Association of Urinary Potassium Excretion with Blood Pressure Variability and Cardiovascular Outcomes in Patients with Pre-Dialysis Chronic Kidney Disease
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Data Collection
2.3. Determination of Visit-to-Visit BPV
2.4. Study Outcomes
2.5. Statistical Analysis
3. Results
3.1. Baseline Characteristics
3.2. Association between Spot Urine K+/Cr and BPV in Patients with Pre-Dialysis CKD
3.3. Association of Low Urine Potassium Excretion with Adverse CV Outcomes in Patients with Pre-Dialysis CKD
3.4. Sensitivity Analyses
3.5. Subgroup Analyses
4. Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Mezue, K.; Goyal, A.; Pressman, G.S.; Matthew, R.; Horrow, J.C.; Rangaswami, J. Blood pressure variability predicts adverse events and cardiovascular outcomes in SPRINT. J. Clin. Hypertens. 2018, 20, 1247–1252. [Google Scholar] [CrossRef][Green Version]
- Myasoedova, E.; Crowson, C.S.; Green, A.B.; Matteson, E.L.; Gabriel, S.E. Longterm blood pressure variability in patients with rheumatoid arthritis and its effect on cardiovascular events and all-cause mortality in RA: A population-based comparative cohort study. J. Rheumatol. 2014, 41, 1638–1644. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Choi, S.; Shin, J.; Choi, S.Y.; Sung, K.C.; Ihm, S.H.; Kim, K.I.; Kim, Y.M. Impact of Visit-to-Visit Variability in Systolic Blood Pressure on Cardiovascular Outcomes in Korean National Health Insurance Service-National Sample Cohort. Am. J. Hypertens. 2017, 30, 577–586. [Google Scholar] [CrossRef][Green Version]
- Li, Y.; Li, D.; Song, Y.; Gao, L.; Fan, F.; Wang, B.; Liang, M.; Wang, G.; Li, J.; Zhang, Y.; et al. Visit-to-visit variability in blood pressure and the development of chronic kidney disease in treated general hypertensive patients. Nephrol. Dial. Transplant. 2020, 35, 1739–1746. [Google Scholar] [CrossRef]
- Okada, H.; Fukui, M.; Tanaka, M.; Matsumoto, S.; Mineoka, Y.; Nakanishi, N.; Asano, M.; Yamazaki, M.; Hasegawa, G.; Nakamura, N. Visit-to-visit blood pressure variability is a novel risk factor for the development and progression of diabetic nephropathy in patients with type 2 diabetes. Diabetes Care 2013, 36, 1908–1912. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Noshad, S.; Mousavizadeh, M.; Mozafari, M.; Nakhjavani, M.; Esteghamati, A. Visit-to-visit blood pressure variability is related to albuminuria variability and progression in patients with type 2 diabetes. J. Hum. Hypertens. 2014, 28, 37–43. [Google Scholar] [CrossRef] [PubMed]
- Whittle, J.; Lynch, A.I.; Tanner, R.M.; Simpson, L.M.; Davis, B.R.; Rahman, M.; Whelton, P.K.; Oparil, S.; Muntner, P. Visit-to-Visit Variability of BP and CKD Outcomes: Results from the ALLHAT. Clin. J. Am. Soc. Nephrol. 2016, 11, 471–480. [Google Scholar] [CrossRef][Green Version]
- Mallamaci, F.; Tripepi, G.; D’Arrigo, G.; Borrelli, S.; Garofalo, C.; Stanzione, G.; Provenzano, M.; De Nicola, L.; Conte, G.; Minutolo, R.; et al. Blood Pressure Variability, Mortality, and Cardiovascular Outcomes in CKD Patients. Clin. J. Am. Soc. Nephrol. 2019, 14, 233–240. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Ruddy, M.C.; Arora, A.; Malka, E.S.; Bialy, G.B. Blood pressure variability and urinary electrolyte excretion in normotensive adults. Am. J. Hypertens. 1993, 6, 480–486. [Google Scholar] [CrossRef]
- Ozkayar, N.; Dede, F.; Ates, I.; Akyel, F.; Yildirim, T.; Altun, B. The relationship between dietary salt intake and ambulatory blood pressure variability in non-diabetic hypertensive patients. Nefrologia 2016, 36, 694–700. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Gu, D.; He, J.; Wu, X.; Duan, X.; Whelton, P.K. Effect of potassium supplementation on blood pressure in Chinese: A randomized, placebo-controlled trial. J. Hypertens. 2001, 19, 1325–1331. [Google Scholar] [CrossRef]
- He, F.J.; Marciniak, M.; Carney, C.; Markandu, N.D.; Anand, V.; Fraser, W.D.; Dalton, R.N.; Kaski, J.C.; MacGregor, G.A. Effects of potassium chloride and potassium bicarbonate on endothelial function, cardiovascular risk factors, and bone turnover in mild hypertensives. Hypertension 2010, 55, 681–688. [Google Scholar] [CrossRef]
- Cupisti, A.; Kovesdy, C.P.; D’Alessandro, C.; Kalantar-Zadeh, K. Dietary Approach to Recurrent or Chronic Hyperkalaemia in Patients with Decreased Kidney Function. Nutrients 2018, 10, 261. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Aaron, K.J.; Sanders, P.W. Role of dietary salt and potassium intake in cardiovascular health and disease: A review of the evidence. Mayo Clin. Proc. 2013, 88, 987–995. [Google Scholar] [CrossRef][Green Version]
- Kovesdy, C.P.; Matsushita, K.; Sang, Y.; Brunskill, N.J.; Carrero, J.J.; Chodick, G.; Hasegawa, T.; Heerspink, H.L.; Hirayama, A.; Landman, G.W.D.; et al. Serum potassium and adverse outcomes across the range of kidney function: A CKD Prognosis Consortium meta-analysis. Eur. Heart J. 2018, 39, 1535–1542. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Leonberg-Yoo, A.K.; Tighiouart, H.; Levey, A.S.; Beck, G.J.; Sarnak, M.J. Urine Potassium Excretion, Kidney Failure, and Mortality in CKD. Am. J. Kidney Dis. 2017, 69, 341–349. [Google Scholar] [CrossRef]
- Kim, H.W.; Park, J.T.; Yoo, T.H.; Lee, J.; Chung, W.; Lee, K.B.; Chae, D.W.; Ahn, C.; Kang, S.W.; Choi, K.H.; et al. Urinary Potassium Excretion and Progression of CKD. Clin. J. Am. Soc. Nephrol. 2019, 14, 330–340. [Google Scholar] [CrossRef][Green Version]
- O’Donnell, M.; Mente, A.; Rangarajan, S.; McQueen, M.J.; Wang, X.; Liu, L.; Yan, H.; Lee, S.F.; Mony, P.; Devanath, A.; et al. Urinary sodium and potassium excretion, mortality, and cardiovascular events. N. Engl. J. Med. 2014, 371, 612–623. [Google Scholar] [CrossRef][Green Version]
- Aburto, N.J.; Hanson, S.; Gutierrez, H.; Hooper, L.; Elliott, P.; Cappuccio, F.P. Effect of increased potassium intake on cardiovascular risk factors and disease: Systematic review and meta-analyses. BMJ 2013, 346, f1378. [Google Scholar] [CrossRef][Green Version]
- Cook, N.R.; Obarzanek, E.; Cutler, J.A.; Buring, J.E.; Rexrode, K.M.; Kumanyika, S.K.; Appel, L.J.; Whelton, P.K.; Trials of Hypertension Prevention Collaborative Research Group. Joint effects of sodium and potassium intake on subsequent cardiovascular disease: The Trials of Hypertension Prevention follow-up study. Arch. Intern. Med. 2009, 169, 32–40. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Whelton, P.K.; He, J.; Cutler, J.A.; Brancati, F.L.; Appel, L.J.; Follmann, D.; Klag, M.J. Effects of oral potassium on blood pressure. Meta-analysis of randomized controlled clinical trials. JAMA 1997, 277, 1624–1632. [Google Scholar] [CrossRef] [PubMed]
- Oh, K.-H.; Park, S.K.; Park, H.C.; Chin, H.J.; Chae, D.W.; Choi, K.H.; Han, S.H.; Yoo, T.H.; Lee, K.; Kim, Y.-S.; et al. KNOW-CKD (KoreaN cohort study for Outcome in patients With Chronic Kidney Disease): Design and methods. BMC Nephrol. 2014, 15, 80. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Levey, A.S.; Stevens, L.A.; Schmid, C.H.; Zhang, Y.L.; Castro, A.F., 3rd; Feldman, H.I.; Kusek, J.W.; Eggers, P.; Van Lente, F.; Greene, T.; et al. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 2009, 150, 604–612. [Google Scholar] [CrossRef] [PubMed]
- Chapter 1: Definition and classification of CKD. Kidney Int. Suppl. (2011) 2013, 3, 19–62. [CrossRef] [PubMed][Green Version]
- Fujita, T.; Ito, Y. Salt loads attenuate potassium-induced vasodilation of forearm vasculature in humans. Hypertension 1993, 21, 772–778. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Phillips, R.J.; Robinson, B.F. The dilator response to K+ is reduced in the forearm resistance vessels of men with primary hypertension. Clin. Sci. 1984, 66, 237–239. [Google Scholar] [CrossRef] [PubMed]
- Jhee, J.H.; Seo, J.; Lee, C.J.; Park, J.T.; Han, S.H.; Kang, S.W.; Park, S.; Yoo, T.H. Ambulatory blood pressure variability and risk of cardiovascular events, all-cause mortality, and progression of kidney disease. J. Hypertens. 2020, 38, 1712–1721. [Google Scholar] [CrossRef]
- Shimbo, D.; Shea, S.; McClelland, R.L.; Viera, A.J.; Mann, D.; Newman, J.; Lima, J.; Polak, J.F.; Psaty, B.M.; Muntner, P. Associations of aortic distensibility and arterial elasticity with long-term visit-to-visit blood pressure variability: The Multi-Ethnic Study of Atherosclerosis (MESA). Am. J. Hypertens. 2013, 26, 896–902. [Google Scholar] [CrossRef][Green Version]
- Nagai, M.; Hoshide, S.; Nishikawa, M.; Masahisa, S.; Kario, K. Visit-to-visit blood pressure variability in the elderly: Associations with cognitive impairment and carotid artery remodeling. Atherosclerosis 2014, 233, 19–26. [Google Scholar] [CrossRef]
- Diaz, K.M.; Veerabhadrappa, P.; Kashem, M.A.; Feairheller, D.L.; Sturgeon, K.M.; Williamson, S.T.; Crabbe, D.L.; Brown, M.D. Relationship of visit-to-visit and ambulatory blood pressure variability to vascular function in African Americans. Hypertens. Res. 2012, 35, 55–61. [Google Scholar] [CrossRef][Green Version]
- Tatasciore, A.; Zimarino, M.; Renda, G.; Zurro, M.; Soccio, M.; Prontera, C.; Emdin, M.; Flacco, M.; Schillaci, G.; De Caterina, R. Awake blood pressure variability, inflammatory markers and target organ damage in newly diagnosed hypertension. Hypertens. Res. 2008, 31, 2137–2146. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Sahranavard, T.; Carbone, F.; Montecucco, F.; Xu, S.; Al-Rasadi, K.; Jamialahmadi, T.; Sahebkar, A. The role of potassium in atherosclerosis. Eur. J. Clin. Investig. 2021, 51, e13454. [Google Scholar] [CrossRef] [PubMed]
- Ikizler, T.A.; Burrowes, J.D.; Byham-Gray, L.D.; Campbell, K.L.; Carrero, J.J.; Chan, W.; Fouque, D.; Friedman, A.N.; Ghaddar, S.; Goldstein-Fuchs, D.J.; et al. KDOQI Clinical Practice Guideline for Nutrition in CKD: 2020 Update. Am. J. Kidney Dis. 2020, 76, S1–S107. [Google Scholar] [CrossRef] [PubMed]
- Parati, G.; Ochoa, J.E.; Lombardi, C.; Bilo, G. Assessment and management of blood-pressure variability. Nat. Rev. Cardiol. 2013, 10, 143–155. [Google Scholar] [CrossRef]
- Wong, Y.K.; Chan, Y.H.; Hai, J.S.H.; Lau, K.K.; Tse, H.F. Predictive value of visit-to-visit blood pressure variability for cardiovascular events in patients with coronary artery disease with and without diabetes mellitus. Cardiovasc. Diabetol. 2021, 20, 88. [Google Scholar] [CrossRef]
- Eguchi, K.; Hoshide, S.; Schwartz, J.E.; Shimada, K.; Kario, K. Visit-to-visit and ambulatory blood pressure variability as predictors of incident cardiovascular events in patients with hypertension. Am. J. Hypertens. 2012, 25, 962–968. [Google Scholar] [CrossRef][Green Version]
- Hoshide, S. Clinical implication of visit-to-visit blood pressure variability. Hypertens. Res. 2018, 41, 993–999. [Google Scholar] [CrossRef]
- Mena, L.; Pintos, S.; Queipo, N.V.; Aizpúrua, J.A.; Maestre, G.; Sulbarán, T. A reliable index for the prognostic significance of blood pressure variability. J. Hypertens. 2005, 23, 505–511. [Google Scholar] [CrossRef][Green Version]
- Rothwell, P.M.; Howard, S.C.; Dolan, E.; O’Brien, E.; Dobson, J.E.; Dahlöf, B.; Sever, P.S.; Poulter, N.R. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet 2010, 375, 895–905. [Google Scholar] [CrossRef]
Spot Urine K+/Cr | p Value | ||||
---|---|---|---|---|---|
Q1 | Q2 | Q3 | Q4 | ||
Follow-up duration (year) | 5.150 ± 1.766 | 5.237 ± 1.724 | 5.180 ± 1.715 | 5.180 ± 1.709 | 0.892 |
Age (year) | 50.785 ± 13.566 | 53.880 ± 11.609 | 54.487 ± 11.157 | 55.282 ± 11.198 | <0.001 |
Male | 358 (77.0) | 330 (71.0) | 260 (55.8) | 172 (37.1) | <0.001 |
Charlson comorbidity index | 0.049 | ||||
0–3 | 316 (68.0) | 348 (74.8) | 353 (75.9) | 354 (76.3) | |
4–5 | 137 (29.5) | 110 (23.7) | 108 (23.2) | 105 (22.6) | |
≥6 | 12 (2.6) | 7 (1.5) | 5 (1.1) | 5 (1.1) | |
Primary renal disease | 0.218 | ||||
DM | 128 (27.5) | 106 (22.8) | 89 (19.1) | 105 (22.6) | |
HTN | 95 (20.4) | 102 (21.9) | 89 (19.1) | 92 (19.8) | |
GN | 154 (33.1) | 144 (31.0) | 164 (35.2) | 152 (32.8) | |
TID | 3 (0.6) | 4 (0.9) | 3 (0.6) | 4 (0.9) | |
PKD | 56 (12.0) | 81 (17.4) | 91 (19.5) | 84 (18.1) | |
Others | 29 (6.2) | 28 (6.0) | 30 (6.4) | 27 (5.8) | |
History of DM | 164 (35.3) | 144 (31.0) | 126 (27.0) | 156 (33.6) | 0.060 |
Medication | |||||
ACEi/ARBs | 399 (89.9) | 382 (89.7) | 415 (94.1) | 395 (90.2) | 0.068 |
Diuretics | 169 (38.1) | 121 (27.7) | 140 (31.7) | 131 (29.9) | 0.007 |
Number of antihypertensive drugs ≥ 3 | 165 (35.5) | 144 (31.0) | 135 (29.0) | 121 (26.1) | 0.016 |
BMI (kg/m2) | 24.635 ± 3.496 | 24.552 ± 3.402 | 24.555 ± 3.196 | 24.517 ± 3.403 | 0.960 |
WC (cm) | 87.461 ± 9.775 | 88.195 ± 10.083 | 86.987 ± 9.343 | 86.682 ± 9.475 | 0.111 |
SBP (mmHg) | 127.194 ± 16.501 | 127.860 ± 15.620 | 126.863 ± 14.774 | 126.170 ± 14.620 | 0.407 |
DBP (mmHg) | 76.428 ± 11.306 | 77.204 ± 11.317 | 77.485 ± 11.010 | 76.069 ± 9.963 | 0.165 |
Laboratory findings | |||||
Serum K+ (mEq/L) | 4.594 ± 0.682 | 4.547 ± 0.661 | 4.529 ± 0.631 | 4.555 ± 0.649 | 0.511 |
24 h urine K+ (mEq/day) | 42.027 ± 17.588 | 51.258 ± 43.036 | 56.539 ± 19.539 | 63.575 ± 23.118 | <0.001 |
Hemoglobin (g/dL) | 12.910 ± 2.116 | 13.138 ± 1.995 | 13.027 ± 1.947 | 12.835 ± 1.816 | 0.098 |
Albumin (g/dL) | 4.192 ± 0.388 | 4.199 ± 0.412 | 4.189 ± 0.370 | 4.245 ± 0.360 | 0.085 |
Total cholesterol (mg/dL) | 168.254 ± 39.284 | 172.600 ± 38.473 | 177.301 ± 37.889 | 177.711 ± 34.974 | <0.001 |
HDL-C (mg/dL) | 46.447 ± 15.762 | 48.837 ± 15.353 | 50.428 ± 14.616 | 52.714 ± 15.800 | <0.001 |
LDL-C (mg/dL) | 93.485 ± 31.973 | 94.838 ± 30.550 | 97.863 ± 28.925 | 99.501 ± 29.626 | 0.011 |
TG (mg/dL) | 163.899 ± 104.737 | 158.026 ± 96.706 | 155.236 ± 101.332 | 150.296 ± 91.559 | 0.213 |
Fasting glucose (mg/dL) | 112.513 ± 46.816 | 109.218 ± 36.002 | 107.429 ± 33.016 | 110.770 ± 35.886 | 0.217 |
25(OH) Vitamin D (ng/mL) | 17.190 ± 9.218 | 18.653 ± 9.408 | 18.806 ± 9.916 | 19.683 ± 10.427 | 0.017 |
hsCRP (mg/dL) | 0.600 [0.100, 1.860] | 0.780 [0.100, 1.800] | 0.550 [0.200, 1.400] | 0.500 [0.200, 1.600] | 0.004 |
Spot urine ACR (mg/gCr) | 349.855 [103.771, 1050.062] | 280.683 [57.545, 856.995] | 318.405 [71.818, 901.375] | 306.642 [48.397, 801.223] | 0.387 |
eGFR (mL/min/1.73 m2) | 48.048 ± 28.928 | 51.516 ± 27.605 | 56.207 ± 58.677 | 64.745 ± 31.792 | <0.001 |
CKD stages | <0.001 | ||||
Stage 1 | 49 (10.5) | 62 (13.3) | 73 (15.7) | 129 (27.8) | |
Stage 2 | 78 (16.8) | 84 (18.1) | 107 (23.0) | 103 (22.2) | |
Stage 3a | 73 (15.7) | 87 (18.7) | 85 (18.2) | 77 (16.6) | |
Stage 3b | 116 (24.9) | 118 (25.4) | 107 (23.0) | 81 (17.5) | |
Stage 4 | 129 (27.7) | 96 (20.6) | 78 (16.7) | 62 (13.4) | |
Stage 5 | 20 (4.3) | 18 (3.9) | 16 (3.4) | 12 (2.6) |
Unadjusted | Adjusted | |||
---|---|---|---|---|
Coefficients (95% CIs) | p Value | Coefficients (95% CIs) | p Value | |
Low urine K+/Cr | ||||
ARV | 1.260 (0.545, 1.975) | 0.001 | 1.163 (0.424, 1.901) | 0.002 |
SD | 0.511 (−0.071, 1.094) | 0.085 | 0.431 (−0.176, 1.037) | 0.164 |
CoV | 0.005 (0.000, 0.009) | 0.057 | 0.004 (−0.001, 0.009) | 0.138 |
High urine K+/Cr | ||||
ARV | −0.130 (−0.857, 0.598) | 0.727 | 0.127 (−0.634, 0.887) | 0.744 |
SD | 0.261 (−0.330, 0.853) | 0.386 | 0.468 (−0.154, 1.091) | 0.140 |
CoV | 0.002 (−0.002, 0.007) | 0.299 | 0.004 (−0.001, 0.009) | 0.101 |
Low urine Na+/Cr | ||||
ARV | −0.139 (−0.871, 0.593) | 0.710 | 0.169 (−0.547, 0.884) | 0.644 |
SD | −0.257 (−0.851, 0.338) | 0.397 | −0.018 (−0.605, 0.568) | 0.951 |
CoV | −0.001 (0.006, 0.004) | 0.611 | 0.000 (−0.005, 0.005) | 0.978 |
High urine Na+/Cr | ||||
ARV | 0.105 (−0.614, 0.824) | 0.774 | −0.190 (−0.904, 0.524) | 0.602 |
SD | 0.127 (−0.457, 0.711) | 0.669 | −0.116 (−0.701, 0.469) | 0.698 |
CoV | 0.000 (−0.005, 0.004) | 0.915 | −0.001 (−0.006, 0.004) | 0.659 |
Low urine Na+/K+ | ||||
ARV | −0.176 (−0.906, 0.553) | 0.635 | 0.222 (−0.483, 0.927) | 0.536 |
SD | 0.060 (−0.533, 0.652) | 0.844 | 0.343 (−0.235, 0.920) | 0.245 |
CoV | 0.001 (−0.004, 0.006) | 0.654 | 0.003 (−0.002, 0.007) | 0.263 |
High urine Na+/K+ | ||||
ARV | 0.873 (0.158, 1.588) | 0.017 | 0.275 (−0.426, 0.976) | 0.442 |
SD | 0.545 (−0.036, 1.126) | 0.066 | 0.146 (−0.429, 0.720) | 0.618 |
CoV | 0.003 (−0.002, 0.008) | 0.220 | 0.001 (−0.004, 0.005) | 0.722 |
Spot Urine K+/Cr | Cases, n (%) | Unadjusted | Adjusted | |||
---|---|---|---|---|---|---|
HR (95% CIs) | p Value | HR (95% CIs) | p Value | |||
eMACE | Q1 | 36 (7.7) | 1.899 (1.114, 3.239) | 0.018 | 2.502 (1.162, 5.387) | 0.019 |
Q2 | 27 (5.8) | 1.727 (0.992, 3.006) | 0.053 | 1.120 (0.512, 2.451) | 0.777 | |
Q3 | 29 (6.2) | 1.393 (0.812, 2.389) | 0.228 | 1.590 (0.777, 3.252) | 0.204 | |
Q4 | 40 (8.6) | Reference | Reference | |||
All-cause mortality | Q1 | 17 (3.7) | 0.733 (0.321, 1.672) | 0.460 | 0.604 (0.240, 1.519) | 0.284 |
Q2 | 20 (4.30) | 1.406 (0.694, 2.846) | 0.344 | 1.222 (0.560, 2.668) | 0.615 | |
Q3 | 17(3.6) | 1.037 (0.487, 2.207) | 0.925 | 0.953 (0.433, 2.099) | 0.905 | |
Q4 | 17 (3.7) | Reference | Reference |
Spot Urine K+/Cr | Cases, n (%) | Unadjusted | Adjusted | |||
---|---|---|---|---|---|---|
HR (95% CIs) | p for Interaction | HR (95% CIs) | p for Interaction | |||
Age < 60 years | Q1 | 14 (4.3) | 4.162 (1.523, 11.373) | 0.672 | 0.502 (0.202, 12.797) | 0.780 |
Q2 | 11 (3.5) | 3.800 (1.334, 10.826) | 5.681 (0.378, 85.486) | |||
Q3 | 16 (5.3) | 4.155 (1.492, 11.570) | 2.271 (0.203, 25.433) | |||
Q4 | 13 (4.6) | Reference | Reference | |||
Age ≥ 60 years | Q1 | 22 (15.4) | 1.221 (0.631, 2.365) | 4.737 (1.453, 15.445) | ||
Q2 | 16 (10.3) | 1.132 (0.557, 2.301) | 2.351 (0.488, 11.334) | |||
Q3 | 13 (7.9) | 0.707 (0.330, 1.514) | 1.645 (0.511, 5.294) | |||
Q4 | 27 (14.9) | Reference | Reference | |||
Diuretics (−) | Q1 | 17 (6.2) | 1.414 (0.684, 2.924) | 0.618 | 1.152 (0.302, 4.386) | 0.896 |
Q2 | 21 (6.6) | 1.631 (0.830, 3.206) | 1.439 (0.432, 4.797) | |||
Q3 | 14 (4.7) | 2.015 (0.962, 4.222) | 5.175 (1.726, 15.518) | |||
Q4 | 22 (7.2) | Reference | Reference | |||
Diuretics (+) | Q1 | 17 (10.1) | 2.873 (1.264, 6.531) | 2.936 (0.465, 18.526) | ||
Q2 | 6 (5.0) | 1.933 (0.666, 5.604) | 0.521 (0.066, 4.077) | |||
Q3 | 13 (9.3) | 0.939 (0.409, 2.158) | 1.445 (0.132, 15.812) | |||
Q4 | 16 (12.2) | Reference | Reference | |||
eGFR ≥ 45 mL/min/1.73 m2 | Q1 | 10 (5.0) | 1.627 (0.678, 3.906) | 0.194 | 2.374 (0.245, 23.011) | 0.535 |
Q2 | 8 (3.4) | 2.030 (0.837, 4.922) | 7.845 (0.368, 167.103) | |||
Q3 | 18 (6.8) | 1.184 (0.575, 2.436) | 8.476 (1.301, 55.226) | |||
Q4 | 22 (7.1) | Reference | Reference | |||
eGFR < 45 mL/min/1.73 m2 | Q1 | 26 (9.8) | 1.958 (0.971, 3.950) | 2.494 (0.841, 7.393) | ||
Q2 | 18 (8.2) | 1.603 (0.767, 3.352) | 1.201 (0.364, 3.961) | |||
Q3 | 11 (5.5) | 1.991 (0.819, 4.840) | 2.600 (0.467, 14.478) | |||
Q4 | 18 (11.6) | Reference | Reference | |||
Spot urine ACR < 300 mg/gCr | Q1 | 17 (7.9) | 2.416 (1.035, 5.644) | 0.913 | 0.421 (0.067, 2.636) | 0.593 |
Q2 | 13 (5.4) | 2.378 (1.053, 5.370) | 2.595 (0.112, 59.942) | |||
Q3 | 10 (4.4) | 1.505 (0.642, 3.531) | 6.738 (1.044, 43.490) | |||
Q4 | 20 (8.8) | Reference | Reference | |||
Spot urine ACR ≥ 300 mg/gCr | Q1 | 19 (7.6) | 1.542 (0.769, 3.093) | 3.888 (1.208, 12.512) | ||
Q2 | 14 (6.2) | 1.339 (0.616, 2.913) | 1.371 (0.313, 6.008) | |||
Q3 | 19 (7.9) | 1.182 (0.573, 2.437) | 2.936 (0.793, 10.867) | |||
Q4 | 20 (8.4) | Reference | Reference |
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Suh, S.H.; Song, S.H.; Oh, T.R.; Choi, H.S.; Kim, C.S.; Bae, E.H.; Oh, K.-H.; Lee, J.; Han, S.H.; Kim, Y.H.; Chae, D.-W.; Ma, S.K.; Kim, S.W.; on behalf of the Korean Cohort Study for Outcomes in Patients with Chronic Kidney Disease Investigators. Association of Urinary Potassium Excretion with Blood Pressure Variability and Cardiovascular Outcomes in Patients with Pre-Dialysis Chronic Kidney Disease. Nutrients 2021, 13, 4443. https://doi.org/10.3390/nu13124443
Suh SH, Song SH, Oh TR, Choi HS, Kim CS, Bae EH, Oh K-H, Lee J, Han SH, Kim YH, Chae D-W, Ma SK, Kim SW, on behalf of the Korean Cohort Study for Outcomes in Patients with Chronic Kidney Disease Investigators. Association of Urinary Potassium Excretion with Blood Pressure Variability and Cardiovascular Outcomes in Patients with Pre-Dialysis Chronic Kidney Disease. Nutrients. 2021; 13(12):4443. https://doi.org/10.3390/nu13124443
Chicago/Turabian StyleSuh, Sang Heon, Su Hyun Song, Tae Ryom Oh, Hong Sang Choi, Chang Seong Kim, Eun Hui Bae, Kook-Hwan Oh, Joongyub Lee, Seung Hyeok Han, Yeong Hoon Kim, Dong-Wan Chae, Seong Kwon Ma, Soo Wan Kim, and on behalf of the Korean Cohort Study for Outcomes in Patients with Chronic Kidney Disease (KNOW-CKD) Investigators. 2021. "Association of Urinary Potassium Excretion with Blood Pressure Variability and Cardiovascular Outcomes in Patients with Pre-Dialysis Chronic Kidney Disease" Nutrients 13, no. 12: 4443. https://doi.org/10.3390/nu13124443