (2136.3 to 140.7) 20.29 (2125.9 to 125.3) 214.99 (2196.1 to 166.1) 0.93 (2164.1 to 165.9) 26.43 (2165.8 to 153.0) 3.26 (2113.8 to 120.3) 0.64 (2152.1 to 153.4) 1.20 (297.6 to 100.0) 16.69 (2119.1 to 152.5) 1.72 (285.0 to 88.5) 288.05 (2326.7 to 150.6) 29.20 (2201 to 259.4) 29.53 (2132.1 to 113.0) 21.79 (2109.7 to 106.1) 24.87 (275.34 to 125.1) 25.92 (290.0 to 78.2) 73.29 (224.5 to 171.0) 15.30 (258.0 to 88.6)
BMI, body mass index; eGFR, estimated glomerular filtration rate; LoA, limits of agreement.
ESTIMATING URINARY SODIUM EXCRETION IN CKD
7
Figure 2. Bland-Altman plots of measured 24-hour urine sodium excretion versus estimated 24-hour urine sodium excretion by Kawasaki (A), INTERSALT (B), Tanaka (C), and CKDSALT (D) equations. The difference between measured and estimated 24hour urine sodium excretion was all estimated values minus the measured values. The mid-dashed line was the mean bias, while the upper and lower dashed lines were the upper and lower limits, respectively.
The collection of 24-hour urine is considered to be the most reliable method to evaluate individual salt intake. However, the complete and accurate collection is always tricky and inconvenient, especially in large-scale studies. Spot urine specimens may be a useful, low-burden, lowcost alternative to 24-hour urine collections for estimation of population sodium intakes.10 The most popular predicting equations of sodium excretion from the spot urine analysis are Kawasaki,9 INTERSALT,10 and Tanaka,11 which have been fully evaluated in many studies, but with a poor agreement between estimated and observed sodium excretion. Polonia et al.15 analyzed 2,399 individuals aged 1896 years representatives of a western population and found that formulas produced mean biases were 21277 mg for Kawasaki, 569 mg for INTERSALT, and 11 mg for Tanaka, and ICCs were 0.303, 0.457, and 0.340, which met the ‘‘low’’ degree. Another study16 revealed that INTERSALT equations (bias 5 2165 mg for morning spot urine) might provide the least biased information about the population mean sodium intakes among US adults aged 18-39 years among the 4 formulas. These equations were also assessed in Chinese adults but were proved to underestimate 24-
hour sodium excretion.17 Furthermore, the validation of these equations in CKD patients has not been estimated. Therefore, a more accurate method is needed to evaluate sodium excretion from spot urine in the general Chinese population as well as CKD patients. Herein, we generated this CKDSALT equation to estimating 24-hour sodium excretion from spot urinary analysis. There were several reasons for the difficulty in predicting 24-hour sodium excretion from spot urine in CKD patients. A common problem exists in all predicting formulas using spot urine, that is, the urinary sodium excretion over 24 hours is not constant but instead varies around the intake, which leads to the inaccuracy of spot urine to estimate salt intake.18 Especially, predicting 24hour sodium excretion using spot urine in CKD patients may be more complex than the general population, because of the influences of the administrations of diuretics, different levels of eGFR, 24-hour urine volume, and changed the rhythm of sodium excretion. Another critical issue is that the level of urine creatinine, which has been used in many predicting formulas, has a strong association with the decreased renal function and its
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Table 6. Pearson Correlation Coefficients Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine Kawasaki Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
INTERSALT
Tanaka
CKDSALT
Coefficient
P-Value
Coefficient
P-Value
Coefficient
P-Value
Coefficient
P-Value
0.511
,.001
0.443
,.001
0.482
,.001
0.745
,.001
0.484 0.496
,.001 ,.001
0.417 0.420
,.001 ,.001
0.469 0.495
,.001 ,.001
0.746 0.691
,.001 ,.001
0.461 0.531
,.001 ,.001
0.398 0.469
,.001 ,.001
0.448 0.510
,.001 ,.001
0.810 0.726
,.001 ,.001
0.486 0.498 0.600
,.001 ,.001 ,.001
0.388 0.419 0.493
,.001 ,.001 ,.001
0.446 0.470 0.606
,.001 ,.001 ,.001
0.727 0.749 0.667
,.001 ,.001 ,.001
0.569 0.523 0.455 0.480 0.554
,.001 ,.001 ,.001 ,.001 ,.001
0.457 0.476 0.441 0.445 0.441
,.001 ,.001 ,.001 ,.001 ,.001
0.545 0.466 0.425 0.468 0.541
,.001 ,.001 ,.001 ,.001 ,.001
0.672 0.707 0.755 0.821 0.845
,.001 ,.001 ,.001 ,.001 ,.001
0.412 0.510 0.496 0.399
,.001 ,.001 ,.001 ,.001
0.436 0.434 0.467 0.452
,.001 ,.001 ,.001 ,.001
0.381 0.485 0.447 0.384
,.001 ,.001 ,.001 ,.001
0.638 0.633 0.652 0.509
,.001 ,.001 ,.001 ,.001
BMI, body mass index; eGFR, estimated glomerular filtration rate.
ranges may be fairly wide in CKD patients. Therefore, when conducting multiple linear regression, not only gender, age, spot urine sodium, and creatinine levels but
also 24-hour urine volume and spot urine urea were concluded as dependent variables to increase the accuracy of the predicting equation. That may be difficult and
Table 7. Intraclass Correlation Coefficients Between Measured and Estimated 24-H Urinary Sodium Excretion by 4 Equations Using Spot Urine ICC (95% CI) Patients (n, %) All (2,755, 100) Gender Male (1,604, 57.8) Female (1,171, 42.2) Age (y) $65 (755, 27.2) 18-64 (2,020, 72.8) BMI (kg/m2) $25 (1,161, 41.8) 18.5-24.9 (1,480, 53.3) ,18.5 (134, 4.8) eGFR (mL/min/1.73 m2) $90 (709, 25.5) 60-89 (561, 20.2) 45-59 (439, 15.8) 30-44 (517, 18.6) 15-29 (549, 19.8) 24-H urine volume (L) $3.0 (340, 12.3) 2.0-2.9 (1,152, 41.5) 1.0-1.9 (1,140, 41.1) ,1.0 (143, 5.2)
Kawasaki
INTERSALT
Tanaka
CKDSALT
0.603 (0.379-0.727)
0.471 (0.411-0.523)
0.553 (0.518-0.585)
0.853 (0.841-0.863)
0.591 (0.428-0.696) 0.552 (0.165-0.730)
0.374 (0.309-0.433) 0.373 (0.224-0.486)
0.520 (0.470-0.566) 0.590 (0.515-0.651)
0.854 (0.839-0.868) 0.811 (0.788-0.831)
0.509 (0.109-0.700) 0.635 (0.466-0.736)
0.503 (0.425-0.570) 0.457 (0.383-0.519)
0.524 (0.436-0.596) 0.567 (0.527-0.603)
0.892 (0.875-0.906) 0.840 (0.826-0.854)
0.596 (0.449-0.694) 0.578 (0.283-0.707) 0.572 (20.119 to 0.804)
0.391 (0.305-0.465) 0.456 (0.384-0.518) 0.537 (0.351-0.670)
0.501 (0.440-0.556) 0.556 (0.508-0.599) 0.650 (0.420-0.777)
0.842 (0.823-0.859) 0.853 (0.837-0.867) 0.778 (0.688-0.842)
0.668 (0.458-0.779) 0.628 (0.527-0.703) 0.555 (0.347-0.683) 0.572 (0.330-0.709) 0.556 (20.015 to 0.770)
0.435 (0.310-0.533) 0.455 (0.332-0.552) 0.473 (0.354-0.569) 0.489 (0.392-0.570) 0.490 (0.398-0.569)
0.624 (0.565-0.676) 0.489 (0.396-0.567) 0.493 (0.389-0.579) 0.545 (0.459-0.617) 0.603 (0.521-0.670)
0.795 (0.763-0.823) 0.827 (0.795-0.853) 0.856 (0.826-0.880) 0.896 (0.877-0.913) 0.913 (0.898-0.927)
0.544 (0.433-0.632) 0.611 (0.379-0.737) 0.471 (20.104 to 0.715) 0.238 (20.167 to 0.531)
0.226 (20.067 to 0.435) 0.463 (0.279-0.589) 0.599 (0.544-0.647) 0.383 (20.184 to 0.673)
0.302 (0.025-0.490) 0.589 (0.536-0.635) 0.565 (0.374-0.683) 0.283 (20.179 to 0.581)
0.767 (0.703-0.816) 0.714 (0.679-0.745) 0.710 (0.673-0.743) 0.574 (0.375-0.705)
BMI, body mass index; CI, confidence interval; eGFR, estimated glomerular filtration rate; ICC, intraclass correlation.
ESTIMATING URINARY SODIUM EXCRETION IN CKD
9
Figure 3. Scatter plots measured 24-hour urine sodium excretion versus estimated 24-hour urine sodium excretion by Kawasaki (A), INTERSALT (B), Tanaka (C), and CKDSALT (D) equations. The real line was the linear regression lines of the scatters in the spots. The dashed lines were the 95% confidence interval lines.
impractical to collect 24-hour urine specimens and record 24-hour urine volume in large-scale studies, and all the previous estimating equations did not contain the variable of 24-hour urine volume. In fact, it is unnecessary to provide 24-hour urine volume as a variable to estimate 24hour urinary sodium excretion from spot urine in general population but necessary for CKD patients. Furthermore, it is feasible to record each urine volume and calculate the sum of 24-hour urine volume to increase the accuracy of the CKDSALT equation in CKD patients, but the urine samples are not necessary to be collected, which is less costly and more convenient than collecting and testing 24-hour urine samples. Both urine urea and sodium excretions are associated with volume status and kidney injury, and the fractional excretion of sodium and urea has been used as indicators of acute kidney injury.19,20 Our present study also showed the association of urine urea and sodium excretion in the multiple linear regression. Therefore, we finally added the above 2 dependent variables in the conduction of CKDSALT equation. However, for the wide range of some variables and nonlinear relationship, several variables were natural logarithmic (ln) transformed in Model 2,
such as urine sodium, urea, and creatinine in spot urine, and measured 24-hour sodium excretion. We finally found that Model 2 equation had better performance to estimate 24-hour sodium excretion than Model 1 equation from crude multiple linear regression, with the ICC (95%CI) 0.853 (0.841-0.863) versus 0.839 (0.8270.851), respectively. Kawasaki equation got the least biased bias among the 3 methods in Chinese17 and diverse population studies.21 But in our study, the most significant bias was observed in the Kawasaki equation, which was derived based on data for the second-morning urine, and less accurate when estimating sodium excretion from the first voiding of urine. We used the first voiding of urine to evaluate the equations mainly because the patients are accustomed to collect the first-morning urine, and it is difficult to collect second-morning urine samples from CKD patients. Bland-Altman plots showed an overestimation of Kawasaki equation in CKD patients in our study (bias 5 46.26 mmol, 95% CI 2114.4 to 207.0, P , .05), which was consistent with the result with another survey to assess the validation of Kawasaki equation in CKD patients. It was suggested that the night-
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HU ET AL
time sodium excretion was higher than the daytime one in a CKD population,22 and so nocturnal polyuria due to natriuresis during the night may affect the estimation performed by Kawasaki equation in CKD patients. Using a single spot urine, INTERSALT equations may provide the least biased information about the population mean sodium intake among young US adults,16 but in the Chinese population, mean bias for the INTERSALT method was 22797 mg/day and was the highest of the 3 methods.17 We found that the INTERSALT equation underestimated the sodium excretion from BlandAltman plots in CKD patients (bias 5 220.44 mmol, 95% CI 2178.8 to 137.9, P , .05). The INTERSALT equation uses actual creatinine, rather than estimated 24-hour creatinine, which is expected to become an issue in older age groups with decreased renal function.23 Furthermore, it includes potassium intake, which may be inappropriate in populations with various dietary patterns and renal function. Except for the CKDSALT equation, Tanaka equation provided the least bias among these 3 equations (bias 5 20.003 mmol). It has been proved to be an accurate formula to estimate sodium excretion from the first-morning urine in CKD patients.24 However, the Pearson and ICC coefficients were only 0.482 and 0.553, and it still had high bias in the following patients: old (bias 5 19.36 mmol), male (underestimation), female (overestimation), BMI ,18.5 kg/m2 (bias 5 26.65 mmol), low eGFR (1529 mL/minute/1.73 m2, bias 5 16.69 mmol), and 24hour urine volume $3.0 L or ,2.0 L. In the present study, the CKDSALT equation had the best performance among the 4 formulas in all validation methods, including Bland-Altman plots, Pearson, and ICC coefficients, not only in CKD patients with normal renal function but also patients with decreased eGFR and 24-hour urine volume.
Study Limitations However, several limitations should be noted. First, this predictive equation needs to record each urine volume and calculate the sum of 24-hour urine volume, which may lead to more participant burden than just collecting spot urine samples. However, it is difficult to increase the accuracy from spot urine without 24-hour urine volume. It needs to be further explored whether the estimated 24-hour urine volume could be used in the equation. Second, even the measured 24-hour sodium excretion may not accurately evaluate individual salt intake in CKD patients with decreased renal function. Right now, there are no related reports pertaining to the association of salt intake with 24-hour urine sodium excretion when eGFR decreases. Third, the validation of the CKDSALTequation in patients without CKD
and international population needs to be thoroughly tested in future research.
Practical Application Spot urine method is acceptable for estimating 24hour urinary sodium excretion in Stage 1-4 CKD patients. The CKDSALT equation provides the least biased estimates of 24-hour sodium excretion not only in CKD patients with normal renal function but also patients with decreased eGFR and 24-hour urine volume.
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