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http://www.kidney-international.org & 2014 International Society of Nephrology

see commentary on page 1077

The relationship between estimated sodium and potassium excretion and subsequent renal outcomes Andrew Smyth1,2, Daniela Dunkler2,3, Peggy Gao2, Koon K. Teo2, Salim Yusuf2, Martin J. O’Donnell1,2, Johannes F.E. Mann2,4 and Catherine M. Clase5 on behalf of the ONTARGET and TRANSCEND investigators 1

Health Research Board Clinical Research Facility Galway, National University of Ireland, Galway, Ireland; 2Population Health Research Institute, McMaster University, Hamilton, ON, Canada; 3Department of Nephrology, University of Erlangen-Nu¨rnberg and Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria; 4Department of Nephrology, University of Erlangen-Nu¨rnberg and Munich General Hospitals, Munich, Germany and 5Department of Nephrology, McMaster University, Hamilton, ON, Canada

Patients are often advised to reduce sodium and potassium intake, but supporting evidence is limited. To help provide such evidence we estimated 24 h urinary sodium and potassium excretion in 28,879 participants at high cardiovascular risk who were followed for a mean of 4.5 years in the ONTARGET and TRANSCEND trials. The primary outcome was eGFR decline of 30% or more or chronic dialysis. Secondary outcomes were eGFR decline of 40% or more or chronic dialysis, doubling of serum creatinine or chronic dialysis, an over 5%/year loss of eGFR, progression of albuminuria, and hyperkalemia. Multinomial logit regression with multivariable fractional polynomials, adjusted for confounders, determined the association between urinary sodium and potassium excretion and renal outcomes, with death as a competing risk. The primary outcome occurred in 2,052 (7.6%) patients. There was no significant association between sodium and any renal outcome (primary outcome odds ratio 0.99; 95% CI 0.89–1.09 for highest [median 6.2 g/day] vs. lowest third [median 3.3 g/day]). Higher potassium was associated with lower odds of all renal outcomes (primary outcome odds ratio 0.74; 95% CI 0.67–0.82 for highest [median 2.7 g/day] vs. lowest third [median 1.7 g/day], except hyperkalemia nonsignificant. Thus, urinary potassium, but not sodium, excretion predicted clinically important renal outcomes. Our findings do not support routine low sodium and potassium diets for prevention of renal outcomes in people with vascular disease with or without chronic kidney disease. Kidney International (2014) 86, 1205–1212; doi:10.1038/ki.2014.214; published online 11 June 2014

Correspondence: Andrew Smyth, Population Health Research Institute, McMaster University, 237 Barton Street East, Hamilton, ON, Canada L8L 2X2. E-mail: [email protected] Received 15 December 2013; revised 10 April 2014; accepted 8 May 2014; published online 11 June 2014 Kidney International (2014) 86, 1205–1212

INTRODUCTION

Hypertension is a risk factor for chronic kidney disease (CKD); prevention and treatment of hypertension are key targets in the prevention and reduction of progression of CKD. Dietary sodium and potassium intake may affect the course of kidney disease directly, or through effects on blood pressure. The 2012 Kidney Disease Improving Global Outcomes guideline recommends that patients with CKD eat o2 g of sodium per day,1 similar to recommendations for the prevention of cardiovascular disease in the general population.2 Because the relationship between sodium intake and renal outcomes is assumed to be linear, guidelines do not include a lower limit for suggested sodium intake. However, for cardiovascular outcomes, recent evidence suggests a J-shaped relationship with sodium intake.3,4 For potassium intake, the Kidney Disease Outcomes Quality Initiative recommends 44 g/day for patients with stage 1 and stage 2 CKD and o2.4 g/day for those with stage 3 and stage 4 CKD.5 Kidney Disease Improving Global Outcomes suggest restricting potassium intake only in patients with hyperkalemia (to o3.0 g/day).1 This study is a post hoc analysis of the ongoing telmisartan alone and in combination with ramipril global endpoint trial (ONTARGET6) and telmistartan randomized assessment study in ACE intolerant subjects with cardiovascular disease (TRANSCEND7) studies. They included patients at high cardiovascular risk, most of whom were treated with blockers of the renin–angiotensin–aldosterone system (RAAS). We tested the hypothesis that low urinary sodium is associated with improved renal outcomes. As higher potassium has been associated with reductions in blood pressure and cardiovascular disease,8 we examined the association between urinary potassium excretion and renal outcomes. RESULTS

Of the 31,546 participants in the ONTARGET and TRANSCEND studies, 28,879 (91.5%) were included, with no 1205

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A Smyth et al.: Sodium, potassium, and renal outcomes

clinically meaningful differences between included and excluded participants (Supplementary Table S1 online). The mean age was 66.5 (7.2) years, mean estimated glomerular filtration rate (eGFR) was 68.4 (17.6) ml/min per 1.73 m2, mean sodium excretion was 4.76 (1.55) g/day, and the mean potassium excretion was 2.18 (0.54) g/day. Patients with higher estimated sodium excretion had higher eGFR, urine albumincreatinine ratio (UACR), and systolic blood pressure (Table 1). Patients with higher estimated potassium excretion also had higher eGFR and UACR (Table 2). During follow-up, the mean decline in eGFR was 1.3 (standard deviation 15.6) ml/min per 1.73 m2 and median increase in UACR was 0.6 mg/g (IQR  2.1 – 6.4). Outcome data were available for 27,077 participants (93.8%) for creatinine-based outcomes and hyperkalemia, and for 25,891 (89.7%) participants for progression of proteinuria (Supplementary Table S1 online). The primary renal outcome occurred in 2052 (7.6%) (Table 3).

proteinuria, or hyperkalemia on adjusted models (Figure 1). Similarly, there was no association with eGFR decline of X40% or CD, doubling of creatinine or CD, but the association with rapid progression of renal disease was U-shaped (P ¼ 0.0334); participants with the lowest and highest sodium excretion were at an increased odds of rapid progression of renal disease (Supplementary Figure S1 online). Compared with the third of patients with the lowest sodium excretion (median 3.3 g/day), there was no association between moderate (median 4.7 g/day) or high (median 6.1 g/day) sodium excretion and the primary outcome (odds ratio (OR) and 95% confidence interval (CI) 0.98 (0.92–1.04) and 0.99 (95% CI 0.89–1.09), respectively) (Table 3). There was no association beween sodium excretion and secondary outcomes (eGFR decline of X40% or CD, rapid progression of renal disease, doubling of creatinine or CD, progression of proteinuria, and hyperkalemia). Potassium

Sodium

There was no association between estimated 24-h urinary sodium excretion and the primary outcome, progression of

There were almost linear, strong, statistically significant associations between estimated 24-h urinary potassium excretion and the primary outcome and progression of

Table 1 | Baseline patient characteristics by estimated sodium excretion Estimated sodium excretion Overall (n ¼ 28,879)

o2 g/day (n ¼ 818)

4.76 (1.55) 66.5 (7.2) 1.06 (0.28) 68.4(17.6)

1.55 (0.35) 67.6 (7.6) 1.08 (0.31) 64.6 (18.3)

3.24 67.0 1.07 67.2

(0.53) (7.4) (0.28) (17.8)

(12.7%) (54.9%) (22.6%) (8.4%) (1.4%)

80 (10.0%) 388 (48.7%) 215 (27.0%) 89 (11.2%) 25 (3.1%)

947 4367 1898 794 127

5.33 (24.21)

UACR categories, n (%) Normoalbuminuria Microalbuminuria Macroalbuminuria Diabetes, n (%)

Sodium excretion, mean (s.d.), g/d Age, mean (s.d.), years Creatinine, mean (s.d.), mg/dl eGFR, mean (s.d.), ml/min per 1.73 m2 eGFR categories, n (%) X90 ml/min per 1.73 m2 60–90 ml/min per 1.73 m2 45–60 ml/min per 1.73 m2 30–45 ml/min per 1.73 m2 o30 ml/min per 1.73 m2 UACR, mean (s.d.), mg/g

Body mass index, mean (s.d.) Obesity, n (%)

6-8 g/day (n ¼ 4706)

48 g/day (n ¼ 847)

P-value

4.93 (0.56) 66.5 (7.2) 1.06 (0.27) 68.7 (17.4)

6.71 65.8 1.06 69.8

(0.53) (7.0) (0.27) (17.5)

8.97 65.4 1.06 69.7

(0.70) (6.8) (0.29) (17.9)

o0.0001 o0.0001 0.2225 o0.0001

(11.6%) (53.7%) (23.3%) (9.8%) (1.6%)

1757 (12.7%) 7706 (55.7%) 3106 (22.5%) 1,074 (7.8%) 183 (1.3%)

676 2562 998 342 41

(14.6%) (55.5%) (21.6%) (7.4%) (0.9%)

124 458 163 64 14

(15.1%) (55.7%) (19.8%) (7.8%) (1.7%)

o0.0001 0.0002 0.0014 o0.0001 o0.0001

3.90 (10.83)

3.85 (14.48)

4.72 (20.16)

7.81 (30.06)

17.73 (76.07)

o0.0001

24,197 (83.9%) 3622 (12.6%) 1020 (3.5%)

654 (80.5%) 139 (17.1%) 19 (2.3%)

7123 (85.5%) 974 (11.7%) 234 (2.8%)

12,106 (85.6%) 1587 (11.2%) 454 (3.2%)

3746 (79.6%) 723 (15.4%) 236 (5.0%)

568 (67.3%) 199 (23.6%) 77 (9.1%)

o0.0001 o0.0001 o0.0001

10,717 (37.1%)

320 (39.1%)

2691 (32.2%)

5128 (36.2%)

2141 (45.5%)

437 (51.6%)

o0.0001

28.1 (4.6) 8537 (29.6%)

27.3 (4.6) 216 (26.4%)

27.5 (4.5) 2080 (24.9%)

28.1 (4.4) 4045 (28.6%)

29.1 (4.7) 1812 (38.7%)

30.2 (5.1) 384 (45.7%)

o0.0001 o0.0001

438 712 550 335

3172 7575 5456 2568

952 4288 3062 1366

178 748 584 367

(21.0%) (88.3%) (68.9%) (43.3%)

o0.0001 0.0008 0.0103 o0.0001

137.60 (18.64) 356 (42.0%)

o0.0001 o0.0001

3584 15,481 6380 2363 390

Women, n (%) RAAS blockade (study drug), n (%) Open-label ACEi /AIIA, n (%) Diuretics, n (%)

8503 26,160 18,715 8298

(29.4%) (90.6%) (64.8%) (28.7%)

Systolic blood pressure Week 6, mean (s.d.), mm Hg Mean on-study 4140 mm Hg, n (%)

134.50 (18.80) 9890 (34.3%)

(53.5%) (87.0%) (67.2%) (41.0%)

134.74 (19.46) 287 (35.1%)

2-3.99 g/day (n ¼ 8353)

4-5.99 g/day (n ¼ 14,155)

(38.0%) (90.7%) (65.3%) (30.7%)

3763 (26.6%) 12,837 (90.7%) 9603 (64.0%) 3662 (25.9%)

134.09 (19.06) 2794 (33.5%)

134.31 (18.66) 4731 (33.4%)

(20.2%) (91.1%) (65.1%) (29.0%)

135.19 (18.58) 1722 (36.6%)

Abbreviations: BMI, body mass index; eGFR, estimated glomerular filtration rate calculated by the CKD-EPI equation;27 s.d., standard deviation; UACR, urine albumincreatinine ratio. Microalbuminuria defined as UACR430 mg/g; macroalbuminuria defined as UACR 4300 mg/g; obesity defined as BMI X30 kg/m2; renin–angiotensin system (RAAS) blockade was defined as assignment to telmisartan, ramipril, or both; diuretic use included loop, thiazide, or thiazide-like diuretics; Mean on-study systolic blood pressure for this tabulation was calculated as the mean of all systolic blood pressures recorded during the study (including those occurring after outcomes).

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Table 2 | Baseline patient characteristics by estimated potassium excretion Estimated potassium excretion Overall (n ¼ 28,879)

o1.5 g/day (n ¼ 2194)

1.5–1.99 g/day (n ¼ 9710)

2.0–2.49 g/day (n ¼ 9876)

2.5–3.0 g/day (n ¼ 4850)

43.0 g/day (n ¼ 2249)

P-value

2.18 (0.54) 66.5 (7.2) 1.06 (0.28) 68.4 (17.6)

1.36 (0.12) 66.9 (7.4) 1.07 (0.31) 65.2 (18.2)

1.77 (0.14) 66.9 (7.3) 1.07 (0.28) 66.6 (17.7)

2.24 (0.14) 66.9 (7.2) 1.07 (0.27) 68.2 (17.3)

2.72 (0.14) 65.8 (7.0) 1.05 (0.26) 71.0 (17.1)

3.38 (0.37) 64.5 (6.6) 1.03 (0.25) 73.9 (16.9)

o0.0001 o0.0001 o0.0001 o0.0001

(12.7%) (54.9%) (22.6%) (8.4%) (1.4%)

221 (10.3%) 1062 (49.4%) 576 (26.8%) 237 (11.0%) 55 (2.6%)

1043 5006 2341 921 155

(11.0%) (52.9%) (24.7%) (9.7%) (1.6%)

1175 (12.2%) 5353 (55.4%) 2218 (23.0%) 803 (8.3%) 114 (1.2%)

718 2762 897 292 52

427 1298 348 110 14

(19.4%) (59.1%) (15.8%) (5.0%) (0.6%)

o0.0001 o0.0001 o0.0001 o0.0001 o0.0001

5.33 (24.21)

2.52 (10.53)

4.15 (18.86)

5.53 (21.02)

6.62 (26.55)

9.49 (48.87)

o0.0001

UACR categories, n (%) Normoalbuminuria Microalbuminuria Macroalbuminuria

24,197 (83.9%) 3622 (12.6%) 1020 (3.5%)

1969 (89.8%) 185 (8.4%) 36 (1.6%)

8408 (86.7%) 1004 (10.4%) 281 (2.9%)

8143 (82.6%) 1336 (13.5%) 385 (3.9%)

3928 (81.0%) 715 (14.8%) 204 (4.2%)

1749 (77.9%) 382 (17.0%) 114 (5.1%)

o0.0001 o0.0001 o0.0001

Diabetes, n (%)

10,717 (37.1%)

696 (31.7%)

3560 (36.7%)

3672 (37.2%)

1860 (38.4%)

929 (41.3%)

o0.0001

28.1 (4.6) 8537 (29.6%)

26.2 (4.4) 380 (17.3%)

27.5 (4.4) 2411 (24.9%)

28.3 (4.4) 2965 (30.1%)

29.0 (4.6) 1802 (37.3%)

29.9 (4.8) 979 (43.8%)

o0.0001 o0.0001

3645 8701 6293 2944

(37.5%) (89.6%) (64.8%) (30.3%)

2518 (25.5%) 9013 (91.3%) 6354 (64.3%) 2768 (28.0%)

888 4460 3164 1236

296 2077 1482 660

(13.2%) (92.4%) (65.9%) (29.3%)

o0.0001 o0.0001 0.6304 o0.0001

134.77 (18.74) 3442 (35.5%)

134.55 (18.66) 3383 (34.3%)

134.15 (18.70) 733 (32.6%)

0.2438 0.0109

Potassium excretion, mean (s.d.), g/d Age, mean (s.d.), years Creatinine, mean (s.d.), mg/dl eGFR, mean (s.d.), ml/min per 1.73 m2 eGFR categories, n (%) X90 ml/min per 1.73 m2 60–90 ml/min per 1.73 m2 45–60 ml/min per 1.73 m2 30–45 ml/min per 1.73 m2 o30 ml/min per 1.73 m2

3584 15,481 6380 2363 390

UACR, mean (s.d.), mg/g

Body mass index, mean (s.d.) Obesity, n (%) Women, n (%) RAAS blockade (study drug), n (%) Open-label ACEi /AIIA, n (%) Diuretics, n (%)

8503 26,160 18,715 8298

(29.4%) (90.6%) (64.8%) (28.7%)

1156 (52.7%) 1909 (87.0%) 1422 (64.8%) 690 (31.4%)

Systolic blood pressure Baseline, mean (s.d.), mm Hg Mean on-study 4140 mm Hg, n (%)

134.50 (18.80) 9890 (34.3%)

133.93 (19.22) 722 (32.9%)

(15.2%) (58.5%) (19.0%) (6.2%) (1.1%)

(18.3%) (92.0%) (65.3%) (25.5%)

134.27 (19.04) 1610 (33.2%)

Abbreviations: BMI, body mass index; eGFR, estimated glomerular filtration rate calculated by the CKD-EPI equation;27 s.d., standard deviation; UACR, urine albumincreatinine ratio. Microalbuminuria defined as UACR430 mg/g; macroalbuminuria defined as UACR4300 mg/g; obesity defined as BMIX30 kg/m2; renin–angiotensin system blockade was defined as assignment to telmisartan, ramipril, or both; diuretics included loop, thiazide, or thiazide-like diuretics; mean on-study systolic blood pressure for this tabulation was calculated as the mean of all systolic blood pressures recorded during the study (including those occurring after outcomes).

Table 3 | Effect of sodium excretion on renal outcomes Outcome

eGFR decline of X30% or chronic dialysis eGFR decline of X40% or chronic dialysis Rapid progression of renal disease Doubling of creatinine or chronic dialysis Progression of proteinuria Hyperkalemia

No. of outcomes (%)

2052 941 3717 302 2471 768

(7.6%) (3.5%) (13.7%) (1.1%) (9.5%) (2.7%)

Adjusteda

Unadjusted

Reference Low (median 3.3 g)

Moderate (median 4.7 g)

High (median 6.2 g)

Moderate (median 4.7 g)

High (median 6.2 g)

1.0 1.0 1.0 1.0 1.0 1.0

0.96 (0.91–1.01) 0.94 (0.87–1.02) 0.96 (0.92–1.00) 0.96 (0.84–1.09) 0.95 (0.91–0.99) 1.08 (0.99–1.19)

1.00 (0.92–1.09) 0.98 (0.87–1.11) 1.00 (0.94–1.07) 1.00 (0.81–1.24) 0.98 (0.91–1.05) 1.14 (0.99–1.32)

0.98 0.95 0.97 0.96 0.96 1.08

0.99 0.93 1.00 0.94 0.92 1.09

(0.92–1.04) (0.87–1.03) (0.93–1.02) (0.84–1.11) (0.91–1.02) (0.98–1.19)

(0.89–1.09) (0.80–1.07) (0.93–1.07) (0.75–1.19) (0.84–1.01) (0.93–1.28)

Abbreviations: BMI, body mass index; eGFR, estimated glomerular filtration rate; RAAS, renin–angiotensin–aldosterone system; UACR, urine albumin-creatinine ratio. eGFR decline defined as a change from 6-week creatinine/GFR measurement; rapid progression of renal disease defined as decline of 5% per year in eGFR from 6-week measurement; progression of proteinuria defined as change from normal to microalbuminuria (UACR430 mg/g) or macroalbuminuria (UACR4300 mg/g) or from microalbuminuria to macroalbuminuria; hyperkalemia defined as a serum potassium 45.5 mmol/l. a Adjusted for known risk factors including age, sex, ethnicity, six-week eGFR, run-in UACR, diabetes, BMI, smoking, use of on-study RAAS blockade, diuretic use, and potassium excretion.

proteinuria on adjusted models (Figure 2); participants with higher potassium excretion had significantly lower odds of the outcomes. Similarly, there were significant associations with eGFR decline of X40% or CD, rapid progression of renal disease, and doubling of creatinine or CD (Supplementary Kidney International (2014) 86, 1205–1212

Figure S2 online). The association with hyperkalemia was nonsignificant, but there was a tendency toward increased odds of hyperkalemia with higher potassium excretion (Figure 2). Compared with the lowest potassium excretion (median 1.7 g), both moderate (median 2.1 g/day) and high (median 1207

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a

Relative odds

7.53%

2.25 2

7.49% 7.82%

1.5 1

Primary outcome 8.01%

7.82%

2.25 2

7.01%

1.5 1 0.5 0.25

b

3 4 5 6 7 8 9 Estimated 24-h urine sodium (g/day)

10

Progression of proteinuria

Relative odds

9.82%

2.25 2

9.23% 10.16%

1.5 1

300 200 100 0 1

2

3 4 5 6 7 8 9 Estimated 24-h urine sodium (g/day)

c

10

Frequency

0.5 0.25

2.25 2

Relative odds

2.86% 3.06%

1.5 1

100 75 50 25 0 2

6 7 8 9 3 4 5 Estimated 24-h urine sodium (g/day)

10

Frequency

0.5 0.25

1

Figure 1 | Association of estimated 24-h urinary sodium excretion and relative odds (solid line) with 95% confidence interval (dotted line) of select renal outcomes. (a) Primary outcome defined as eGFR decline X30% or CD, observed in 7.6% (n ¼ 2052) (P ¼ 0.3659). (b) Proteinuria defined as progression of proteinuria, observed in 9.5% (n ¼ 2471) (P ¼ 0.1203). (c) Hyperkalemia, defined as serum potassium measurement of 45.5 mmol/l at 2 years or at the end of study, observed in 2.7% (n ¼ 768) (P ¼ 0.209). All plots are based on the model for sodium and potassium excretion (adjusted for age, sex, ethnicity, six-week eGFR, run-in UACR, diabetes, BMI, smoking, diuretic use, and use of on-study RAAS blockade). Histograms present the distribution of sodium excretion in participants with the outcome of interest. The vertical lines show tertiles, and the reported percentages within each tertile indicate the percentage of participants experiencing the outcome of interest.

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b

Frequency

4

Progression of proteinuria 10.19% 10.1%

2.25 2

8.92%

1.5 1 0.5 0.25

200 100 0 3 3.5 1.5 2 2.5 Estimated 24-h urine potassium (g/day)

c

Hyperkalemia 2.63%

3 3.5 1.5 2 2.5 Estimated 24-h urine potassium (g/day)

Frequency

2

0

4

Hyperkalemia 2.72%

2.6%

2.25 2

3.23%

Relative odds

1

100

Relative odds

200 100 0

Frequency

0.5 0.25

1.5 1 0.5 0.25

50 25 0 3.5 1.5 2 2.5 3 Estimated 24-h urine potassium (g/day)

4

Frequency

Primary outcome

Relative odds

a

A Smyth et al.: Sodium, potassium, and renal outcomes

Figure 2 | Association of estimated 24-h urinary potassium excretion and relative odds (solid line) with 95% confidence interval (dotted line) of select renal outcomes. (a) Primary outcome defined as eGFR decline X30% or CD, observed in 7.6% (n ¼ 2052) (Po0.0001). (b) Proteinuria defined as progression of proteinuria, observed in 9.5% (n ¼ 2471) (Po0.0001). (c) Hyperkalemia, defined as serum potassium measurement of 45.5 mmol/l at two years or at the end of study, observed in 2.7% (n ¼ 768) (P ¼ 0.0649). All plots are based on the model for sodium and potassium excretion (adjusted for age, sex, ethnicity, 6-week eGFR, run-in UACR, diabetes, BMI, smoking, diuretic use, and use of on-study RAAS blockade). Histograms present the distribution of potassium excretion in participants with the outcome of interest. The vertical lines show tertiles and the reported percentages within each tertile indicate the percentage of participants experiencing the outcome of interest.

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Table 4 | Effect of potassium excretion on renal outcomes Outcome

eGFR decline of X30% or chronic dialysis eGFR decline of X40% or chronic dialysis Rapid progression of renal disease Doubling of creatinine or chronic dialysis Progression of proteinuria Hyperkalemia

No. of outcomes (%)

2052 941 3717 302 2471 768

(7.6%) (3.3%) (13.7%) (1.1%) (9.5%) (2.7%)

Adjusteda

Unadjusted

Reference Low (median 1.7 g)

Moderate (median 1.7 g)

High (median 2.7 g)

Moderate (median 2.1 g)

High (median 2.7 g)

1.0 1.0 1.0 1.0 1.0 1.0

0.94 (0.91–0.98) 0.97 (0.91–1.02) 0.96 (0.93–0.98) 0.95 (0.87–1.05) 0.93 (0.90–0.96) 1.06 (1.00–1.12)

0.87 (0.80–0.95) 0.92 (0.81–1.04) 0.90 (0.84–0.96) 0.89 (0.72–1.11) 0.84 (0.78–0.91) 1.14 (1.00–1.30)

0.88 0.91 0.89 0.88 0.89 1.07

0.74 0.81 0.77 0.75 0.76 1.16

(0.84–0.92) (0.85–0.97) (0.86–0.92) (0.79–0.99) (0.85–0.93) (1.00–1.14)

(0.67–0.82) (0.69–0.94) (0.71–0.84) (0.58–0.98) (0.69–0.84) (0.99–1.36)

Abbreviations: BMI, body mass index; eGFR, estimated glomerular filtration rate; RAAS, renin–angiotensin–aldosterone system; UACR, urine albumin-creatinine ratio. eGFR decline defined as a change from 6-week creatinine/GFR measurement; rapid progression of renal disease defined as decline of 5% per year in eGFR from 6-week measurement; progression of proteinuria defined as change from normal to microalbuminuria (UACR 430 mg/g) or macroalbuminuria (UACR 4300 mg/g) or from microalbuminuria to macroalbuminuria; hyperkalemia defined as a serum potassium 45.5 mmol/l. a Adjusted for known risk factors including age, sex, ethnicity, six-week eGFR, run-in UACR, diabetes, BMI, smoking, use of on-study RAAS blockade, diuretic use, and sodium excretion.

2.7 g/day) potassium excretions were associated with a dosedependent reduction in the odds of the primary outcome (OR 0.88 (95% CI 0.84–0.92) and 0.74 (95% CI 0.67–0.82), respectively) (Table 4). The magnitude of the reduction in the odds was similar for eGFR decline of X40% or CD, rapid progression of renal disease, doubling of creatinine or CD, and progression of proteinuria. Both moderate and high potassium excretions were associated with a tendency toward an increase in the odds of hyperkalemia (OR 1.07 (95% CI 1.00–1.14) and 1.16 (95% CI 0.99–1.36), respectively). Sensitivity analyses

When all-cause hospitalization was included as a competing risk event, higher sodium excretion was associated with reduced odds of progression of proteinuria (OR 0.86 (95% CI 0.76–0.97)). There were no other important changes in findings (Supplementary Table S2 online). Subgroup analyses

There were no interactions or subgroup effects identified in the analysis of sodium excretion (Supplementary Figure S3 online), with the exception of a reduction in the odds of progression of proteinuria with higher sodium excretion in patients without diabetes (P ¼ 0.04). For potassium excretion (Supplementary Figure S4 online), there was a loss of statistical significance of the reduced odds of the primary outcome in patients with eGFR p45 ml/min per 1.73 m2 (P ¼ 0.01) and macroalbuminuria (P ¼ 0.02), and an increase in the odds of hyperkalemia was seen in patients without diabetes (P ¼ 0.03) and normal baseline UACR (P ¼ 0.02). There were no other significant effects in the analysis of potassium excretion. DISCUSSION

We found no support for our hypothesis that lower sodium excretion is associated with reduced renal risk. Sodium excretion varied widely and there were a substantial number of outcomes that included changes of eGFR, chronic dialysis Kidney International (2014) 86, 1205–1212

(CD), and proteinuria. A new observation is the robust protective effect of higher potassium excretion. There was a nonsignificant tendency toward a J-shaped association between sodium excretion and the primary outcome (eGFR decline of X30% or CD), and a significant U-shaped association with rapid progression of renal disease (P ¼ 0.0334). These results are consistent with previous studies that report increased risk with high intake (44.6 g/day).9–11 A possible increase in risk below 4 g/day is consistent with our systematic review,12 and with findings in patients with type 1 diabetes,3 and it does not support current recommendations of low intakes (o2.3 g/day, with no lower limit suggested).1 A US-based cross-sectional study (n ¼ 13,917) observed an increased prevalence of low GFR in those with sodium intake o2.1 g compared with higher sodium intakes,13 and we observed the same effect cross-sectionally at baseline, perhaps owing to confounding by indication. However, unlike that study, which reported that higher sodium intake was associated with lower odds of CKD, we did not observe a protective association between higher sodium and any outcomes. This may be due to differences in population characteristics (high cardivascular risk patients vs. general population) and study design (sodium may have differential effects on GFR in acute [detected cross-sectionally] and chronic [detected on followup] settings). We did not find an association between sodium excretion and progression of proteinuria. The acute antiproteinuric action of renin system inhibition is greater in those with a negative sodium balance,14 and there are trial data showing that the risk of kidney outcomes decreases with lower sodium intake in patients with proteinuric nephropathies on RAAS blockade.9 We may have missed an effect of sodium excretion on proteinuria, as most participants were on RAAS blockade at enrollment and the effect of RAAS inhibition on proteinuria is acute. The association of potassium excretion with reduction in odds of renal outcomes was strong, dose dependent, and consistent across outcomes. The OR for the primary outcome 1209

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varied substantially with potassium excretion from approximately 1.2 to 0.5, with narrow CIs. No previous large longitudinal study has examined the association between potassium intake and prospectively recorded renal outcomes. A cross-sectional study (n ¼ 13,917) reported a protective association between high potassium intake (43.3 g/day) and CKD,13 which is confirmed here (Table 2). Three small shortterm controlled trials reported that the addition of approximately 60 mmol/day of potassium chloride compared with placebo resulted in either no change15,16 or a decrease in serum creatinine.17 However, subgroup analysis showed loss of statistical significance in those with eGFR o45 ml/min per 1.73 m2 (P ¼ 0.01) or macroalbuminuria (P ¼ 0.02) (Supplementary Figure S4 online), suggesting that the protective association may not extend to those with advanced CKD. How might a high potassium excretion reduce progression of kidney disease? ONTARGET previously reported that a diet rich in fruits and vegetables is associated with better renal outcomes.18 Obviously such a diet will lead to higher potassium excretion. Thus, the potassium effect observed here may entirely be due to a healthy diet, mediated by dietary antioxidants that have anti-inflammatory activity, which may decrease kidney disease progression.19A high potassium intake may increase plasma potassium, which is reported to reduce renal vascular resistance and increase glomerular filtration rate.20 Another possibility is that higher potassium excretion itself is renoprotective, mediated by upregulation of renal kinins, such as kallikrein. In a proteinoverload rat model of kidney injury, high potassium intake increased renal kallikrein expression and decreased blood pressure, profibrotic tissue growth factor beta, and tubulointerstitial fibrosis; the last three effects were blunted by kinin antagonism.21 Finally, confounding by indication may explain findings, namely patients with more severe renal disease or worse prognosis may have limited potassium intake. Several facts speak against this last interpretation. The number of participants with clearly elevated serum creatinine, which prompts physicians to advise reduced potassium intake, was low in these trials; furthermore, participants with elevated serum potassium were excluded during run-in. A high potassium intake has the obvious concern of promoting hyperkalemia and cardiac arrhythmia. There was a tendency toward increased odds of hyperkalemia with higher potassium excretion. Subgroup analyses showed that association was similar at all levels of GFR (P ¼ 0.36), but those without diabetes (P ¼ 0.03) and with normal UACR appeared to be at increased risk (P ¼ 0.02) (Supplementary Figure S4 online). However, these findings have borderline statistical significance, have questionable biological plausibility, and are limited by multiple testing. Previous analyses of ONTARGET reported that the risk of hyperkalemia increases with lower GFR and higher UACR.22 A prospective cohort study of patients with CKD (n ¼ 840) associated both low and high serum potassium with risk of death and endstage renal disease.23 1210

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This study suggests that a diet associated with a high potassium intake may benefit the kidney, and a previous analysis exhibited cardiovascular benefits.4 It may therefore be important not to restrict potassium intake prematurely in people with CKD. The effect of potassium intake on kidney outcomes in other large longitudinal trials, including studies of people with lower GFR than studied here, will be of great interest, in particular as our subgroup analysis suggested a loss of the protective association with higher potassium excretion in those with eGFR o45 ml/min per 1.73 m2. Interventional studies of a healthy, high-potassium diet or potassium supplementation to prevent kidney outcomes would not be straightforward, but the absolute risk of severe hyperkalemia (46.5 mmol/l) in our participants on RAAS blockade was low (0.02 per 100 patient-years in the monotherapy groups in ONTARGET). Estimating electrolyte excretion from a single morning urine has limitations. Seven or more urine collections or dietary recalls may be necessary to estimate usual intake.24 The method we used to estimate sodium and potassium intake is a simple, objective method, previously validated for use in patients with25 and without CKD.26 Although lacking in precision for individuals, the method provides a measure of intake feasible for large-scale studies,24 and a previous study reported overall consistency with other studies that used 24-hour urinary collections, the criterion standard.4 Although we did not identify a strong effect for sodium excretion on kidney outcomes, potassium excretion, assessed with the same methodology, yielded robust results. We recognize some additional limitations. First, our cohort includes only participants at high cardiovascular risk but relatively low renal risk who were recruited into a randomized controlled trial. As a result, our outcomes are predominantly derived from changes of eGFR and proteinuria, which are surrogate outcomes. Although serum creatinine and eGFR measurements were performed locally, the outcomes are based on proportional changes from the 6-week value, making it unlikely that our results are affected by the method. We found no interactions between sodium excretion and other variables; however, we acknowledge that even in studies as large as this, such analyses may be statistically underpowered. Finally, we are unable to generalize to patients with more severe CKD, for example, to patients with very low GFR or nephrotic-range proteinuria. The strengths of this study include the use of a central laboratory for urinary electrolytes, international representation, high completion of follow-up, completeness of data, and the large number of patients followed up prospectively for a mean of 56 months, accumulating over 120,000 person-years. This observational analysis can generate hypotheses but is not the optimal study design to inform treatment. However, our data do not support recommendations to reduce sodium intake substantially below 3 g/d in order to protect the kidney—recommendations largely based on observational data. Even more important, our data speak against a general recommendation of a low-potassium diet in patients with Kidney International (2014) 86, 1205–1212

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A Smyth et al.: Sodium, potassium, and renal outcomes

CKD and certainly not in those with serum potassium values well within the normal range. Randomized trials of healthy diets, or sodium or potassium intake, in patients with CKD (in particular with lower eGFR), powered for kidney outcomes, are needed. Feasibility of a diet trial was recently exemplified for cardiovascular outcomes,27 and the strong circumstantial evidence for potassium-rich diet from this and other studies18 supports this approach. METHODS Population We studied participants in the ONTARGET6 (n ¼ 25,620) and TRANSCEND7 (n ¼ 5926) studies who had data available on urinary sodium and urinary potassium, excluding those lost to follow-up and those with missing or implausible serum creatinine (p35 umol/l). These trials enrolled participants aged X55 years with established vascular disease or diabetes with end-organ damage. ONTARGET participants were randomized to telmisartan 80 mg/day, ramipril 10 mg/day, or their combination, and TRANSCEND participants were randomized to telmisartan 80 mg/ day or placebo. Median follow-up was 56 months. Laboratory analysis Serum creatinine and potassium were measured locally before runin, six weeks after randomization, after two years, and at the end of study. We eGFR using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) CKD-EPI formula.28 UACR was measured centrally, as previously described.29 Morning fasting urine samples were shipped using STP 250 ambient specimen boxes and stored at the Hamilton Research Laboratory or a regional laboratory in Beijing, China. Both laboratories measured sodium and potassium identically with indirect potentiometry using the Beckman Coulter Synchron Clinical System. Urinary creatinine was determined with a Roche Hitachi 917 analyzer using an enzymatic colorimetric assay. We used the Kawasaki formula26 to estimate 24-h urinary sodium and potassium excretion from a single fasting morning urine sample, taken at the pre-run-in visit. This approach has been used to estimate sodium intake in previous studies of healthy controls26 and patients taking antihypertensive therapies.30 Although this formula was developed and validated in Asians, comparison of estimated values with 24-h collections showed Pearson correlations of 0.55 (Po0.001) for sodium and 0.43 (Po0.001) for potassium.31 It has also been validated in patients with CKD.25 Estimates for sodium and potassium excretion were truncated at 10 g/day and 5 g/day, respectively. Outcomes The primary renal outcome was decline in eGFR of X30% or CD. Secondary outcomes were a decline in eGFR of X40% or CD, rapid progression of renal disease, doubling of serum creatinine or CD, progression of proteinuria, and hyperkalemia. Rapid progression of renal disease was defined as a decline of 5%/year in eGFR, with the rate of change defined by regression within participant. Creatinine-based outcomes were defined as change from six weeks after randomization, to minimize changes due to the hemodynamic effects of initiation of RAAS blockade. CD was defined as dialysis occurring for 2 months or longer. Progression of proteinuria was defined as progression from normal (UACRo30 mg/g) to microalbuminuria (UACR X30 to o300 mg/g) or macroalbuminuria Kidney International (2014) 86, 1205–1212

(UACR X300 mg/g) or from microalbuminuria to macroalbuminuria, based on change from UACR measured at run-in. Hyperkalemia was defined as a serum potassium of 45.5 mmol/l on laboratory measurement either at two years or at the end of study. For creatinine-based outcomes and hyperkalemia, we included only participants with a six-week laboratory measurement and one of the following: outcome event, death, or laboratory measurement at the end of follow-up. For the outcome progression of proteinuria, we included only participants with a run-in UACR measurement that was o300 mg/g and one of the following: outcome event, death, or laboratory measurement at the end of follow-up. To maximize power, we adopted a conservative approach and used the 2-year value for participants with missing information at the end of study. Statistical analysis Continuous data are presented as mean with standard deviation or median with interquartile range, and categorical data as frequencies and percentages. Baseline differences were compared using w2 test and analysis of variance. All P values are two-sided and Pp0.05 was considered statistically significant, without adjustment for multiple comparisons. We used multinomial logit regression modeling with the multivariable fractional polynomial algorithm with a significance level of 0.05 for the continuous variables sodium or potassium excretion, age, BMI, six-week eGFR, and run-in UACR, to allow nonlinear effects, and the categorical variables sex, ethnicity, diabetes, smoking, diuretic use (loop, thiazide, and thiazide-like diuretics but information on potassium sparing diuretics was not collected), and RAAS blockade to identify OR and 95% CI for the effects of estimated daily sodium and potassium excretion on each renal outcomes and the competing risk of death. We chose multinomial logit regression over proportional subdistribution hazard models for competing risk data, according to Fine and Gray, because the exact dates of change in eGFR, proteinuria, or hyperkalemia are not known, and because rapid progression is calculated over the entire study period and does not occur at a particular time. We also analyzed sodium and potassium excretion divided into thirds of intake. Potential confounders or explanatory variables were prespecified and forced into every model. To assess whether the effects of sodium and potassium differed according to patients’ baseline characteristics, according to prespecified hypotheses, we added two-way interaction terms, one at a time, to the base model. We used a false discovery rate of 5% to adjust for multiple testing. We used the interaction terms as the formal test for subgroup effects, but for presentation we also analyzed the effect within subgroups defined categorically. Sensitivity analyses were based on the hypothesis that renal outcomes might be consequences of other adverse outcomes, and that renal outcomes occuring in these settings would be less likely predicted by baseline dietary habits. First, we included hospitalization for any reason with death in the competing risk for each outcome. Second, we included myocardial infarction, stroke, or hospitalization for heart failure with death in the competing risk. Third, we included only myocardial infarction or hospitalization for heart failure with death in the competing risk. DISCLOSURE

MJOD, JFEM, KKT, and SY received consulting and lecture fees and research grants from Boehringer Ingelheim and from other companies manufacturing angiotensin receptor blockers. The remaining authors declared no competing interests. 1211

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ACKNOWLEDGMENTS

This analysis was supported by the Population Health Research Institute and the European Commission (SysKid, grant HEALTH–F2–2009–241544). The trials were supported by Boehringer Ingelheim. AS was supported by the Health Research Board and Health Services Executive (Ireland) under the National SpR Academic Fellowship Program 2011. Funding agencies had no role in the design, conduct, or analysis of the study, nor in the decision to submit the manuscript for publication. The results of this manuscript were presented, in abstract format, at the American Society of Nephrology Kidney Week 2013, Atlanta, GA (FR-PO272, Friday November 8th 2013). SUPPLEMENTARY MATERIAL Supplementary material is linked to the online version of the paper at http://www.nature.com/ki

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Kidney International (2014) 86, 1205–1212

The relationship between estimated sodium and potassium excretion and subsequent renal outcomes.

Patients are often advised to reduce sodium and potassium intake, but supporting evidence is limited. To help provide such evidence we estimated 24 h ...
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