Prevalence,Recurrence, Risk Factors and Adverse Clinical Outcomes of Hyperkalemia in Maintenance Hemodialysis Patients

Prevalence,Recurrence, Risk Factors and Adverse Clinical Outcomes of Hyperkalemia in Maintenance Hemodialysis Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence,Recurrence, Risk Factors and Adverse Clinical Outcomes of Hyperkalemia in Maintenance Hemodialysis Patients Weitang Liao, Minhong Luo, Lili Zhang, Hongbo Ye, Ni Xu, Yinyang Liang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5952868/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Oct, 2025 Read the published version in BMC Nephrology → Version 1 posted 8 You are reading this latest preprint version Abstract Background The study aimed to investigate the prevalence, recurrence, and risk factors associated with serum potassium levels in patients undergoing maintenance hemodialysis (MHD), as well as to explore the correlation between hyperkalemia (HK) and adverse clinical outcomes. Methods A cohort of 499 patients was enrolled in this study. Comprehensive data collection was performed,encompassing serum potassium levels, laboratory parameters, comorbid conditions, and medication regimens. The primary endpoints included major adverse cardiovascular events (MACEs), defined as a composite of hospitalizations for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, congestive heart failure, transient ischemic attack, or stroke. Secondary outcomes comprised all-cause hospitalizations. Both univariate and multivariate logistic regression analyses were conducted to identify risk factors associated with HK and its recurrence in MHD patients. Furthermore, the study evaluated the potential association between elevated serum potassium levels and the risk of MACEs or hospitalization events. Results A total of 499 MHD patients with 1812 records wereincluded in this analysis during the follow-up period of 4 years. The prevalence of HK, stratified by serum potassium thresholds of ≥5.0, ≥5.5, and ≥6.0 mmol/L, was 55.11%, 27.66%, and 11.62%, respectively. Recurrent HK, defined as at least two episodes of serum potassium ≥5.0 mmol/L, was observed in 53.09% of the hyperkalemia patients. Multivariate logistic regression models for HK revealed that gender, dialysis duration, Kt/v, creatinine and treatment with ACEI or ARB drugs were associated with increased serum potassium odds. Of the 275 patients with HK, 84 patients (30.55%) had recurrent HK twice and 62 patients (22.55%) had recurrent HK≥ 3 times. Albumin, phosphorus and the growth rate of body weight in the recurrent HK group were significantly higher than that in the single HK group. Serum potassium levels ≥ 5.0, ≥ 5.5 and ≥ 6.0 mmol/L were significantly associated with the rates of MACEs and hospitalization, respectively. When HK was defined as serum potassium level ≥ 5.0, the odds ratio (OR) of MACEs in HK was 1.535 (95 % CI 1.017-2.318, p = 0.041), The adjusted OR increased progressively as the serum potassium level gradually increased, reaching 1.598(95 % CI 1.046-2.439, p=0.030 ) for ≥ 5.5mmol/L, and 1.823 ( 95 % CI 1.027-3.236, p=0.040 ) for ≥ 6.0mmol/L. Compared with the normal potassium group, the OR for hospitalization in serum potassium ≥5.0 group were 1.541 (95% CI 1.014-2.342, p=0.043) after adjustment, and the adjusted OR value increased to 1.887 (95% CI 1.187-2.537, p=0.007) and 2.083 (95% CI 1.039-4.177, p=0.039) when the serum potassium level was ≥5.5 mmol/L and ≥6.0 mmol/L. Conclusions Among MHD patients, the prevalence of pre-dialysis HK and its recurrence rate remained high. Elevated serum potassium levels were correlated with an augmented risk of MACEs and hospitalization in these patients. These research findings emphasized the crucial significance of implementing effective monitoring and management strategies to precisely control potassium levels in MHD patients. chronic kidney disease maintenance hemodialysis hyperkalemia major adverse cardiovascular events hospitalization Figures Figure 1 Introduction Hyperkalemia, generally defined as a serum potassium (K + ) concentration of > 5.0 mmol/L, is a common electrolyte disturbance in chronic kidney disease (CKD)[ 1 ], particularly in patients with end-stage renal disease (ESRD) receiving maintenance hemodialysis[ 2 ]. The development of HK in MHD patients is usually the result of a combination of various factors, such as an impaired glomerular filtration rate[ 3 ], a high-potassium diet[ 4 ], the use of potassium-based salt substitutes[ 5 ], and the use of medications interfering with potassium homeostasis[ 6 , 7 ]. Because of the key role of the kidney in maintaining potassium homeostasis[ 8 ], HK frequently results in poor clinical outcomes in CKD patients, especially in MHD patients. As serum K levels increase, the rates of major MACEs, hospitalization and death increase[ 9 ]. The role of HK in MACEs had attracted increasing interest, and many studies had examined the associations between HK and adverse events. [ 10 ]. While HK had been repeatedly associated with cardiac dysrhythmia, sudden death, and other adverse events, the potential outcomes associated with HK in MHD patients had remained poorly described. There had been no universally accepted definition of significant HK; the thresholds most widely used for the categorization of mild, moderate, and severe HK had been 5.0, 5.5, and 6.0 mmol/L, respectively. There had been no clear threshold of HK at which these complications were expected to occur, and the relationship between different levels of HK and adverse clinical outcomes had not been studied in detail. Recently, many studies had suggested that the risk for HK-related adverse events had been increased when pre-dialysis serum potassium levels were > 5.5 or > 6.0 mmol/L. In 2020, to strengthen the prevention and control of HK in patients with chronic kidney disease and improve the prognosis of kidney disease worldwide, on the basis of previous research results, the definition of HK was adjusted from an original serum potassium concentration > 5.5 mmol/L to > 5.0 mmol/L[ 11 ]. The precise relationship between HK and the clinical outcomes of patients on hemodialysis still needed further study. Accordingly, we designed a large retrospective cohort study using routine quarterly monitored pre-dialysis serum potassium measurements obtained over a 4-year-long period in a cohort of 499 ESRD patients receiving maintenance thrice-weekly hemodialysis. The primary aim of the present study was to investigate the prevalence, recurrence, and risk factors for HK. A secondary objective was to explore the associations of different levels of HK with adverse clinical outcomes. By varying the definition of HK, we specifically sought to determine whether there was a threshold at which potassium was associated with a marked increase in MACEs and hospitalization. Characterizing the relationships between different degrees of HK and the risk of adverse clinical outcomes helped provide practical guidance for nephrologists and other healthcare providers in dialysis settings. Materials and methods Study patients and design This retrospective study was conducted in the dialysis centers of Sun Yat-sen Memorial Hospital affiliated with Sun Yat-sen University, the Eighth Affiliated Hospital of Sun Yat-sen University, and the Shenshan Medical Center of Sun Yat-sen Memorial Hospital. All patients undergoing maintenance hemodialysis three times a week in these three dialysis centers were enrolled. The inclusion criteria were as follows: (1) age > 18 years; (2) dialysis duration ≥ 3 months with at least one recorded serum potassium measurement; (3) no prior history of peritoneal dialysis or renal transplantation; and (4) complete case information and patient cooperation. The exclusion criteria included: (1) an estimated survival period of less than 1 year; (2) planning to undergo a kidney transplant within the next 6 months; (3) a history of severe infection or surgery in the past 6 months; (4) patients with rickets or primary parathyroid diseases affecting calcium and phosphorus metabolism; and (5) patients with confirmed or suspected malignant tumors. Each MHD session lasted 3.5-4 hours and was performed using a dialyzer with blood flow rates ranging from 200 to 220 mL/min and a dialysate flow rate of 500 mL/min. Between January 2020 and March 2024, a total of 499 MHD patients were enrolled in the study. Collection of demographics, medical, and laboratory data Demographic and clinical data, including age, sex, and comorbid conditions, were collected from medical records and patient interviews. Primary nephrological diagnoses, such as diabetic kidney disease and nondiabetic glomerular disease, were extracted from medical records. Venous blood samples were collected after an overnight fast prior to hemodialysis to measure various biomarkers, including albumin, serum triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), hemoglobin, creatinine, potassium, total calcium, serum intact parathyroid hormone (PTH), and phosphorus levels. Blood samples were obtained at three-month intervals throughout the study period. Study Outcomes HK was precisely defined as a serum potassium concentration reaching or exceeding 5.0 mmol/L. In accordance with established clinical guidelines, hyperkalemia was meticulously categorized into three distinct grades: mild (serum potassium ranging from 5.0 to 5.5 mmol/L), moderate (5.5 to 6.0 mmol/L), and severe (equal to or greater than 6.0 mmol/L). During the follow-up period, a comprehensive assessment was conducted to examine the recurrence of pre-dialysis HK. Recurrence was rigorously defined as the presence of at least two separate laboratory measurements of potassium (K⁺) that fulfilled the pre-established HK criteria. These pre-dialysis K⁺ values were systematically obtained following the inter-dialysis interval to ensure accurate and representative data collection. For the univariate and multivariate statistical analyses aiming to identify factors associated with HK, a cut-off value of ≥ 5.0 mmol/L was employed. This threshold was selected based on current medical knowledge and best practices in the field to optimize the accuracy and relevance of the analysis. The primary outcome were all-cause hospitalization and major adverse cardiovascular events (defined as a composite of hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, congestive heart failure, transient ischemia attack or stroke). Statistical analysis SPSS 22.0 statistical software was used for data analysis. Measurement data conforming to a normal distribution are expressed as (x ± σ), and an independent sample t test was used for comparisons between groups. Measurement data that did not conform to a normal distribution were represented by M (Q1, Q3), and the Mann-Whitney U test was used for comparisons between groups. Categorical variables are shown as percentages (%), and the χ2 test was used for comparisons between groups. In addition, multiple logistic regression analysis was performed to assess the associations of several demographic and clinical characteristics with HK. Variables were tested for interactions and included in the model if P was < 0.50 in the univariate analysis. P values < 0.05 (two-tailed) were considered statistically significant. Results Characteristics, prevalence and recurrence of HK in MHD patients A total of 499 MHD patients were included in this study, according to the inclusion and exclusion criteria (Fig. 1 ). The patients’ demographic, clinical and biochemical data are shown in Table 1 . A total of 319 males and 180 females with a mean age of 58.00 years and a median dialysis duration of 37.00 months were included (range: 15.00, 75.00). The dialysate potassium bath prescription was set at a concentration of 2 mmol/L. No patient was prescribed sodium polystyrene sulfonate or other potassium-binding agents for the long-term management of hyperkalemia during the entire four-year study period. Among the 499 MHD patients, a total of 1812 blood potassium measurements were detected, with an average of 3.63 measurements per patient and the mean serum potassium level was 4.51 ± 0.83 mmol/L. The characteristics of patients with and without HK are summarized in Table 1 . HK was defined as as patients who had at least one serum potassium measurement ≥ 5.0 mmol/L during the study period. Among the 499 patients, 224 (44.89%) had normal serum potassium levels, while 275 (55.11%) had hyperkalemia. Among the 275 hyperkalemia patients, 129 had single-episode hyperkalemia (46.91% of the hyperkalemic patients), and 146 had recurrent hyperkalemia (53.09%). In the recurrent hyperkalemia group, the maximum recurrence was 6 times, seen in 2 cases (1.37%); 62 cases (42.47%) had 3 or more recurrences, and 84 cases (57.53%) had 2 recurrences. Table 1 Baseline characteristics of MHD patients with and without HK. Characteristics All( N = 499) Without HK ( n = 224) HK ( n = 275) x 2 /z P Male(n,%) 319,63.93% 154,68.75% 165,60.00% 4.121 0.049 Age (year) 58.00(47.00,68.00) 57.00(48.00,69.00) 58.00(47.00,68.00) 0.010 0.983 Dialysis duration(month) 37.00(15.00,75.00) 14.00(3.00,45.00) 32.00(10.00,69.00) 89.239 0.001 Kt/v 1.41(1.23,1.63) 1.44(1.26,1.67) 1.37(1.19,1.59) 8.025 0.005 URR 69.43(64.39,74.46) 69.31(64.42,73.81) 69.50(64.39,74.87) 0.578 0.447 β2-Microglobulin (mg/L) 29.60(21.42,35.86) 26.50(21.42,35.86) 31.90(24.20,39.30) 13.927 0.001 Serum albumin(mmol/L) 38.18(35.35,40.57) 37.70(34.20,40.00) 37.85(36.20,40.90) 10.822 0.001 LDL-C (mmol/L) 2.21(1.61,2.78) 2.14(1.54,2.59) 2.26(1.63,2.91) 1.756 0.185 Triglyceride (mol/L) 1.10(0.81,1.82) 1.32(0.81,2.14) 1.06(0.79,1.59) 4.277 0.039 Total cholesterol(mmol/L) 3.76(3.21,4.50) 3.73(3.20,4.32) 3.80(3.22,4.64) 0.501 0.479 Serum Calcium(mmol/L) 2.22(2.11,2.34) 2.21(2.10,2.34) 2.23(2.12,2.35) 1.450 0.229 Creatinine(µmol/L) 903.90(688.95,1109.00) 809.50(603.00,1046.50) 956.00(754.00,1170.00) 24.212 0.000 Parathyroid Hormone(pmol/L) 194.00(105.00,331.00) 189.00(89.50,304.00) 201.00(117.00,345.00) 4.794 0.029 Serum Phosphorus(mmol/L) 1.95(1.57,2.38) 1.75(1.43,2.15) 2.11(1.72,2.58) 44.941 0.000 Serum urea(mmol/L) 19.75(9.10,27.70) 18.48(8.47,25.91) 20.93(9.90,29.50) 6.936 0.008 Uric Acid(µmol/L) 435.00(350.00,506.00) 427.80(331.96,494.49) 440.19(365.00,510.00) 2.037 0.154 Prealbumin(g/L) 0.43(0.29,304.20) 0.60(0.27,310.43) 0.41(0.30,302.62) 0.243 0.622 Hemoglobin(g/L) 110.00(94.00,123.00) 110.00(95.00,121.00) 110.00(94.00,124.00) 0.114 0.735 Serum Iron(umol/L) 10.23(7.48,13.90) 9.78(7.01,13.55) 10.35(7.80,14.60) 3.393 0.066 Serum ferritin (ng/ml) 102.00(50.40,225.70) 107.80(53.20,255.75) 97.60(49.00,195.00) 3.603 0.058 Total iron binding capacity 45.70(40.30,51.40) 44.33(38.90,51.50) 46.40(41.65,51.05) 3.606 0.058 CRP(mg/L) 3.21(1.23,6.82) 3.19(0.98,7.12) 3.28(1.63,6.48) 0.809 0.369 Dry weight(kg) 58.75(51.00,67.00) 58.75(50.50,66.90) 58.75(52.50,67.10) 0.321 0.571 Weight growth rate(%) 8.85(6.47,10.61) 8.15(5.80,10.11) 9.35(7.14,11.15) 8.774 0.003 Use of ACEI\ARB Drugs(n,%) 232,46.49% 87,38.84% 145,52.73% 9.617 0.002 Calcified heart valves(n,%) 150,33.41% 60,26.79% 90,32.73% 2.073 0.150 Risk factors associated with HK As shown in Table 1 , there are obvious differences in demographic and clinical characteristics between the normal serum potassium group and the hyperkalemia (HK) group. The median age of patients in the normal potassium cohort was 57.00 years, while those in the HK group had a median age of 58.00 years. Similarly, the median dialysis duration in the normal potassium group was 14.00 months, as opposed to 32.00 months in the HK group. These disparities in age and dialysis duration were statistically significant (both p < 0.05), suggesting potential associations with the development of hyperkalemia. The gender distribution also differed significantly between the two groups. The proportion of male patients in the HK group was 60.00%, which was notably lower than the 68.75% observed in the normal potassium group (p < 0.05). This finding may imply a gender - related susceptibility to hyperkalemia. In terms of biochemical and clinical parameters, the HK group presented a distinct profile compared to the normal potassium group. Specifically, patients in the HK group had a longer dialysis duration (in months), along with significantly elevated levels of β2-microglobulin, albumin, triglycerides, creatinine, serum parathyroid hormone, phosphorus, and urea. Additionally, they exhibited a higher weight gain rate. Conversely, the Kt/v value, an important indicator of dialysis adequacy, was lower in the HK group. All these differences were statistically significant (all P < 0.05), indicating that these factors could play crucial roles in the pathogenesis of hyperkalemia. Regarding the use of ACEI/ARB drugs, the normal potassium group had a usage rate of 38.84%, while the HK group showed a significantly higher proportion of 52.73% (P < 0.05). This disparity suggests a potential link between the use of these drugs and the occurrence of hyperkalemia. Lastly, when examining the prevalence of cardiac valve calcification, the percentages of affected patients were 26.79% in the normal potassium group and 32.73% in the HK group. However, this difference did not reach statistical significance (P > 0.05), indicating that cardiac valve calcification may not be directly associated with hyperkalemia in this study population. Multivariate logistic regression analysis was carried out with gender, dialysis duration, β2-microglobulin, triglyceride, albumin, creatinine, serum parathyroid hormone, phosphorus, urea, body weight growth rate, Kt/v, and the use of ACEI/ARB drugs as independent variables. The findings indicated that dialysis duration, creatinine and the use of ACEI/ARB drugs were independent risk factors for HK. In contrast, Kt/v and being male were independent protective factors for HK. The risk of HK in patients undergoing ACEI/ARB drug treatment was 3.79 times higher than that in those not receiving these drugs. Females were more prone to developing HK compared to males (Table 2 ). Table 2 Multivariate logistic regression analysis of risk factors for HK in MHD patients Variables ß SE Walk χ2 P OR(95%CI) Gender -0.687 0.210 10.693 0.001 0.253 (0.111–0.577) Use of ACEI/ARB drugs 0.654 0.207 10.001 0.002 3.695(1.644–8.308) Dialysis duration(month) 0.021 0.005 16.078 < 0.001 1.021(1.011–1.031) Kt/v -1.729 0.549 9.923 0.002 0.177(0.061–0.520) β2-Microglobulin(mg/L) -0.003 0.0125 0.067 0.795 0.997(0.973–1.022) Serum albumin (mmol/L) 0.035 0.041 0.717 0.397 1.035(0.955–1.122) Creatinine(µmol/L) 0.003 0.001 9.958 0.002 1.003(1.001–1.004) Triglyceride (mmol/L) -0.155 0.161 0.924 0.337 0.856(0.624–1.175) Parathyroid Hormone (mmol/L) 0.001 0.001 0.811 0.368 1.001(0.999–1.002) Serum Phosphorus (mmol/L) 0.380 0.333 1.303 0.254 1.462(0.761–2.808) Serum urea(µmol/L)) 0.045 0.024 3.394 0.065 1.046(0.997–1.097) Weight growth rate(%) 0.052 0.058 0.819 0.366 1.054(0.941–1.180) Analysis of factors related to single and recurrent HK The median ages of patients with single and recurrent hyperkalemia (HK) were 57.50 and 59.00 years, respectively. As shown in Table 3 , the median dialysis durations for the two groups were 23.00 and 24.50 months. No statistically significant differences were found between the single - and recurrent - HK groups in these parameters (all P > 0.05). Table 3 Characteristics of MHD patients with single HK and recurrent HK Variables Single HK( n = 129) Recurrent HK ( n = 146) x 2 /z P Male(n,%) 77,59.69% 88,60.27% 0.010 0.921 Age(years) 57.50(47.00,70.00) 59.00(46.00,66.00) 0.383 0.536 Dialysis duration(month) 23.00(4.00,68.00) 24.50(5.00,66.00) 0.197 0.657 Kt/v 1.39(1.04,1.60) 1.36(1.19,1.58) 0.718 0.397 URR 70.29(64.73,75.74) 69.20(63.33,74.33) 1.445 0.229 β2-Microglobulin(mg/L) 31.08(24.4,39.00) 32.11(24.20,39.50) 0.063 0.802 Serum albumin(mmol/L) 37.65(35.2,40.30) 39.25(36.70,41.60) 9.832 0.002 LDL-C(mmol/L) 2.10(2.11,2.86) 2.36(1.67,2.94) 2.807 0.094 Creatinine(µmol/L) 1.06(0.83,1.63) 1.07(0.78,1.58) 0.019 0.891 Total cholesterol(mmol/L) 3.77(3.08,4.52) 3.85(3.25,4.82) 1.568 0.211 Serum Calcium(mmol/L) 2.22(2.11,2.32) 2.25(2.13,2.37) 3.795 0.051 Creatinine(µmol/L) 882.27(720.00,1172.34) 1002.00(815.00,1170.00) 2.516 0.113 Parathyroid Hormone(pmol/L) 183.50(110.00,311.00) 225.50(120.00,396.00) 2.552 0.110 Serum Phosphorus(mmol/L) 1.99(1.62,2.39) 2.25(1.78,2.65) 6.912 0.009 Serum urea(mmol/L) 20.00(9.30,28.33) 22.45(10.10,29.96) 1.034 0.309 Uric Acid(µmol/L) 441.37(332.00,502.00) 439.79(369.00,515.11) 0.252 0.616 Prealbumin(g/L) 112.40(0.29,303.55) 0.37(0.31,299.91) 0.270 0.603 Hemoglobin(g/L) 106.00(91.00,122.00) 114.00(96.00,125.00) 3.740 0.053 Serum Iron(umol/L) 10.10(7.33,14.51) 10.65(8.19,14.96) 1.567 0.211 Serum ferritin (ng/ml) 83.50(42.80,209.00) 102.2(53.40,195.00) 1.184 0.277 Total iron binding capacity 46.80(41.40,50.70) 46.30(42.00,51.70) 0.003 0.960 CRP(mg/L) 3.20(1.16,6.94) 3.41(2.14,6.38) 0.440 0.507 Dry weight(kg) 61.15(54.00,70.00) 56.80(51.00,66.50) 3.746 0.062 Weight growth rate(%) 8.49(5.80,10.54) 9.62(7.81,12.12) 6.755 0.009 Use of ACEI/ARB drugs(n,%) 69.00,53.49% 76.00,52.05% 0.057 0.812 Calcified heart valves(n,%) 37.00,28.68% 53.00,36.30% 1.813 0.178 The utilization rates of ACEI/ARB drugs in the two groups were 53.49% and 52.05%, and the prevalences of heart valve calcification were 28.68% and 36.60%, respectively. Similarly, no significant differences were noted in these indicators between the two groups (all P > 0.05). However, the recurrent-HK group had significantly higher serum albumin and phosphorus levels, as well as a higher body weight increase rate, than the single - HK group (all P < 0.05). A multivariate logistic regression analysis with recurrent HK as the dependent variable was performed. As presented in Table 4 , albumin, phosphorus, and body weight increase rate were selected as independent variables. The results indicated that serum albumin concentration, phosphorus level, and weight gain rate were all independent risk factors for recurrent HK. Table 4 Multivariate logistic regression analysis of recurrent HK in MHD patients Variables ß SE Walk χ2 P OR(95%CI) Serum albumin(mmol/L) 0.134 0.045 8.752 0.003 1.143(1.046–1.249) Serum Phosphorus(mmol/L) 0.846 0.353 5.751 0.017 2.331(1.167–4.563) Weight growth rate(%) 0.151 0.058 6.772 0.009 1.163(1.038–1.303) Associations between HK and MACEs in MHD patients Among the 499 patients, 154 experienced MACEs during the observation period, with an overall MACE incidence of 30.86%. As presented in Table 5 , a total of 179 MACEs were documented among these 154 patients. On average, each patient with MACEs had 1.16 events. Specifically, 118 patients (76.62%) had a single cardiovascular event, 29 patients (18.83%) experienced two MACEs, and 7 patients (4.55%) had three MACEs. Table 6 shows that among the 275 patients with hyperkalemia (HK), 98 developed MACEs during the observation period, resulting in a MACE incidence of 35.64%. In contrast, among the 224 patients with normal serum potassium levels, 56 patients had cardiovascular and cerebrovascular events, with a MACE incidence of 25.00%. The incidence of MACEs was significantly higher in patients with HK compared to those with normal serum potassium (χ² = 6.545, P = 0.011). Further analysis of the 275 HK patients indicated that 34 out of 129 patients with single-episode HK had MACEs during the observation period, with an incidence of 26.36%. In the 146 patients with recurrent HK, 64 experienced MACEs, and the incidence was 43.84%. The incidence of MACEs was significantly higher in patients with recurrent HK than in those with single - episode HK (χ² = 9.122, p = 0.003). When HK was defined as a serum potassium level ≥ 5.0 mmol/L, the odds ratios (ORs) of MACEs in HK patients were 1.661 (95% confidence interval [CI]: 1.124–2.454, p = 0.011) in the unadjusted analysis and 1.535 (95% CI: 1.017–2.318, p = 0.04) in the adjusted analysis, compared with patients having normal potassium levels. Throughout the entire study period, both the unadjusted and adjusted ORs increased gradually as the serum potassium level rose. The adjusted OR reached 1.598 (95% CI: 1.046–2.439, p = 0.030) when the serum potassium concentration was ≥ 5.5 mmol/L and further increased to 1.823 (95% CI: 1.027–3.236, p = 0.040) when the serum potassium concentration was ≥ 6.0 mmol/L. Table 5 MACEs and hospitalization rates in patients with different frequencies of HK Group Total MACEs( N = 156) Hospitalization( N = 311) n ratio (%) χ2 P n ratio (%) χ2 P Normal potassium group 224 56 25.00 6.545 0.011 125 55.80 7.353 0.007 HK group 275 98 35.64 186 67.64 Single HK group 129 34 26.36 9.122 0.003 80 62.02 3.506 0.061 Recurrent HK group 146 64 43.84 106 72.60 Table 6 Association between elevated serum levels and MACEs and hospitalization in MHD patients Blood potassium levels MACEs Hospitalization unadjusted adjusted a unadjusted Adjusted b OR(95%CI) c P OR(95%CI) c P OR(95%CI) c P OR(95%CI) c P ≥ 5.0(mmol/L) 1.661(1.124–2.454) 0.011 1.535(1.017–2.318) 0.041 1.655(1.149–2.385) 0.007 1.541(1.014–2.342) 0.043 ≥ 5.5(mmol/L) 1.678(1.111–2.534) 0.014 1.598(1.046–2.439) 0.003 1.962(1.275–3.019) 0.002 1.887(1.187–2.537) 0.007 ≥ 6.0(mmol/L) 1.987(1.139–3.468) 0.016 1.823(1.027–3.236) 0.040 2.546(1.312–4.942) 0.006 2.083(1.039–4.177) 0.039 a Adjusted for age, Dialysis duration, use of ACEI/ARB drugs and cardiac valve calcification. b Adjusted for age, Dialysis duration, use of ACEI/ARB drugs, cardiac valve calcification and kt\v. c Corresponds to MACEs and hospitalization risk for elevated serum potassium relative to normal potassium in MHD patients The potassium values used for classification were based on a single measurement of blood potassium values Associations between HK and hospital admission in MHD patients Among the 499 patients, 311 patients were hospitalized for various reasons during the observation period, the hospitalization rate was 62.32%. Among the hospitalized patients, the average number of hospitalizations was 1.96, of which 145 patients (46.62%) were hospitalized once. 91 patients (29.26%) were hospitalized 2 times, 45 patients (14.47%) were hospitalized 3 times, and 30 patients were hospitalized more than 3 times. Of the 275 patients with HK, 186 were hospitalized during the observation period (Table 5 ), and the hospitalization rate was 67.64%. Among the 224 patients with normal blood potassium levels, 125 patients were hospitalized during the observation period, the hospitalization rate was 55.80%, and the hospitalization rate of HK patients was higher than that of patients with normal blood potassium levels (χ²=7.353, P = 0.007). Further analysis of 275 patients with HK revealed that 80 of 129 patients with single HK were hospitalized during the observation period, for a hospitalization rate of 62.02%. Among the 146 patients with recurrent HK, 106 patients were hospitalized during the observation period, and the hospitalization rate was 72.60%, but there was no significant difference in the hospitalization rate between single HK patients and recurrent HK patients (P > 0.05). Compared with the normal potassium group, the ORs for hospitalization in serum potassium ≥ 5.0 group were 1.655 (95% CI 1.149–2.385, p = 0.007) and 1.541 (95% CI 1.014–2.342, p = 0.043) in the unadjusted and adjusted analyses, respectively. During the whole study period, With the increase of serum potassium level, the OR continued to rise, reaching to 1.887(95% CI 1.187–2.537, p = 0.007) and 2.083 (95% CI 1.039–4.177, p = 0.039) when the serum potassium level was ≥ 5.5 mmol/L and ≥ 6.0 mmol/L, respectively. (Table 6 ). Discussion HK was a serious electrolyte disturbances and was associated with sudden cardiac death and fatal arrhythmias[ 12 ]. Under normal conditions, the serum potassium concentration was strictly regulated by redundant homeostatic mechanisms and was maintained within a narrow range of 3.5-5.0 mmol/L[ 13 ]. Once these homeostatic mechanisms were disrupted, potassium abnormalities may occur. With increasing serum potassium concentrations, the risk of adverse outcomes increased substantially, which made HK a medical emergency that needs special attention[ 14 ]. In this retrospective investigation, a 4-year follow-up was conducted on 499 MHD patients to explore the prevalence of hyperkalemia (HK) and evaluate its recurrence rate. Additionally, the correlations between HK and the risks of MACEs as well as hospitalization in MHD patients were analyzed. In our research, The pre-dialysis serum potassium was measured 1812 times, with an average of 3.63 measurements per patient. Serum potassium levels were ≥ 5.0 mmol/L in 517 cases (28.53%). Among the 499 patients, 224 (44.89%) had normal serum potassium levels, and 275 (55.11%) had hyperkalemia. The report published by the DOOPS study indicated that the prevalence of hyperkalemia in MHD patients was 30%-50%[ 15 ], which was largely consistent with the findings of this study. Research by Tsiaigka et al. on the incidence of hyperkalemia in MHD patients showed that the prevalence of pre-dialysis serum potassium levels ≥ 5.1 mmol/L was as high as 60.4%, and the prevalence of pre-dialysis serum potassium levels ≥ 5.5 mmol/L reached 42.2%, which was higher than the incidence of HK found in this study[ 16 ]. In our study cohort, 57.53% and 38.27% of the patients experienced recurrence, with a second and third laboratory K⁺ value reaching or exceeding 5.0 mmol/L, respectively. Among the 275 patients with hyperkalemia, 129 had single-episode hyperkalemia, constituting 46.90% of the total hyperkalemia patient population. Meanwhile, 146 patients had recurrent hyperkalemia, accounting for 53.09%. Among those with recurrent hyperkalemia, the maximum number of hyperkalemia episodes was 6 times, with 2 patients representing 1.37% of the total recurrent hyperkalemia patient group. There were 62 patients (42.47%) who had 3 or more episodes, and 84 patients (57.53%) who had 2 episodes. These findings imply that a significant number of MHD patients might not be receiving optimal treatment for HK, highlighting the necessity for more extensive clinical efforts to enhance potassium homeostasis in MHD patients. In the study population under our investigation, it was observed that the risk of pre-dialysis HK in females was 3.95-fold higher compared to that in males. This result was in line with the findings of a prior study on MHD patients, which demonstrated a significantly elevated prevalence of pre-dialysis HK among women[ 17 ]. Similarly, Kim T et al. also observed gender differences in hyperkalemia among African-Americans and Caucasians, indicating that female hemodialysis patients were more likely to develop hyperkalemia[ 18 ]. Nevertheless, the underlying mechanism responsible for the increased susceptibility of females to hyperkalemia remains elusive. Potential factors might encompass variations in dietary potassium ingestion, dialysis session duration, as well as the efficacy of potassium ion elimination [ 19 – 21 ]. This demanded further investigation to fully elucidate the underlying mechanisms. MHD patients with HK were found to have a longer dialysis duration. One potential explanation for the lower prevalence of pre-dialysis HK in patients with shorter dialysis durations might be that these patients were newly initiated maintenance hemodialysis; their kidneys still retained part of their renal function, although these residual renal functions were very small (less than 10% of their normal function), not enough to maintain life, but they still played a substantial role in the removal of toxins and excess water in the patient's body, as well as the maintenance of electrolytes and acid-base balance. Our findings were consistent with those of a study conducted in the United States. Notably, this study also found an association between hyperkalemia and deterioration of residual kidney function in MHD patients[ 22 ]. Therefore, when contrasted with patients who had undergone dialysis for an extended period, MHD patients with shorter dialysis histories exhibited a lower propensity for developing HK. KT/V was a crucial indicator for evaluating the adequacy of dialysis. A low KT/V indicated a reduced capacity of dialysis to eliminate solutes[ 23 ]. Potassium, as a major extracellular cation, was one of the important solutes that need to be removed during dialysis. When dialysis was inadequate, renal replacement therapy fails to effectively excrete the excessive potassium ions from the body. Consequently, in our study, we found that hemodialysis patients with a low KT/V are prone to hyperkalemia. Our study also revealed that the risk of HK in patients treated with ACE inhibitors or ARBs was 3.792 times greater than that in patients not treated with these drugs. This finding was consistent with prior studies that reported that HK was common among CKD patients who used ACEIs or ARBs[ 24 ]. The explanation for this phenomenon was that ACEI drugs inhibited the activity of angiotensin-converting enzyme (ACE), thus reducing the production of angiotensin II and subsequently suppressing the activity of the renin-angiotensin-aldosterone system (RAAS)[ 25 ]. Since the sodium-retaining and potassium-excreting function of aldosterone was inhibited, the excretion of potassium decreased and the serum potassium level rose, which potentially led to hyperkalemia.[ 26 ]. In the present study, it was discovered that HK was independently correlated with a heightened risk of MACEs and hospitalizations. These results align with those of multiple previous studies, which indicated an association between HK and an elevated risk of lethal cardiac arrhythmias among dialysis patients.[ 27 , 28 ]. Subsequently, our aim was to ascertain whether there existed evidence indicating a graded correlation between the serum potassium level and both MACEs as well as hospitalization. In the course of this study, it was observed that elevated serum potassium levels (≥ 5.0, ≥ 5.5, or ≥ 6.0 mmol/L, contingent upon the specific outcome under consideration) were independently linked to a heightened risk of MACEs and hospitalization. As anticipated, we determined that escalating serum potassium levels were associated with an augmented risk of MACEs and hospitalization, with 5.0 mmol/L, 5.5 mmol/L, and 6.0 mmol/L serving as the crucial threshold values. While HK represents a significant burden due to its contribution to an increased likelihood of adverse clinical outcomes and mortality, diverse definitions of HK have been implemented. For instance, Iseki et al. defined HK as a serum potassium concentration of ≥ 5.5 mmol/L and reported a greater risk of death in comparison to a baseline concentration of < 3.5 mmol/L.[ 29 ]. Kovesdy et al.[ 30 ], in a large observational study of a contemporary cohort of hemodialysis patients, reported that a serum potassium concentration of ≥ 5.6 mmol/L was associated with an increased risk of all-cause and cardiovascular death. In our study population, we identified a graded association between HK and MACEs and hospitalization. We found that the risk becomes statistically significant at potassium concentrations of approximately 5.0 mmol/L, 5.5 mmol/L and 6.0 mmol/L. This may have clinical implications, as it could be a threshold at which clinicians should consider taking action or at which protocols designed to safeguard patients could be employed. However, given the association of HK with MHD patients and the elevated odds of MACEs and hospitalization associated with HK, this metabolic disturbance should be considered a disease-specific safety event. More work was needed to determine the extent to which alterations in disease management reduce the incidence of this patient safety indicator. The current study was subject to several limitations. Firstly, it was a retrospective study conducted at three centers, and the follow-up duration might not have been extensive enough to comprehensively assess the late outcomes of patients undergoing MHD. Secondly, due to constraints in sample size, the prevalence and incidence of HK exhibited considerable variability, which could be attributed to factors such as the target population and the potassium threshold employed to define it. Additionally, we were incapable of conducting subgroup analyses to explore the risk factors for HK among MHD patients. Future, larger-scale studies should take subgroups into account. Declarations Acknowledgments We thanked all participants for their support and cooperation. Authors’ contributions Weitang Liao and Minhong Luo contributed to the conception and design of the work, data analysis and wrote the main manuscript text. Lili Zhang, Hongbo Ye, Ni Xu, Yinyang Liang, Lina Zhuang, Hao Li, Qianqian Han, Caiju Mo contributed to the acquisition of data. Ying ying Zhu contributed to data analysis. Qiongqiong Yang had drafted the work and substantively revised it. All authors reviewed the manuscript. Funding This work was funded by the Key Technologies R&D Program of Guangdong Province (No. 3552023B1111030004) and the National Science Foundation of China (No. 82270743). Data Availability The data presented in this study were available on request from the corresponding author Declarations The study was approved by the Clinical Trial Ethics Committee of Sun Yat-sen Memorial Hospital .Informed consent was obtained from all individual participants included in the study. Laboratory data used in this study were extracted from routine examination files and analyzed retrospectively. Consent for publication This section is not applicable in this article. Competing interests All authors have no conflicts of interest. References Sarnowski A, Gama RM, Dawson A, Mason H, Banerjee D. Hyperkalemia in Chronic Kidney Disease: Links, Risks and Management. Int J Nephrol renovascular disease. 2022;15:215–28. Spinowitz B, Fishbane S, Fukagawa M, Ford M, Guzman N, Rastogi A. Course of Hyperkalemia in Patients on Hemodialysis. Int J Nephrol. 2022;2022:6304571. Shibata S, Uchida S. Hyperkalemia in patients undergoing hemodialysis: Its pathophysiology and management. Therapeutic apheresis and dialysis: official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy 2022, 26(1):3–14. Bernier-Jean A, Wong G, Saglimbene V, Ruospo M, Palmer SC, Natale P, Garcia-Larsen V, Johnson DW, Tonelli M, Hegbrant J, et al. Self-Reported Physical Activity and Survival in Adults Treated With Hemodialysis: A DIET-HD Cohort Study. Kidney Int Rep. 2021;6(12):3014–25. Pantanowitz L. Drug-induced hyperkalemia. Am J Med. 2002;112(4):334–5. Kang SH, Kim GO, Kim BY, Son EJ, Do JY. Effect of angiotensin-converting enzyme inhibitors versus that of angiotensin receptor blockers on survival in patients undergoing hemodialysis: a nationwide observational cohort study. Ren Fail. 2024;46(1):2313173. Mahmud HA, Palmer BF. Management of Hyperkalemia in Renin-Angiotensin-Aldosterone System Inhibitor: Strategies to Maintain Chronic Kidney Disease Patients with Type II Diabetes on Therapy. Cardiorenal Med. 2024;14(1):191–201. Palmer BF. Regulation of Potassium Homeostasis. Clin J Am Soc Nephrology: CJASN. 2015;10(6):1050–60. Kashihara N, Kumeda Y, Higashino Y, Maeda Y, Kaneko Y, Kanai H, Taniguchi Y, Ishii T, Tomioka Y. Efficacy and safety of patiromer for non-dialysis and dialysis patients with hyperkalemia: the randomized, placebo-controlled and long-term study. Clinical and experimental nephrology 2024. Singh T, Alagasundaramoorthy S, Gregory A, Astor BC, Maursetter L. Low dialysis potassium bath is associated with lower mortality in end-stage renal disease patients admitted to hospital with severe hyperkalemia. Clin kidney J. 2021;14(9):2059–63. Clase CM, Carrero JJ, Ellison DH, Grams ME, Hemmelgarn BR, Jardine MJ, Kovesdy CP, Kline GA, Lindner G, Obrador GT et al. Potassium homeostasis and management of dyskalemia in kidney diseases: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney international 2020, 97(1):42–61. Hougen I, Leon SJ, Whitlock R, Rigatto C, Komenda P, Bohm C, Tangri N. Hyperkalemia and its Association With Mortality, Cardiovascular Events, Hospitalizations, and Intensive Care Unit Admissions in a Population-Based Retrospective Cohort. Kidney Int Rep. 2021;6(5):1309–16. Hoppe LK, Muhlack DC, Koenig W, Carr PR, Brenner H, Schottker B. Association of Abnormal Serum Potassium Levels with Arrhythmias and Cardiovascular Mortality: a Systematic Review and Meta-Analysis of Observational Studies. Cardiovasc Drugs Ther. 2018;32(2):197–212. Bianchi S, Aucella F, De Nicola L, Genovesi S, Paoletti E, Regolisti G. Management of hyperkalemia in patients with kidney disease: a position paper endorsed by the Italian Society of Nephrology. J Nephrol. 2019;32(4):499–516. Karaboyas A, Zee J, Brunelli SM, Usvyat LA, Weiner DE, Maddux FW, Nissenson AR, Jadoul M, Locatelli F, Winkelmayer WC, et al. Dialysate Potassium, Serum Potassium, Mortality, and Arrhythmia Events in Hemodialysis: Results From the Dialysis Outcomes and Practice Patterns Study (DOPPS). Am J kidney diseases: official J Natl Kidney Foundation. 2017;69(2):266–77. Dimitra Tsiagka PIG, Maria I, Pikilidou V, Vaios S, Roumeliotis C, Syrganis K, Mavromatidis S, Metallidis. Vassilios Liakopoulos, Pantelis E Zebekakis Prevalence, recurrence and seasonal variation of hyperkalemia among patients on hemodialysis. Int Urol Nephrol. 2022;54:2327–34. Agiro A, Duling I, Eudicone J, Davis J, Brahmbhatt YG, Cooper K. The prevalence of predialysis hyperkalemia and associated characteristics among hemodialysis patients: The RE-UTILIZE study. Hemodialysis international International Symposium on Home Hemodialysis 2022, 26(3):397–407. Kim T, Rhee CM, Streja E, Soohoo M, Obi Y, Chou JA, Tortorici AR, Ravel VA, Kovesdy CP, Kalantar-Zadeh K. Racial and Ethnic Differences in Mortality Associated with Serum Potassium in a Large Hemodialysis Cohort. Am J Nephrol. 2017;45(6):509–21. Naber T, Purohit S. Chronic Kidney Disease: Role of Diet for a Reduction in the Severity of the Disease. Nutrients 2021, 13(9). Babich JS, Dupuis L, Kalantar-Zadeh K, Joshi S. Hyperkalemia and Plant-Based Diets in Chronic Kidney Disease. Adv kidney disease health. 2023;30(6):487–95. Bansal S, Pergola PE. Current Management of Hyperkalemia in Patients on Dialysis. Kidney Int Rep. 2020;5(6):779–89. Arif Y, Wenziger C, Hsiung JT, Edward A, Lau WL, Hanna RM, Lee Y, Obi Y, Kovesdy CP, Kalantar-Zadeh K, et al. Association of serum potassium with decline in residual kidney function in incident hemodialysis patients. Nephrol dialysis transplantation: official publication Eur Dialysis Transpl Association - Eur Ren Association. 2022;37(11):2234–40. Jeon J, Kim GO, Kim BY, Son EJ, Do JY, Lee JE, Kang SH. Effects of Kt/V(urea) on outcomes according to age in patients on maintenance hemodialysis. Clin kidney J. 2024;17(5):sfae116. Leon SJ, Whitlock R, Rigatto C, Komenda P, Bohm C, Sucha E, Bota SE, Tuna M, Collister D, Sood M, et al. Hyperkalemia-Related Discontinuation of Renin-Angiotensin-Aldosterone System Inhibitors and Clinical Outcomes in CKD: A Population-Based Cohort Study. Am J kidney diseases: official J Natl Kidney Foundation. 2022;80(2):164–73. e161. Parikh RV, Nash DM, Brimble KS, Markle-Reid M, Tan TC, McArthur E, Khoshniat-Rad F, Sood MM, Zheng S, Pravoverov L, et al. Kidney Function and Potassium Monitoring After Initiation of Renin-Angiotensin-Aldosterone System Blockade Therapy and Outcomes in 2 North American Populations. Circulation Cardiovasc Qual outcomes. 2020;13(9):e006415. Silva-Cardoso J, Brito D, Frazao JM, Ferreira A, Bettencourt P, Branco P, Fonseca C. Management of RAASi-associated hyperkalemia in patients with cardiovascular disease. Heart Fail Rev. 2021;26(4):891–6. Calabrese V, Cernaro V, Battaglia V, Gembillo G, Longhitano E, Siligato R, Sposito G, Ferlazzo G, Santoro D. Correlation between Hyperkalemia and the Duration of Several Hospitalizations in Patients with Chronic Kidney Disease. J Clin Med 2022, 11(1). Ferraro PM, Bolignano D, Aucella F, Brunori G, Gesualdo L, Limido A, Locatelli F, Nordio M, Postorino M, Pecoits-Filho R, et al. Hyperkalemia excursions and risk of mortality and hospitalizations in hemodialysis patients: results from DOPPS-Italy. J Nephrol. 2022;35(2):707–9. Iseki K, Uehara H, Nishime K, Tokuyama K, Yoshihara K, Kinjo K, Shiohira Y, Fukiyama K. Impact of the initial levels of laboratory variables on survival in chronic dialysis patients. Am J kidney diseases: official J Natl Kidney Foundation. 1996;28(4):541–8. Kovesdy CP, Regidor DL, Mehrotra R, Jing J, McAllister CJ, Greenland S, Kopple JD, Kalantar-Zadeh K. Serum and dialysate potassium concentrations and survival in hemodialysis patients. Clin J Am Soc Nephrology: CJASN. 2007;2(5):999–1007. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5952868","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442932674,"identity":"443385ed-37dc-4417-b9ad-a18a4a0fa00c","order_by":0,"name":"Weitang Liao","email":"","orcid":"","institution":"Department of Nephrology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Weitang","middleName":"","lastName":"Liao","suffix":""},{"id":442932677,"identity":"5189c8ec-ff08-4e96-8ff0-8b025ca9b694","order_by":1,"name":"Minhong Luo","email":"","orcid":"","institution":"Department of 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Clinical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Zhu","suffix":""},{"id":442932706,"identity":"556ac395-1933-437e-a1ec-f28b4a0c8731","order_by":11,"name":"Qiongqiong Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYPACGwYGZuYGGM+AGC1pQC2MpGk5DMTEajE4fvbwizdl56P52xkbGH+21SU2sDdvk2CouYNby5m8NMs5527nzjjM2MDM23Y4sYHnWJkEw7FnuLUcyDEz5m27ndsA0sLYdiCxQSLHTIKx4TBuLeffgLScy51/GOYw+TcEtNzIMX7M23YgdwNQCwNvGzPQFh78WiRvvDFjnHMuOXcjUMthnnOHjdt40ootEo7h1sJ3Psf4w5syu9x55w8ffPijrE62n/3wxhsfanBrUTjAwCbBwwbhHGAEMsDsBJwaGBjkGxiYP8C0MDD8waN0FIyCUTAKRiwAAJ+YWzTAApFrAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Nephrology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":true,"prefix":"","firstName":"Qiongqiong","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-02-03 17:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5952868/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5952868/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-025-04454-z","type":"published","date":"2025-10-16T15:57:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80791191,"identity":"3ddee05f-2ab1-4206-b050-122d1a541037","added_by":"auto","created_at":"2025-04-17 06:47:45","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":187962,"visible":true,"origin":"","legend":"\u003cp\u003eSample size of the study cohorts, with iterative application of the inclusion and exclusion criteria.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5952868/v1/d79fc7a699a955a031197f5e.jpeg"},{"id":93956728,"identity":"871fb2a8-1a8d-4907-928a-08b3044bff23","added_by":"auto","created_at":"2025-10-20 16:11:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1246442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5952868/v1/2c9c9f8e-65d4-4e29-9e05-39f557246851.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence,Recurrence, Risk Factors and Adverse Clinical Outcomes of Hyperkalemia in Maintenance Hemodialysis Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHyperkalemia, generally defined as a serum potassium (K\u003csup\u003e+\u003c/sup\u003e) concentration of \u0026gt;\u0026thinsp;5.0 mmol/L, is a common electrolyte disturbance in chronic kidney disease (CKD)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], particularly in patients with end-stage renal disease (ESRD) receiving maintenance hemodialysis[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The development of HK in MHD patients is usually the result of a combination of various factors, such as an impaired glomerular filtration rate[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], a high-potassium diet[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], the use of potassium-based salt substitutes[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and the use of medications interfering with potassium homeostasis[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Because of the key role of the kidney in maintaining potassium homeostasis[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], HK frequently results in poor clinical outcomes in CKD patients, especially in MHD patients. As serum K levels increase, the rates of major MACEs, hospitalization and death increase[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe role of HK in MACEs had attracted increasing interest, and many studies had examined the associations between HK and adverse events. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While HK had been repeatedly associated with cardiac dysrhythmia, sudden death, and other adverse events, the potential outcomes associated with HK in MHD patients had remained poorly described. There had been no universally accepted definition of significant HK; the thresholds most widely used for the categorization of mild, moderate, and severe HK had been 5.0, 5.5, and 6.0 mmol/L, respectively. There had been no clear threshold of HK at which these complications were expected to occur, and the relationship between different levels of HK and adverse clinical outcomes had not been studied in detail.\u003c/p\u003e \u003cp\u003eRecently, many studies had suggested that the risk for HK-related adverse events had been increased when pre-dialysis serum potassium levels were \u0026gt;\u0026thinsp;5.5 or \u0026gt;\u0026thinsp;6.0 mmol/L. In 2020, to strengthen the prevention and control of HK in patients with chronic kidney disease and improve the prognosis of kidney disease worldwide, on the basis of previous research results, the definition of HK was adjusted from an original serum potassium concentration\u0026thinsp;\u0026gt;\u0026thinsp;5.5 mmol/L to \u0026gt;\u0026thinsp;5.0 mmol/L[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The precise relationship between HK and the clinical outcomes of patients on hemodialysis still needed further study. Accordingly, we designed a large retrospective cohort study using routine quarterly monitored pre-dialysis serum potassium measurements obtained over a 4-year-long period in a cohort of 499 ESRD patients receiving maintenance thrice-weekly hemodialysis. The primary aim of the present study was to investigate the prevalence, recurrence, and risk factors for HK. A secondary objective was to explore the associations of different levels of HK with adverse clinical outcomes. By varying the definition of HK, we specifically sought to determine whether there was a threshold at which potassium was associated with a marked increase in MACEs and hospitalization. Characterizing the relationships between different degrees of HK and the risk of adverse clinical outcomes helped provide practical guidance for nephrologists and other healthcare providers in dialysis settings.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy patients and design\u003c/h2\u003e \u003cp\u003eThis retrospective study was conducted in the dialysis centers of Sun Yat-sen Memorial Hospital affiliated with Sun Yat-sen University, the Eighth Affiliated Hospital of Sun Yat-sen University, and the Shenshan Medical Center of Sun Yat-sen Memorial Hospital. All patients undergoing maintenance hemodialysis three times a week in these three dialysis centers were enrolled. The inclusion criteria were as follows: (1) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; (2) dialysis duration\u0026thinsp;\u0026ge;\u0026thinsp;3 months with at least one recorded serum potassium measurement; (3) no prior history of peritoneal dialysis or renal transplantation; and (4) complete case information and patient cooperation. The exclusion criteria included: (1) an estimated survival period of less than 1 year; (2) planning to undergo a kidney transplant within the next 6 months; (3) a history of severe infection or surgery in the past 6 months; (4) patients with rickets or primary parathyroid diseases affecting calcium and phosphorus metabolism; and (5) patients with confirmed or suspected malignant tumors. Each MHD session lasted 3.5-4 hours and was performed using a dialyzer with blood flow rates ranging from 200 to 220 mL/min and a dialysate flow rate of 500 mL/min. Between January 2020 and March 2024, a total of 499 MHD patients were enrolled in the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCollection of demographics, medical, and laboratory data\u003c/h3\u003e\n\u003cp\u003eDemographic and clinical data, including age, sex, and comorbid conditions, were collected from medical records and patient interviews. Primary nephrological diagnoses, such as diabetic kidney disease and nondiabetic glomerular disease, were extracted from medical records. Venous blood samples were collected after an overnight fast prior to hemodialysis to measure various biomarkers, including albumin, serum triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), hemoglobin, creatinine, potassium, total calcium, serum intact parathyroid hormone (PTH), and phosphorus levels. Blood samples were obtained at three-month intervals throughout the study period.\u003c/p\u003e\n\u003ch3\u003eStudy Outcomes\u003c/h3\u003e\n\u003cp\u003eHK was precisely defined as a serum potassium concentration reaching or exceeding 5.0 mmol/L. In accordance with established clinical guidelines, hyperkalemia was meticulously categorized into three distinct grades: mild (serum potassium ranging from 5.0 to 5.5 mmol/L), moderate (5.5 to 6.0 mmol/L), and severe (equal to or greater than 6.0 mmol/L). During the follow-up period, a comprehensive assessment was conducted to examine the recurrence of pre-dialysis HK. Recurrence was rigorously defined as the presence of at least two separate laboratory measurements of potassium (K⁺) that fulfilled the pre-established HK criteria. These pre-dialysis K⁺ values were systematically obtained following the inter-dialysis interval to ensure accurate and representative data collection.\u003c/p\u003e \u003cp\u003eFor the univariate and multivariate statistical analyses aiming to identify factors associated with HK, a cut-off value of \u0026ge;\u0026thinsp;5.0 mmol/L was employed. This threshold was selected based on current medical knowledge and best practices in the field to optimize the accuracy and relevance of the analysis. The primary outcome were all-cause hospitalization and major adverse cardiovascular events (defined as a composite of hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, congestive heart failure, transient ischemia attack or stroke).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSPSS 22.0 statistical software was used for data analysis. Measurement data conforming to a normal distribution are expressed as (x\u0026thinsp;\u0026plusmn;\u0026thinsp;σ), and an independent sample t test was used for comparisons between groups. Measurement data that did not conform to a normal distribution were represented by M (Q1, Q3), and the Mann-Whitney U test was used for comparisons between groups. Categorical variables are shown as percentages (%), and the χ2 test was used for comparisons between groups. In addition, multiple logistic regression analysis was performed to assess the associations of several demographic and clinical characteristics with HK. Variables were tested for interactions and included in the model if P was \u0026lt;\u0026thinsp;0.50 in the univariate analysis. P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed) were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics, prevalence and recurrence of HK in MHD patients\u003c/h2\u003e \u003cp\u003eA total of 499 MHD patients were included in this study, according to the inclusion and exclusion criteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The patients\u0026rsquo; demographic, clinical and biochemical data are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 319 males and 180 females with a mean age of 58.00 years and a median dialysis duration of 37.00 months were included (range: 15.00, 75.00). The dialysate potassium bath prescription was set at a concentration of 2 mmol/L. No patient was prescribed sodium polystyrene sulfonate or other potassium-binding agents for the long-term management of hyperkalemia during the entire four-year study period. Among the 499 MHD patients, a total of 1812 blood potassium measurements were detected, with an average of 3.63 measurements per patient and the mean serum potassium level was 4.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83 mmol/L. The characteristics of patients with and without HK are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. HK was defined as as patients who had at least one serum potassium measurement\u0026thinsp;\u0026ge;\u0026thinsp;5.0 mmol/L during the study period. Among the 499 patients, 224 (44.89%) had normal serum potassium levels, while 275 (55.11%) had hyperkalemia. Among the 275 hyperkalemia patients, 129 had single-episode hyperkalemia (46.91% of the hyperkalemic patients), and 146 had recurrent hyperkalemia (53.09%). In the recurrent hyperkalemia group, the maximum recurrence was 6 times, seen in 2 cases (1.37%); 62 cases (42.47%) had 3 or more recurrences, and 84 cases (57.53%) had 2 recurrences.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of MHD patients with and without HK.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;499)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout HK (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;224)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHK (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;275)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/z\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e319,63.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e154,68.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e165,60.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.00(47.00,68.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.00(48.00,69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.00(47.00,68.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis duration(month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.00(15.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00(3.00,45.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.00(10.00,69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKt/v\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.41(1.23,1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.44(1.26,1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.37(1.19,1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eURR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.43(64.39,74.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.31(64.42,73.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.50(64.39,74.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-Microglobulin (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.60(21.42,35.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.50(21.42,35.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.90(24.20,39.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.18(35.35,40.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.70(34.20,40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.85(36.20,40.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.21(1.61,2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.14(1.54,2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.26(1.63,2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglyceride (mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.10(0.81,1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.32(0.81,2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.06(0.79,1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.76(3.21,4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.73(3.20,4.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.80(3.22,4.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Calcium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.22(2.11,2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.21(2.10,2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.23(2.12,2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e903.90(688.95,1109.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e809.50(603.00,1046.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e956.00(754.00,1170.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid Hormone(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194.00(105.00,331.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e189.00(89.50,304.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e201.00(117.00,345.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Phosphorus(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.95(1.57,2.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.75(1.43,2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.11(1.72,2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum urea(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.75(9.10,27.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.48(8.47,25.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.93(9.90,29.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric Acid(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e435.00(350.00,506.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e427.80(331.96,494.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e440.19(365.00,510.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrealbumin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.43(0.29,304.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60(0.27,310.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41(0.30,302.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110.00(94.00,123.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110.00(95.00,121.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e110.00(94.00,124.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Iron(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.23(7.48,13.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.78(7.01,13.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.35(7.80,14.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102.00(50.40,225.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107.80(53.20,255.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97.60(49.00,195.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal iron binding capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.70(40.30,51.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.33(38.90,51.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.40(41.65,51.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.21(1.23,6.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.19(0.98,7.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.28(1.63,6.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry weight(kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.75(51.00,67.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.75(50.50,66.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.75(52.50,67.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight growth rate(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.85(6.47,10.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.15(5.80,10.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.35(7.14,11.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of ACEI\\ARB\u003c/p\u003e \u003cp\u003eDrugs(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232,46.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87,38.84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e145,52.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcified heart valves(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150,33.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60,26.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90,32.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRisk factors associated with HK\u003c/h3\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, there are obvious differences in demographic and clinical characteristics between the normal serum potassium group and the hyperkalemia (HK) group. The median age of patients in the normal potassium cohort was 57.00 years, while those in the HK group had a median age of 58.00 years. Similarly, the median dialysis duration in the normal potassium group was 14.00 months, as opposed to 32.00 months in the HK group. These disparities in age and dialysis duration were statistically significant (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting potential associations with the development of hyperkalemia. The gender distribution also differed significantly between the two groups. The proportion of male patients in the HK group was 60.00%, which was notably lower than the 68.75% observed in the normal potassium group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This finding may imply a gender - related susceptibility to hyperkalemia. In terms of biochemical and clinical parameters, the HK group presented a distinct profile compared to the normal potassium group. Specifically, patients in the HK group had a longer dialysis duration (in months), along with significantly elevated levels of β2-microglobulin, albumin, triglycerides, creatinine, serum parathyroid hormone, phosphorus, and urea. Additionally, they exhibited a higher weight gain rate. Conversely, the Kt/v value, an important indicator of dialysis adequacy, was lower in the HK group. All these differences were statistically significant (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that these factors could play crucial roles in the pathogenesis of hyperkalemia. Regarding the use of ACEI/ARB drugs, the normal potassium group had a usage rate of 38.84%, while the HK group showed a significantly higher proportion of 52.73% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This disparity suggests a potential link between the use of these drugs and the occurrence of hyperkalemia. Lastly, when examining the prevalence of cardiac valve calcification, the percentages of affected patients were 26.79% in the normal potassium group and 32.73% in the HK group. However, this difference did not reach statistical significance (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that cardiac valve calcification may not be directly associated with hyperkalemia in this study population.\u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis was carried out with gender, dialysis duration, β2-microglobulin, triglyceride, albumin, creatinine, serum parathyroid hormone, phosphorus, urea, body weight growth rate, Kt/v, and the use of ACEI/ARB drugs as independent variables. The findings indicated that dialysis duration, creatinine and the use of ACEI/ARB drugs were independent risk factors for HK. In contrast, Kt/v and being male were independent protective factors for HK. The risk of HK in patients undergoing ACEI/ARB drug treatment was 3.79 times higher than that in those not receiving these drugs. Females were more prone to developing HK compared to males (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis of risk factors for HK in MHD patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026szlig;\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eWalk χ2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.253 (0.111\u0026ndash;0.577)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of ACEI/ARB drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.695(1.644\u0026ndash;8.308)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis duration(month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.021(1.011\u0026ndash;1.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKt/v\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.177(0.061\u0026ndash;0.520)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-Microglobulin(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.997(0.973\u0026ndash;1.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.035(0.955\u0026ndash;1.122)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.003(1.001\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglyceride (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.856(0.624\u0026ndash;1.175)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid Hormone (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.001(0.999\u0026ndash;1.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Phosphorus (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.462(0.761\u0026ndash;2.808)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum urea(\u0026micro;mol/L))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.046(0.997\u0026ndash;1.097)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight growth rate(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.054(0.941\u0026ndash;1.180)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eAnalysis of factors related to single and recurrent HK\u003c/h3\u003e\n\u003cp\u003eThe median ages of patients with single and recurrent hyperkalemia (HK) were 57.50 and 59.00 years, respectively. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the median dialysis durations for the two groups were 23.00 and 24.50 months. No statistically significant differences were found between the single - and recurrent - HK groups in these parameters (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of MHD patients with single HK and recurrent HK\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle HK(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;129)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecurrent HK (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ex\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/z\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77,59.69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88,60.27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.50(47.00,70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.00(46.00,66.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis duration(month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.00(4.00,68.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.50(5.00,66.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKt/v\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.39(1.04,1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.36(1.19,1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eURR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70.29(64.73,75.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.20(63.33,74.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ2-Microglobulin(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.08(24.4,39.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.11(24.20,39.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.65(35.2,40.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.25(36.70,41.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.10(2.11,2.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.36(1.67,2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06(0.83,1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.07(0.78,1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.77(3.08,4.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.85(3.25,4.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Calcium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.22(2.11,2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.25(2.13,2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e882.27(720.00,1172.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1002.00(815.00,1170.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParathyroid Hormone(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e183.50(110.00,311.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e225.50(120.00,396.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Phosphorus(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.99(1.62,2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.25(1.78,2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum urea(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.00(9.30,28.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.45(10.10,29.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric Acid(\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e441.37(332.00,502.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e439.79(369.00,515.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrealbumin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112.40(0.29,303.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37(0.31,299.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106.00(91.00,122.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114.00(96.00,125.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Iron(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.10(7.33,14.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.65(8.19,14.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83.50(42.80,209.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102.2(53.40,195.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal iron binding capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.80(41.40,50.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.30(42.00,51.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.20(1.16,6.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.41(2.14,6.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry weight(kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.15(54.00,70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.80(51.00,66.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight growth rate(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.49(5.80,10.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.62(7.81,12.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of ACEI/ARB drugs(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.00,53.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.00,52.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcified heart valves(n,%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.00,28.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.00,36.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe utilization rates of ACEI/ARB drugs in the two groups were 53.49% and 52.05%, and the prevalences of heart valve calcification were 28.68% and 36.60%, respectively. Similarly, no significant differences were noted in these indicators between the two groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, the recurrent-HK group had significantly higher serum albumin and phosphorus levels, as well as a higher body weight increase rate, than the single - HK group (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A multivariate logistic regression analysis with recurrent HK as the dependent variable was performed. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, albumin, phosphorus, and body weight increase rate were selected as independent variables. The results indicated that serum albumin concentration, phosphorus level, and weight gain rate were all independent risk factors for recurrent HK.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis of recurrent HK in MHD patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e\u0026szlig;\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eWalk χ2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum albumin(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.143(1.046\u0026ndash;1.249)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Phosphorus(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.331(1.167\u0026ndash;4.563)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight growth rate(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.163(1.038\u0026ndash;1.303)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between HK and MACEs in MHD patients\u003c/h2\u003e \u003cp\u003eAmong the 499 patients, 154 experienced MACEs during the observation period, with an overall MACE incidence of 30.86%. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, a total of 179 MACEs were documented among these 154 patients. On average, each patient with MACEs had 1.16 events. Specifically, 118 patients (76.62%) had a single cardiovascular event, 29 patients (18.83%) experienced two MACEs, and 7 patients (4.55%) had three MACEs. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows that among the 275 patients with hyperkalemia (HK), 98 developed MACEs during the observation period, resulting in a MACE incidence of 35.64%. In contrast, among the 224 patients with normal serum potassium levels, 56 patients had cardiovascular and cerebrovascular events, with a MACE incidence of 25.00%. The incidence of MACEs was significantly higher in patients with HK compared to those with normal serum potassium (χ\u0026sup2; = 6.545, P\u0026thinsp;=\u0026thinsp;0.011). Further analysis of the 275 HK patients indicated that 34 out of 129 patients with single-episode HK had MACEs during the observation period, with an incidence of 26.36%. In the 146 patients with recurrent HK, 64 experienced MACEs, and the incidence was 43.84%. The incidence of MACEs was significantly higher in patients with recurrent HK than in those with single - episode HK (χ\u0026sup2; = 9.122, p\u0026thinsp;=\u0026thinsp;0.003). When HK was defined as a serum potassium level\u0026thinsp;\u0026ge;\u0026thinsp;5.0 mmol/L, the odds ratios (ORs) of MACEs in HK patients were 1.661 (95% confidence interval [CI]: 1.124\u0026ndash;2.454, p\u0026thinsp;=\u0026thinsp;0.011) in the unadjusted analysis and 1.535 (95% CI: 1.017\u0026ndash;2.318, p\u0026thinsp;=\u0026thinsp;0.04) in the adjusted analysis, compared with patients having normal potassium levels. Throughout the entire study period, both the unadjusted and adjusted ORs increased gradually as the serum potassium level rose. The adjusted OR reached 1.598 (95% CI: 1.046\u0026ndash;2.439, p\u0026thinsp;=\u0026thinsp;0.030) when the serum potassium concentration was \u0026ge;\u0026thinsp;5.5 mmol/L and further increased to 1.823 (95% CI: 1.027\u0026ndash;3.236, p\u0026thinsp;=\u0026thinsp;0.040) when the serum potassium concentration was \u0026ge;\u0026thinsp;6.0 mmol/L.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMACEs and hospitalization rates in patients with different frequencies of HK\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eMACEs(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eHospitalization(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;311)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eratio (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eratio (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eχ2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal potassium group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e55.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHK group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle HK group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e62.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurrent HK group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e72.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between elevated serum levels and MACEs and hospitalization in MHD patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBlood potassium levels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eMACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eHospitalization\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eunadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eadjusted\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eunadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eAdjusted\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eOR(95%CI)\u003c/em\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5.0(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.661(1.124\u0026ndash;2.454)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.535(1.017\u0026ndash;2.318)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.655(1.149\u0026ndash;2.385)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.541(1.014\u0026ndash;2.342)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5.5(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.678(1.111\u0026ndash;2.534)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.598(1.046\u0026ndash;2.439)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.962(1.275\u0026ndash;3.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.887(1.187\u0026ndash;2.537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;6.0(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.987(1.139\u0026ndash;3.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.823(1.027\u0026ndash;3.236)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.546(1.312\u0026ndash;4.942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.083(1.039\u0026ndash;4.177)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003e Adjusted for age, Dialysis duration, use of ACEI/ARB drugs and cardiac valve calcification.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e Adjusted for age, Dialysis duration, use of ACEI/ARB drugs, cardiac valve calcification and kt\\v.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e Corresponds to MACEs and hospitalization risk for elevated serum potassium relative to normal potassium in MHD patients\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eThe potassium values used for classification were based on a single measurement of blood potassium values\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between HK and hospital admission in MHD patients\u003c/h2\u003e \u003cp\u003eAmong the 499 patients, 311 patients were hospitalized for various reasons during the observation period, the hospitalization rate was 62.32%. Among the hospitalized patients, the average number of hospitalizations was 1.96, of which 145 patients (46.62%) were hospitalized once. 91 patients (29.26%) were hospitalized 2 times, 45 patients (14.47%) were hospitalized 3 times, and 30 patients were hospitalized more than 3 times. Of the 275 patients with HK, 186 were hospitalized during the observation period (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), and the hospitalization rate was 67.64%. Among the 224 patients with normal blood potassium levels, 125 patients were hospitalized during the observation period, the hospitalization rate was 55.80%, and the hospitalization rate of HK patients was higher than that of patients with normal blood potassium levels (χ\u0026sup2;=7.353, P\u0026thinsp;=\u0026thinsp;0.007). Further analysis of 275 patients with HK revealed that 80 of 129 patients with single HK were hospitalized during the observation period, for a hospitalization rate of 62.02%. Among the 146 patients with recurrent HK, 106 patients were hospitalized during the observation period, and the hospitalization rate was 72.60%, but there was no significant difference in the hospitalization rate between single HK patients and recurrent HK patients (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Compared with the normal potassium group, the ORs for hospitalization in serum potassium\u0026thinsp;\u0026ge;\u0026thinsp;5.0 group were 1.655 (95% CI 1.149\u0026ndash;2.385, p\u0026thinsp;=\u0026thinsp;0.007) and 1.541 (95% CI 1.014\u0026ndash;2.342, p\u0026thinsp;=\u0026thinsp;0.043) in the unadjusted and adjusted analyses, respectively. During the whole study period, With the increase of serum potassium level, the OR continued to rise, reaching to 1.887(95% CI 1.187\u0026ndash;2.537, p\u0026thinsp;=\u0026thinsp;0.007) and 2.083 (95% CI 1.039\u0026ndash;4.177, p\u0026thinsp;=\u0026thinsp;0.039) when the serum potassium level was \u0026ge;\u0026thinsp;5.5 mmol/L and \u0026ge;\u0026thinsp;6.0 mmol/L, respectively. (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHK was a serious electrolyte disturbances and was associated with sudden cardiac death and fatal arrhythmias[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Under normal conditions, the serum potassium concentration was strictly regulated by redundant homeostatic mechanisms and was maintained within a narrow range of 3.5-5.0 mmol/L[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Once these homeostatic mechanisms were disrupted, potassium abnormalities may occur. With increasing serum potassium concentrations, the risk of adverse outcomes increased substantially, which made HK a medical emergency that needs special attention[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this retrospective investigation, a 4-year follow-up was conducted on 499 MHD patients to explore the prevalence of hyperkalemia (HK) and evaluate its recurrence rate. Additionally, the correlations between HK and the risks of MACEs as well as hospitalization in MHD patients were analyzed. In our research, The pre-dialysis serum potassium was measured 1812 times, with an average of 3.63 measurements per patient. Serum potassium levels were \u0026ge;\u0026thinsp;5.0 mmol/L in 517 cases (28.53%). Among the 499 patients, 224 (44.89%) had normal serum potassium levels, and 275 (55.11%) had hyperkalemia. The report published by the DOOPS study indicated that the prevalence of hyperkalemia in MHD patients was 30%-50%[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which was largely consistent with the findings of this study. Research by Tsiaigka et al. on the incidence of hyperkalemia in MHD patients showed that the prevalence of pre-dialysis serum potassium levels\u0026thinsp;\u0026ge;\u0026thinsp;5.1 mmol/L was as high as 60.4%, and the prevalence of pre-dialysis serum potassium levels\u0026thinsp;\u0026ge;\u0026thinsp;5.5 mmol/L reached 42.2%, which was higher than the incidence of HK found in this study[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study cohort, 57.53% and 38.27% of the patients experienced recurrence, with a second and third laboratory K⁺ value reaching or exceeding 5.0 mmol/L, respectively. Among the 275 patients with hyperkalemia, 129 had single-episode hyperkalemia, constituting 46.90% of the total hyperkalemia patient population. Meanwhile, 146 patients had recurrent hyperkalemia, accounting for 53.09%. Among those with recurrent hyperkalemia, the maximum number of hyperkalemia episodes was 6 times, with 2 patients representing 1.37% of the total recurrent hyperkalemia patient group. There were 62 patients (42.47%) who had 3 or more episodes, and 84 patients (57.53%) who had 2 episodes. These findings imply that a significant number of MHD patients might not be receiving optimal treatment for HK, highlighting the necessity for more extensive clinical efforts to enhance potassium homeostasis in MHD patients.\u003c/p\u003e \u003cp\u003eIn the study population under our investigation, it was observed that the risk of pre-dialysis HK in females was 3.95-fold higher compared to that in males. This result was in line with the findings of a prior study on MHD patients, which demonstrated a significantly elevated prevalence of pre-dialysis HK among women[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, Kim T et al. also observed gender differences in hyperkalemia among African-Americans and Caucasians, indicating that female hemodialysis patients were more likely to develop hyperkalemia[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Nevertheless, the underlying mechanism responsible for the increased susceptibility of females to hyperkalemia remains elusive. Potential factors might encompass variations in dietary potassium ingestion, dialysis session duration, as well as the efficacy of potassium ion elimination [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This demanded further investigation to fully elucidate the underlying mechanisms.\u003c/p\u003e \u003cp\u003eMHD patients with HK were found to have a longer dialysis duration. One potential explanation for the lower prevalence of pre-dialysis HK in patients with shorter dialysis durations might be that these patients were newly initiated maintenance hemodialysis; their kidneys still retained part of their renal function, although these residual renal functions were very small (less than 10% of their normal function), not enough to maintain life, but they still played a substantial role in the removal of toxins and excess water in the patient's body, as well as the maintenance of electrolytes and acid-base balance. Our findings were consistent with those of a study conducted in the United States. Notably, this study also found an association between hyperkalemia and deterioration of residual kidney function in MHD patients[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, when contrasted with patients who had undergone dialysis for an extended period, MHD patients with shorter dialysis histories exhibited a lower propensity for developing HK.\u003c/p\u003e \u003cp\u003eKT/V was a crucial indicator for evaluating the adequacy of dialysis. A low KT/V indicated a reduced capacity of dialysis to eliminate solutes[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Potassium, as a major extracellular cation, was one of the important solutes that need to be removed during dialysis. When dialysis was inadequate, renal replacement therapy fails to effectively excrete the excessive potassium ions from the body. Consequently, in our study, we found that hemodialysis patients with a low KT/V are prone to hyperkalemia.\u003c/p\u003e \u003cp\u003eOur study also revealed that the risk of HK in patients treated with ACE inhibitors or ARBs was 3.792 times greater than that in patients not treated with these drugs. This finding was consistent with prior studies that reported that HK was common among CKD patients who used ACEIs or ARBs[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The explanation for this phenomenon was that ACEI drugs inhibited the activity of angiotensin-converting enzyme (ACE), thus reducing the production of angiotensin II and subsequently suppressing the activity of the renin-angiotensin-aldosterone system (RAAS)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Since the sodium-retaining and potassium-excreting function of aldosterone was inhibited, the excretion of potassium decreased and the serum potassium level rose, which potentially led to hyperkalemia.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, it was discovered that HK was independently correlated with a heightened risk of MACEs and hospitalizations. These results align with those of multiple previous studies, which indicated an association between HK and an elevated risk of lethal cardiac arrhythmias among dialysis patients.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Subsequently, our aim was to ascertain whether there existed evidence indicating a graded correlation between the serum potassium level and both MACEs as well as hospitalization.\u003c/p\u003e \u003cp\u003eIn the course of this study, it was observed that elevated serum potassium levels (\u0026ge;\u0026thinsp;5.0, \u0026ge;\u0026thinsp;5.5, or \u0026ge;\u0026thinsp;6.0 mmol/L, contingent upon the specific outcome under consideration) were independently linked to a heightened risk of MACEs and hospitalization. As anticipated, we determined that escalating serum potassium levels were associated with an augmented risk of MACEs and hospitalization, with 5.0 mmol/L, 5.5 mmol/L, and 6.0 mmol/L serving as the crucial threshold values. While HK represents a significant burden due to its contribution to an increased likelihood of adverse clinical outcomes and mortality, diverse definitions of HK have been implemented. For instance, Iseki et al. defined HK as a serum potassium concentration of \u0026ge;\u0026thinsp;5.5 mmol/L and reported a greater risk of death in comparison to a baseline concentration of \u0026lt;\u0026thinsp;3.5 mmol/L.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Kovesdy et al.[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], in a large observational study of a contemporary cohort of hemodialysis patients, reported that a serum potassium concentration of \u0026ge;\u0026thinsp;5.6 mmol/L was associated with an increased risk of all-cause and cardiovascular death.\u003c/p\u003e \u003cp\u003eIn our study population, we identified a graded association between HK and MACEs and hospitalization. We found that the risk becomes statistically significant at potassium concentrations of approximately 5.0 mmol/L, 5.5 mmol/L and 6.0 mmol/L. This may have clinical implications, as it could be a threshold at which clinicians should consider taking action or at which protocols designed to safeguard patients could be employed. However, given the association of HK with MHD patients and the elevated odds of MACEs and hospitalization associated with HK, this metabolic disturbance should be considered a disease-specific safety event. More work was needed to determine the extent to which alterations in disease management reduce the incidence of this patient safety indicator.\u003c/p\u003e \u003cp\u003eThe current study was subject to several limitations. Firstly, it was a retrospective study conducted at three centers, and the follow-up duration might not have been extensive enough to comprehensively assess the late outcomes of patients undergoing MHD. Secondly, due to constraints in sample size, the prevalence and incidence of HK exhibited considerable variability, which could be attributed to factors such as the target population and the potassium threshold employed to define it. Additionally, we were incapable of conducting subgroup analyses to explore the risk factors for HK among MHD patients. Future, larger-scale studies should take subgroups into account.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thanked all participants for their support and cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeitang Liao and Minhong Luo contributed to the conception and design of the work, data analysis and wrote the main manuscript text. Lili Zhang, Hongbo Ye, Ni Xu, Yinyang Liang, Lina Zhuang, Hao Li, Qianqian Han, Caiju Mo contributed to the acquisition of data. Ying ying Zhu contributed to data analysis. Qiongqiong Yang had drafted the work and substantively revised it. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Key Technologies R\u0026amp;D Program of Guangdong Province (No. 3552023B1111030004) and the National Science Foundation of China (No. 82270743).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study were available on request from the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Clinical Trial Ethics Committee of Sun Yat-sen Memorial Hospital .Informed consent was obtained from all individual participants included in the study. Laboratory data used in this study were extracted from routine examination files and analyzed retrospectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis section is not applicable in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSarnowski A, Gama RM, Dawson A, Mason H, Banerjee D. Hyperkalemia in Chronic Kidney Disease: Links, Risks and Management. Int J Nephrol renovascular disease. 2022;15:215\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpinowitz B, Fishbane S, Fukagawa M, Ford M, Guzman N, Rastogi A. Course of Hyperkalemia in Patients on Hemodialysis. Int J Nephrol. 2022;2022:6304571.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShibata S, Uchida S. Hyperkalemia in patients undergoing hemodialysis: Its pathophysiology and management. \u003cem\u003eTherapeutic apheresis and dialysis: official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy\u003c/em\u003e 2022, 26(1):3\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernier-Jean A, Wong G, Saglimbene V, Ruospo M, Palmer SC, Natale P, Garcia-Larsen V, Johnson DW, Tonelli M, Hegbrant J, et al. Self-Reported Physical Activity and Survival in Adults Treated With Hemodialysis: A DIET-HD Cohort Study. Kidney Int Rep. 2021;6(12):3014\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePantanowitz L. Drug-induced hyperkalemia. Am J Med. 2002;112(4):334\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang SH, Kim GO, Kim BY, Son EJ, Do JY. Effect of angiotensin-converting enzyme inhibitors versus that of angiotensin receptor blockers on survival in patients undergoing hemodialysis: a nationwide observational cohort study. Ren Fail. 2024;46(1):2313173.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahmud HA, Palmer BF. Management of Hyperkalemia in Renin-Angiotensin-Aldosterone System Inhibitor: Strategies to Maintain Chronic Kidney Disease Patients with Type II Diabetes on Therapy. Cardiorenal Med. 2024;14(1):191\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalmer BF. Regulation of Potassium Homeostasis. Clin J Am Soc Nephrology: CJASN. 2015;10(6):1050\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKashihara N, Kumeda Y, Higashino Y, Maeda Y, Kaneko Y, Kanai H, Taniguchi Y, Ishii T, Tomioka Y. Efficacy and safety of patiromer for non-dialysis and dialysis patients with hyperkalemia: the randomized, placebo-controlled and long-term study. \u003cem\u003eClinical and experimental nephrology\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh T, Alagasundaramoorthy S, Gregory A, Astor BC, Maursetter L. Low dialysis potassium bath is associated with lower mortality in end-stage renal disease patients admitted to hospital with severe hyperkalemia. Clin kidney J. 2021;14(9):2059\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClase CM, Carrero JJ, Ellison DH, Grams ME, Hemmelgarn BR, Jardine MJ, Kovesdy CP, Kline GA, Lindner G, Obrador GT et al. Potassium homeostasis and management of dyskalemia in kidney diseases: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. \u003cem\u003eKidney international\u003c/em\u003e 2020, 97(1):42\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHougen I, Leon SJ, Whitlock R, Rigatto C, Komenda P, Bohm C, Tangri N. Hyperkalemia and its Association With Mortality, Cardiovascular Events, Hospitalizations, and Intensive Care Unit Admissions in a Population-Based Retrospective Cohort. Kidney Int Rep. 2021;6(5):1309\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoppe LK, Muhlack DC, Koenig W, Carr PR, Brenner H, Schottker B. Association of Abnormal Serum Potassium Levels with Arrhythmias and Cardiovascular Mortality: a Systematic Review and Meta-Analysis of Observational Studies. Cardiovasc Drugs Ther. 2018;32(2):197\u0026ndash;212.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBianchi S, Aucella F, De Nicola L, Genovesi S, Paoletti E, Regolisti G. Management of hyperkalemia in patients with kidney disease: a position paper endorsed by the Italian Society of Nephrology. J Nephrol. 2019;32(4):499\u0026ndash;516.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaraboyas A, Zee J, Brunelli SM, Usvyat LA, Weiner DE, Maddux FW, Nissenson AR, Jadoul M, Locatelli F, Winkelmayer WC, et al. Dialysate Potassium, Serum Potassium, Mortality, and Arrhythmia Events in Hemodialysis: Results From the Dialysis Outcomes and Practice Patterns Study (DOPPS). Am J kidney diseases: official J Natl Kidney Foundation. 2017;69(2):266\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimitra Tsiagka PIG, Maria I, Pikilidou V, Vaios S, Roumeliotis C, Syrganis K, Mavromatidis S, Metallidis. Vassilios Liakopoulos, Pantelis E Zebekakis Prevalence, recurrence and seasonal variation of hyperkalemia among patients on hemodialysis. Int Urol Nephrol. 2022;54:2327\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgiro A, Duling I, Eudicone J, Davis J, Brahmbhatt YG, Cooper K. The prevalence of predialysis hyperkalemia and associated characteristics among hemodialysis patients: The RE-UTILIZE study. \u003cem\u003eHemodialysis international International Symposium on Home Hemodialysis\u003c/em\u003e 2022, 26(3):397\u0026ndash;407.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim T, Rhee CM, Streja E, Soohoo M, Obi Y, Chou JA, Tortorici AR, Ravel VA, Kovesdy CP, Kalantar-Zadeh K. Racial and Ethnic Differences in Mortality Associated with Serum Potassium in a Large Hemodialysis Cohort. Am J Nephrol. 2017;45(6):509\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaber T, Purohit S. Chronic Kidney Disease: Role of Diet for a Reduction in the Severity of the Disease. Nutrients 2021, 13(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabich JS, Dupuis L, Kalantar-Zadeh K, Joshi S. Hyperkalemia and Plant-Based Diets in Chronic Kidney Disease. Adv kidney disease health. 2023;30(6):487\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBansal S, Pergola PE. Current Management of Hyperkalemia in Patients on Dialysis. Kidney Int Rep. 2020;5(6):779\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArif Y, Wenziger C, Hsiung JT, Edward A, Lau WL, Hanna RM, Lee Y, Obi Y, Kovesdy CP, Kalantar-Zadeh K, et al. Association of serum potassium with decline in residual kidney function in incident hemodialysis patients. Nephrol dialysis transplantation: official publication Eur Dialysis Transpl Association - Eur Ren Association. 2022;37(11):2234\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeon J, Kim GO, Kim BY, Son EJ, Do JY, Lee JE, Kang SH. Effects of Kt/V(urea) on outcomes according to age in patients on maintenance hemodialysis. Clin kidney J. 2024;17(5):sfae116.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeon SJ, Whitlock R, Rigatto C, Komenda P, Bohm C, Sucha E, Bota SE, Tuna M, Collister D, Sood M, et al. Hyperkalemia-Related Discontinuation of Renin-Angiotensin-Aldosterone System Inhibitors and Clinical Outcomes in CKD: A Population-Based Cohort Study. Am J kidney diseases: official J Natl Kidney Foundation. 2022;80(2):164\u0026ndash;73. e161.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParikh RV, Nash DM, Brimble KS, Markle-Reid M, Tan TC, McArthur E, Khoshniat-Rad F, Sood MM, Zheng S, Pravoverov L, et al. Kidney Function and Potassium Monitoring After Initiation of Renin-Angiotensin-Aldosterone System Blockade Therapy and Outcomes in 2 North American Populations. Circulation Cardiovasc Qual outcomes. 2020;13(9):e006415.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva-Cardoso J, Brito D, Frazao JM, Ferreira A, Bettencourt P, Branco P, Fonseca C. Management of RAASi-associated hyperkalemia in patients with cardiovascular disease. Heart Fail Rev. 2021;26(4):891\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalabrese V, Cernaro V, Battaglia V, Gembillo G, Longhitano E, Siligato R, Sposito G, Ferlazzo G, Santoro D. Correlation between Hyperkalemia and the Duration of Several Hospitalizations in Patients with Chronic Kidney Disease. J Clin Med 2022, 11(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerraro PM, Bolignano D, Aucella F, Brunori G, Gesualdo L, Limido A, Locatelli F, Nordio M, Postorino M, Pecoits-Filho R, et al. Hyperkalemia excursions and risk of mortality and hospitalizations in hemodialysis patients: results from DOPPS-Italy. J Nephrol. 2022;35(2):707\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIseki K, Uehara H, Nishime K, Tokuyama K, Yoshihara K, Kinjo K, Shiohira Y, Fukiyama K. Impact of the initial levels of laboratory variables on survival in chronic dialysis patients. Am J kidney diseases: official J Natl Kidney Foundation. 1996;28(4):541\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKovesdy CP, Regidor DL, Mehrotra R, Jing J, McAllister CJ, Greenland S, Kopple JD, Kalantar-Zadeh K. Serum and dialysate potassium concentrations and survival in hemodialysis patients. Clin J Am Soc Nephrology: CJASN. 2007;2(5):999\u0026ndash;1007.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chronic kidney disease, maintenance hemodialysis, hyperkalemia, major adverse cardiovascular events, hospitalization","lastPublishedDoi":"10.21203/rs.3.rs-5952868/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5952868/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study aimed to investigate the prevalence, recurrence, and risk factors associated with serum potassium levels in patients undergoing maintenance hemodialysis (MHD), as well as to explore the correlation between hyperkalemia (HK) and adverse clinical outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cohort of 499 patients was enrolled in this study. Comprehensive data collection was performed,encompassing serum potassium levels, laboratory parameters, comorbid conditions, and medication regimens. The primary endpoints included major adverse cardiovascular events (MACEs), defined as a composite of hospitalizations for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, congestive heart failure, transient ischemic attack, or stroke. Secondary outcomes comprised all-cause hospitalizations. Both univariate and multivariate logistic regression analyses were conducted to identify risk factors associated with HK and its recurrence in MHD patients. Furthermore, the study evaluated the potential association between elevated serum potassium levels and the risk of MACEs or hospitalization events.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 499 MHD patients with 1812 records wereincluded in this analysis during the follow-up period of 4 years. The prevalence of HK, stratified by serum potassium thresholds of ≥5.0, ≥5.5, and ≥6.0 mmol/L, was 55.11%, 27.66%, and 11.62%, respectively. Recurrent HK, defined as at least two episodes of serum potassium ≥5.0 mmol/L, was observed in 53.09% of the hyperkalemia patients. Multivariate logistic regression models for HK revealed that gender, dialysis duration, Kt/v, creatinine and treatment with ACEI or ARB drugs were associated with increased serum potassium odds. Of the 275 patients with HK, 84 patients (30.55%) had recurrent HK twice and 62 patients (22.55%) had recurrent HK≥ 3 times. Albumin, phosphorus and the growth rate of body weight in the recurrent HK group were significantly higher than that in the single HK group. Serum potassium levels ≥ 5.0, ≥ 5.5 and ≥ 6.0 mmol/L were significantly associated with the rates of MACEs and hospitalization, respectively. When HK was defined as serum potassium level ≥ 5.0, the odds ratio (OR) of MACEs in HK was 1.535 (95 % CI 1.017-2.318, p = 0.041), The adjusted OR increased progressively as the serum potassium level gradually increased, reaching 1.598(95 % CI 1.046-2.439, p=0.030 ) for ≥ 5.5mmol/L, and 1.823 ( 95 % CI 1.027-3.236, p=0.040 ) for ≥ 6.0mmol/L. Compared with the normal potassium group, the OR for hospitalization in serum potassium ≥5.0 group were 1.541 (95% CI 1.014-2.342, p=0.043) after adjustment, and the adjusted OR value increased to 1.887 (95% CI 1.187-2.537, p=0.007) and 2.083 (95% CI 1.039-4.177, p=0.039) when the serum potassium level was ≥5.5 mmol/L and ≥6.0 mmol/L.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong MHD patients, the prevalence of pre-dialysis HK and its recurrence rate remained high. Elevated serum potassium levels were correlated with an augmented risk of MACEs and hospitalization in these patients. These research findings emphasized the crucial significance of implementing effective monitoring and management strategies to precisely control potassium levels in MHD patients.\u003c/p\u003e","manuscriptTitle":"Prevalence,Recurrence, Risk Factors and Adverse Clinical Outcomes of Hyperkalemia in Maintenance Hemodialysis Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 06:47:41","doi":"10.21203/rs.3.rs-5952868/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-21T07:30:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-10T14:09:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19115755129767905419169069300749410506","date":"2025-05-10T13:36:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T22:26:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82025305418495257038593942208656366565","date":"2025-04-14T07:05:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-14T06:56:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-10T06:16:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2025-03-28T23:28:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e943eca-0ecc-4c9b-a7d5-4977a5a50750","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:09:23+00:00","versionOfRecord":{"articleIdentity":"rs-5952868","link":"https://doi.org/10.1186/s12882-025-04454-z","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2025-10-16 15:57:59","publishedOnDateReadable":"October 16th, 2025"},"versionCreatedAt":"2025-04-17 06:47:41","video":"","vorDoi":"10.1186/s12882-025-04454-z","vorDoiUrl":"https://doi.org/10.1186/s12882-025-04454-z","workflowStages":[]},"version":"v1","identity":"rs-5952868","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5952868","identity":"rs-5952868","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}