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. 2019 Mar 25;20:104. doi: 10.1186/s12882-019-1292-3

Table 2.

Logistic regression analysis for the risk of hyperkalemia according to etiology of CKD

CKD subcohort Unadjusted Model 1 Model 2 Model 3
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
PKD (Reference) (Reference) (Reference) (Reference)
DN 9.52 (6.02–15.06) < 0.001 8.77 (4.74–16.24) < 0.001 4.65 (2.42–8.93) < 0.001 4.91 (2.54–9.50) < 0.001
HTN 3.42 (2.10–5.57) < 0.001 3.47 (2.07–5.83) < 0.001 2.54 (1.50–4.30) 0.001 2.57 (1.51–4.37) < 0.001
GN 2.79 (1.76–4.42) < 0.001 2.92 (1.82–4.66) < 0.001 1.70 (1.03–2.81) 0.038 1.82 (1.10–3.03) 0.02
Unclassified 4.57 (2.55–8.17) < 0.001 4.59 (2.44–8.65) < 0.001 2.86 (1.48–5.53) 0.002 2.95 (1.52–5.72) 0.001

Model 1: adjusted age, sex, history of DM, BMI, and SBP

Model 2: Model 1 + serum sodium and UPCR*

Model 3: Model 2 + use of RAAS blockade, diuretics, CCB, and beta blockers

*Data were log transformed

Abbreviations: CKD Chronic kidney disease, OR odds ratio, CI Confidence interval, PKD Polycystic kidney disease, DN Diabetic nephropathy, HTN Hypertensive nephrosclerosis, GN, glomerulonephritis; eGFR, estimated glomerular filtration rate; BMI Body mass index; SBP, systolic blood pressure; UPCR, urine protein-to-creatinine ratio; RAAS, renin-angiotensin-aldosterone system; CCB, calcium channel blocker