Hyperkalemia is frequently encountered and associated with cardio-vascular mortality in chronic hemodialysis (HD) patients. While online hemodiafiltration (OL-HDF) is thought to offer clinical benefit over high-flux HD, the impact of convective clearance on intra-dialytic potassium removal is unknown.

Methods

Chronic dialysis patients undergoing outpatient HD or OL-HDF at a single center attached to a university hospital were recruited in a prospective observational study. Spent dialysate along with clinical and biological variables were collected during a single mid-week session.

Results

We included 141 patients, with 21 treated with HD and 120 with OL-HDF. Mean age was 65.7 ± 15.6 years with 87 (61.7%) men. Mean intra-dialytic potassium removal was 69.9 ± 34.2 mmol. Patients on OL-HDF and HD have similar intra-dialytic potassium removal, with mean values of 69.1 ± 34.2 and 74.3 ± 35.0, respectively. In multivariate analysis, factors associated with intra-dialytic potassium removal were (decreasing order of effect size): dialysate potassium (β −15.5, p < 0.001), pre-HD serum potassium (β 9.1, p < 0.001), and session time (β 7.8, p = 0.003). In OL-HDF patients, substitution flow was not associated with potassium removal.

Conclusion

In chronic dialysis patients, convective therapy provided by OL-HDF does not affect potassium removal when compared with high-flux HD. Moreover, the importance of convective volume is not associated with potassium clearance in OL-HDF. Overall, session length and serum-to-dialysate potassium gradient are the main determinants of potassium clearance regardless of dialysis modality. Those results should inform clinicians on the optimal therapy in chronic dialysis patients in the era of OL-HDF.

1 INTRODUCTION

Cardiovascular disease affects more than two-thirds of end-stage kidney disease (ESKD) patients receiving hemodialysis (HD) and remains the leading cause of mortality accounting for almost 50% of deaths in this population.^{1, 2} Hyperkalemia is frequent in HD patients with almost two-thirds of patients presenting with a serum potassium >5.5 mmol/L at least once a month.³ Hyperkalemia is itself a potentially life-threatening condition causing arrhythmias and sudden cardiac death and observational studies demonstrate a robust association between hyperkalemia and cardiovascular mortality.^3-5 When HD patients have minimal to absent residual kidney function, they rely almost exclusively on intra-dialytic clearance to maintain potassium homeostasis with marginal assistance from gastro-intestinal excretion.⁶ Consequently, key measures to manage hyperkalemia in HD patients are relatively limited and include restriction in dietary intake, prescription of potassium binders, modification of drugs that increase serum potassium concentration, and optimization of dialysis prescription. Among factors determining intra-dialytic potassium removal, serum-to-dialysate potassium gradient and session duration were shown to be of major influence.⁷ In contrary to sodium, where convection accounts for most of the intradialytic clearance, potassium removal is thought to largely depend on diffusion with convection only accounting for 5 to 15% of total mass balance.^7-9

Hemodiafiltration (HDF) is a dialysis technique that combines diffusive and convective clearances.¹⁰ Recently, the CONVINCE trial reported a lower risk of death from any cause with the use of post-dilution online HDF (OL-HDF) as compared to high-flux HD.¹¹ While the exact mechanisms for the beneficial effect of OL-HDF have not been fully elucidated, a dose–response effect of convection volumes, with higher volumes associating with lower risk of mortality, has been described in meta-analyses.¹² Among several putative factors, improvement of electrolyte mass balance with high convective volumes could potentially mediate those favorable outcomes.¹³ In regard to dialytic potassium removal, the effect of OL-HDF as compared to conventional HD is largely unknown and any assumption would rely solely on theoretical considerations. Namely, prior studies exploring this question have considered the convective clearance of potassium achieved by net ultrafiltration (UF) only, while data on the impact of large convective volumes offered by OL-HDF are non-existent.^{7, 8} Finally, theoretical concerns exist that potassium removal may be less efficient with OL-HDF as compared to high-flux HD owing to a reduction in diffusive gradient for small molecule.

Considering the major impact of potassium homeostasis on the health of ESKD patients, the central role of dialytic therapy in removing potassium and the recent accumulation of evidence in favor of OL-HDF, we conducted a prospective observational study to characterize the impact of convective therapy on potassium clearance in chronic dialysis patients.

2 METHODS

2.1 Participants and study design

We conducted a prospective cross-sectional observational study at a single dialysis center under the care of a university hospital (Royal Free Hospital, London, UK) between December 2021 and July 2023. We included adult ESKD patients undergoing routine outpatient chronic hemodialysis. Exclusion criteria were (i) age <18, (ii) cognitive impairment, (iii) unplanned hemodialysis initiation, and (iv) unable to provide written informed consent. Medical management and dialysis prescription were left to attending physician's discretion. Patients were grouped according to dialytic modality: high-flux HD or post-dilution OL-HDF. A single dialysis session per patient was considered.

2.2 Collection of variables

Samples were collected during the mid-week dialysis session. Patients comorbidities and relevant medical history were obtained from computerized medical records. Diabetes was defined based on the presence of related medications. Patients were dialyzed using Fresenius 5008H dialysis machines (Fresenius MC, Bad Homburg, Germany) with polysulfone high-flux dialyzers (Fresenius MC, Bad Homburg, Germany) and ultra-pure quality dialysis water. Dialysis sessions were tailored to achieve an equilibrated urea Kt/V of 1.4 when including residual kidney function. All patients were treated with a dialysate containing: acetate 3.0 mmol/L, bicarbonate 28 mmol/L, magnesium 0.5 mmol/L, and glucose 5.5 mmol/L. Dialysate calcium and potassium concentrations varied according to physician's prescription. Potential dialysate calcium concentrations were 1.0, 1.25, and 1.75 mmol/L, while potential dialysate potassium concentrations were 1.0, 2.0 and 3.0 mmol/L. Dialysate sodium was tailored according to physician's prescription. Dialysate temperature was set between 35° and 35.5°. When using HD, dialysate flow was set to 500 mL/min. When using OL-HDF, post-dilution reinjection was used while substitution fluid was generated online and derived from total dialysate flow so that effective dialysate flow was then equal to 500—substitution flow mL/min.¹⁰ In HD, total convection volume was equal to net UF volume. In OL-HFD, total convection volume was equal to net UF volume + substitution volume. No patient received insulin during or immediately prior to the dialysis session.

A line was attached to the waste dialysate drain with continuous collection of the spent effluent in a container during the entire session.¹⁴ At the end of the session, the spent effluent was thoroughly mixed and potassium concentration was measured. Intra-dialytic potassium removal (mmol) was defined as potassium “outflow”—potassium “inflow,” as follows:

K inflow = K dialysate conc \times 500 \times Session time / 1000

\begin{matrix} K outflow = K effluent conc \\ \times (500 \times Session time + Net UF volume) / 1000 \end{matrix}

where K inflow is given in mmol, K dialysate, and effluent concentrations are given in mmol/L, session time is given in min, net UF volume is given in mL, and 500 represents total dialysate flow in mL/min.

All analyses were conducted in a UK-accredited laboratory (United Kingdom Accreditation Services [UKAS]). Urea clearance (Kt/V) was calculated using standard methods. Dialysis prescriptions and session details were gathered from the TMon® electronic software (Fresenius MC, Bad Homburg, Germany).

2.3 Statistical analysis

Continuous variables are expressed as means ± standard deviation (SD) or median (interquartile range) according to distribution. Baseline characteristics were compared between HD and OL-HDF patients. Patient characteristics were compared using Student's t-test and chi-squared for continuous and categorical variables, respectively.

In statistical models, intra-dialytic potassium removal was considered as the dependent variable. Predictors of intra-dialytic potassium removal were characterized using univariate and multivariate linear regressions. Predictors were a priori specified based on prior scientific and theoretical knowledge as follows: dialysis modality (HD vs. OL-HDF), dialysis session time, dialysate potassium concentration, pre-HD serum potassium concentration, net UF volume, blood flow, dialyzer surface area, and pre-HD bicarbonate concentration.⁷ When considering only OL-HDF patients, substitution flow was considered instead of dialysis modality. Predictors were standardized to a mean value of 0 and a SD of 1 to allow direct comparison of effect sizes. Results are presented as β coefficient as well as associated 95% confidence intervals (CI) and p-values. A two-sided p-value <0.05 was considered significant in every analysis. Patients with missing values on considered covariates were excluded from the analyses, and no data were imputed. For linear regression models, normality of residuals was assessed with Q-Q plot, while homoscedasticity was assessed with residual versus fitted plot. Collinearity was tested using variance inflation factors. Statistical analyses were conducted using Stata version 17 (StataCorp, College Station, TX, USA).

2.4 Ethics

This study was approved by a UK National Research Ethics Committee (21/NI/0059) and was carried out in accordance with the Declaration of Helsinki (2013), with all patients providing written informed consent. All patient data were coded prior to analysis.

3 RESULTS

3.1 Baseline characteristics

The study cohort consisted of 155 patients. Among those, 10 had missing values on intra-dialytic potassium removal, while four had missing values on any a priori considered covariates. Eventually, 141 patients were thus included in the present study, with 21 patients on HD and 120 patients on OL-HDF.

We included 87 (61.7%) men with a mean age of 65.7 ± 15.6 years. Mean sessional intra-dialytic potassium removal was 69.9 ± 34.2 mmol. Participants’ characteristics are described according to dialysis modality in Table 1. As compared to HD, patients on OL-HDF had shorter dialysis vintage. By definition, substitution flow, substitution volume, and total convection volume were higher with OL-HDF, while effective dialysate flow was lower, as compared to HD. Pre-HD and post-HD serum potassium concentrations were similar between groups. Moreover, patients on OL-HDF and HD have similar intra-dialytic potassium removal, with mean values of 69.1 ± 34.2 and 74.3 ± 35.0, respectively (Figure 1). Other characteristics were similar between the dialysis modalities.

TABLE 1. Baseline characteristics (N = 141).

	HD (N = 21)	OL-HDF (N = 120)	p-value
Clinical
Age (years)	71.1 ± 14.1	64.7 ± 15.7	0.083
Gender (men)	12 (57.1%)	75 (62.5%)	0.641
Ethnicity (Caucasian)	10 (47.6%)	39 (32.5%)	0.110
BMI (kg/m²)	26.3 ± 6.5	26.5 ± 5.2	0.872
Diabetes (yes)	6 (28.5%)	47 (39.1%)	0.355
Dialysis
Vintage (months)	57 (31–93)	30.5 (18.5–59.5)	0.008
Session time (min)	200.3 ± 40.1	210.1 ± 29.1	0.182
Blood flow (mL/min)	289 ± 28	288 ± 31	0.947
Effective dialysate flow (mL/min)	500 ± 0	418 ± 22	<0.001
Substitution flow (mL/min)	0 ± 0	81 ± 22	<0.001
Substitution volume (L)	0 ± 0	17.1 ± 5.2	<0.001
Total convection volume (L)	1.3 ± 0.7	18.7 ± 5.4	<0.001
Net UF volume (mL)	1′347 ± 713	1′665 ± 853	0.110
Total effluent outflow (L)	101.5 ± 20.4	106.7 ± 15.0	0.167
Dialyzer surface (m²)	2.05 ± 0.34	1.95 ± 0.29	0.139
Dialysate potassium (mmol/L)	2 (1–2)	2 (1–2)	0.206
Urea Kt/V	1.11 ± 0.30	1.18 ± 0.27	0.303
Laboratory
Pre-HD potassium (mmol/L)	4.9 ± 0.9	4.9 ± 0.7	0.889
Post-HD potassium (mmol/L)	3.3 ± 0.3	3.4 ± 0.4	0.219
Effluent potassium (mmol/L)	2.2 ± 0.4	2.3 ± 0.4	0.436
Intra-HD potassium removal (mmol)	74.3 ± 35.0	69.1 ± 34.2	0.525
Pre-HD serum bicarbonate (mmol/L)	19.9 ± 2.5	20.4 ± 2.1	0.365

Note: Bold values correspond to p < 0.05.
Abbreviations: BMI, body mass index; HD, hemodialysis; OL-HDF, online hemodiafiltration; UF, ultrafiltration.

Details are in the caption following the image — **FIGURE 1**
Open in figure viewer PowerPoint

Intra-dialytic potassium removal (mmol) according to dialysis modality in univariate analysis (N = 141). [Color figure can be viewed at wileyonlinelibrary.com]

3.2 Intra-dialytic potassium removal: Impact of dialysis modality

We first analyzed the determinants of intra-dialytic potassium removal in the whole study cohort (Table 2).

TABLE 2. Determinants of intra-dialytic potassium removal (mmol) in multivariate analysis (N = 141).

	β	95% CI	p-value	β	95% CI	p-value
	Univariate			Multivariate
Dialysate potassium	−17.6	−22.6 to −12.7	<0.001	−15.5	−20.1 to −10.9	<0.001
Pre-HD serum potassium	12.2	6.9 to 17.6	<0.001	9.1	4.8 to 13.5	<0.001
Session time	11.7	6.4 to 17.0	<0.001	7.8	2.7 to 13.0	0.003
Pre-HD serum bicarbonate	5.4	−0.1 to 11.0	0.057	4.1	−0.2 to 8.4	0.066
Dialyzer surface	10.5	5.1 to 16.0	<0.001	3.5	−1.2 to 8.3	0.146
OL-HDF (as opposed to HD)	−5.1	−21.2 to 10.8	0.525	−2.2	−14.7 to 10.3	0.727
Blood flow	4.5	−1-1 to 10.1	0.115	1.1	−3.5 to 5.9	0.619
Net UF volume	7.2	1.5 to 12.8	0.012	−0.5	−5.7 to 4.7	0.844

Note: Continuous variables are standardized to a mean value of 0 and a SD of 1 to allow comparison of effect size. Variables are order in descending order of effect sizes based on multivariate analysis. Bold values correspond to p < 0.05.
Abbreviations: HD, hemodialysis; OL-HDF, online hemodiafiltration; UF, ultrafiltration.

In univariate analysis, the following variables were positively associated with intra-dialytic potassium removal: Session time, pre-HD serum potassium concentration, dialyzer surface area, and net UF volume. In contrast, dialysate potassium concentration was negatively associated with intra-dialytic potassium removal. OL-HDF (as opposed to HD), blood flow, and pre-HD serum bicarbonate concentration were not associated with intra-dialytic potassium removal.

In multivariate analysis, the following variables were positively associated with intra-dialytic potassium removal (decreasing order of effect size): Pre-HD serum potassium concentration and session time. In contrast, dialysate potassium concentration was negatively associated with intra-dialytic potassium removal. Finally, dialyzer surface area, pre-HD serum bicarbonate concentration, blood flow, net UF volume, and OL-HDF (as opposed to HD) were not associated with intra-dialytic potassium removal. The calculated R² for the multivariate model was 0.46. Variance inflation factors showed no significant collinearity. Intra-dialytic potassium removal according to dialysis modality (OL-HDF vs. HD) and session time in multivariate analysis is represented in Figure 2.

As pre-HD serum potassium concentration and dialysate potassium concentration were both significantly but oppositely associated with intra-dialytic potassium removal, they were combined in a single variable representing the serum-to-dialysate potassium gradient (i.e., pre-HD serum potassium concentration—dialysate potassium concentration). As expected, when replaced in the previous multivariate model, serum-to-dialysate potassium gradient was positively associated with intra-dialytic potassium removal (β 17.7, 95% CI 13.1 to 22.3, p < 0.001). Intra-dialytic potassium removal according to session time and serum-to-dialysate potassium gradient in multivariate analysis is presented in Figure 3.

These data indicate that the type of dialysis modality (OL-HDF as opposed to high-flux HD) is not associated with intra-dialytic potassium removal.

3.3 Intra-dialytic potassium removal: Impact of substitution flow

We next analyzed the determinants of intra-dialytic potassium removal in the sub-group of patients on OL-HDF treatment (Table 3).

TABLE 3. Determinants of intra-dialytic potassium removal (mmol) in OL-HDF patients in multivariate analysis (N = 120).

	β	95% CI	p-value	β	95% CI	p-value
	Univariate			Multivariate
Dialysate potassium	−17.5	−22.9 to −12.1	<0.001	−15.9	−21.1 to −10.7	<0.001
Pre-HD potassium	9.9	3.7 to 16.1	0.002	8.6	3.4 to 13.8	0.001
Session time	10.8	4.6 to 17.1	0.001	6.3	0.0 to 12.7	0.048
Dialyzer surface	10.3	4.1 to 16.5	0.001	4.3	−1.3 to 10.0	0.132
Pre-HD bicarbonate	3.5	−2.7 to 9.8	0.269	4.2	−0.9 to 9.4	0.108
Substitution flow	−6.7	−17.2 to 3.7	0.204	−3.2	−11.7 to 5.3	0.457
Blood flow	3.9	−1.9 to 9.9	0.190	1.9	−3.3 to 7.2	0.470
Net UF volume	6.1	0.1 to 12.2	0.046	−0.7	−6.5 to 4.9	0.785

Note: Continuous variables are standardized to a mean value of 0 and a SD of 1 to allow comparison of effect size. Variables are order in descending order of effect sizes based on multivariate analysis. Bold values correspond to p < 0.05.
Abbreviations: HD, hemodialysis; OL-HDF, online hemodiafiltration; UF, ultrafiltration.

In univariate analysis, the following variables were positively associated with intra-dialytic potassium removal: session time, pre-HD serum potassium concentration, dialyzer surface area, and net UF volume. In contrast, dialysate potassium concentration was negatively associated with intra-dialytic potassium removal. Finally, blood flow, substitution flow, and pre-HD serum bicarbonate concentration were not associated with intra-dialytic potassium removal.

In multivariate analysis, the following variables were positively associated with intra-dialytic potassium removal (decreasing order of effect size): Pre-HD serum potassium concentration and session time. In contrast, dialysate potassium concentration was negatively associated with intra-dialytic potassium removal. Finally, dialyzer surface area, pre-HD serum bicarbonate concentration, blood flow, net UF volume, and substitution flow were not associated with intra-dialytic potassium removal. The calculated R² for the multivariate model was 0.41. Variance inflation factors showed no significant collinearity. Intra-dialytic potassium removal according to substitution flow in multivariate analysis is represented in Figure 4A. An alternative representation also illustrating the effect of session time is given in Figure 4B.

These data indicate that substitution flow is not associated with intra-dialytic potassium removal in OL-HDF patients.

4 DISCUSSION

In this study, we characterized the impact of convective therapy on potassium clearance in chronic dialysis patients. While session length and dialysate to serum potassium gradient are the main determinants of intra-dialytic potassium removal, the type of dialysis modality (OL-HDF or high-flux HD) does not impact potassium clearance. Moreover, in patients on OL-HDF, higher convective volumes do not affect intra-dialytic potassium removal. These results provide new insights into the management of potassium balance in chronic dialysis patients in the era of OL-HDF therapy.

Data regarding the impact of convective clearance offered by HDF therapy on intra-dialytic potassium removal are non-existent. Among potential explanations for this knowledge gap is the fact that in-center HDF could not be implemented on a large scale in the United States owing to regulatory barriers imposed by the Food and Drug Administration (FDA).¹⁵ Similarly, while free of such restrictions, a minority of European patients only benefited from HDF therapy in the past decade.¹⁶ Following the recent publication of the CONVINCE trial and results from various meta-analyses, in-center HDF therapy could rapidly gain in popularity and characterization of potassium removal with this modality is essential.^{11, 17, 18} It is usually accepted that potassium removal largely depends on diffusive clearance with convection only accounting for 5 to 15% of total potassium mass balance.^7-9 These numbers, however, are derived from studies in which patients were treated with conventional HD therapy, and so convective clearance was represented by net ultrafiltration only. Such results are thus not informative in the setting of the larger convective volumes offered by OL-HDF in its standard form.¹² The present study was specifically designed to assess the convective clearance of potassium offered by OL-HDF as prescribed in a real-world setting in Western Europe. We found that OL-HDF did not affect intra-dialytic potassium removal when compared to HD therapy alone. This finding is to be compared with other biological markers measured in routine clinical care. Specifically, pre-HD and post-HD serum potassium concentrations as well as session urea Kt/V were not different when comparing HD to OL-HDF patients in our study. While seemingly expected, prior studies reported a clear dissociation between post-HD serum potassium concentrations, metrics of small solute clearance, and intra-dialytic potassium removal.^{7, 19-21} Consequently, our findings attest that potassium removal is not affected by the choice of dialysis modality beyond what would be apparent on usual markers of dialysis adequacy.

When investigating specifically patients on OL-HDF, we did not observe a dose–response effect of convective flow on potassium removal. It is here worth mentioning that generators used in our study were programmed so that substitution flow was derived online from dialysate flow with a set total flow of 500 mL/min. Consequently, as patients undergoing OL-HDF systematically had lower effective dialysate flow as compared to HD patients, a theoretical concern of decreased small solute clearance might arise. However, we not only show that urea Kt/V but also overall potassium removal is not affected by online dialysis flow derivation. Moreover, as convective flow was generated online from total dialysis flow, it is worth noting that OL-HDF therapy did not require additional water resources when compared to standard HD therapy. Overall, this provides incentive favoring high convective volumes when prescribing OL-HDF, as illustrated by the dose–response relationship with clinical outcomes highlighted in meta-analyses.¹²

Several factors have been recognized to influence intra-dialytic potassium removal in prior studies on standard HD treatment. Traditionally, pre-HD potassium concentration, potassium dialysate concentration, duration of dialysis session, and efficiency of the dialyzer have been regarded as significant predictors.²² Experimental studies have subsequently been designed to characterize those parameters. The dialysate potassium concentration was a key determinant of potassium removal in chronic HD patients successively exposed to dialysates containing 0, 1, or 2 mmol/L of potassium.²¹ Importantly, urea reduction ratio and urea Kt/V were not associated with intra-dialytic potassium removal suggesting that urea kinetic modeling does not reliably capture the magnitude of potassium removal.²¹ The favorable impact of time on small solute removal has been well established in chronic HD patients exposed to various session lengths while processing identical blood and dialysate volumes.^{19, 20} Here again, the improved solute removal offered by longer sessions was not associated with higher urea Kt/V, further illustrating potential limitations of those metrics.²⁰ Basile et al. more recently reviewed factors associated with intradialytic potassium mass balance in two distinct study protocols including 11 and 63 patients respectively undergoing standard HD treatment. Overall, they identified session duration and plasma-to-dialysate potassium concentration gradient as the only determinants of intra-dialytic potassium removal.⁷ In the present study, we confirm those findings with session time, pre-HD serum potassium concentration, and dialysate potassium concentration being the most important determinants of potassium removal. Thus, our results extend prior findings and confirm their applicability to OL-HDF patients in a real-word setting.

Finally, acid–base status has an intricate relationship with potassium repartition and balance during HD procedure.²³ Theoretically, correction of acidosis during dialysis could promote cellular uptake of potassium thereby decreasing its serum concentration but also its dialytic removal.²⁴ However, while a dialysis with a high bicarbonate dialysate was associated with a faster decline in serum potassium in a cross-over study, total potassium removal remained largely unaffected.²⁵ In our study, high pre-HD serum bicarbonate showed borderline association with increased intra-dialytic potassium removal in univariate analysis. This theoretically is consistent with lower cellular uptake and thus higher dialytic removal in alkalotic patients. However, in agreement with data from Basile et al., this relationship was not maintained in multivariate analysis confirming the clinically negligible role of acid–base status on potassium removal during dialysis.⁷

Readers must bear in mind certain limitations of our study. First, as dialysis treatment was tailored toward a total clearance accounting for residual kidney function, dialysis dose, and convective volumes observed in our study could be considered lower than what is usually targeted in OL-HDF. However, our data clearly show the absence of an association between substitution flow and potassium removal, thus rendering a significant effect of high convective volumes highly unlikely. Second, data were collected at a single time-point and our study focused on total intra-dialytic potassium clearance rather than removal kinetics during dialysis. Second, serum glucose was not included in data collection of this study, and we could not account for potential compartments shifts secondary to endogenous insulin secretion. However, as discussed, such shifts are likely to be of minor importance in this setting and no patient received peri-dialytic insulin in our study. Finally, data on colonic excretion of potassium and residual kidney function were not available. However, while an impact on chronic potassium homeostasis is possible, a direct effect of those variables on the intra-dialytic removal of potassium itself is highly unlikely. The main strength of our study comprises a relatively large sample size of patients undergoing HD and OL-HDF with comprehensive measurement of intra-dialytic potassium removal in a real-world setting.

5 CONCLUSION

We conducted a prospective observational study to characterize intra-dialytic potassium removal in OL-HDF as compared to high-flux HD in chronic dialysis patients. We observed that convective therapy provided by OL-HDF does not affect potassium removal when compared to high-flux HD. Regardless of dialysis modality, session length and serum-to-dialysate potassium gradient are the main determinants of potassium clearance. Moreover, in patients treated with OL-HDF, the importance of convective volume is not associated with potassium removal. Those results should inform clinicians on the optimal therapy in chronic dialysis patients in the era of OL-HDF.

AUTHOR CONTRIBUTIONS

DAJ analyzed the data, interpreted the results, and wrote the manuscript. RC and PK recruited patients and collected the data. AD designed the study, interpreted the results, and revised the manuscript.

ACKNOWLEDGMENTS

The authors have nothing to report. Open access funding provided by Universite de Geneve.

FUNDING INFORMATION

This study required no specific source of funding.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflicts of interest with the contents of this article.

Open Research

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Volume49, Issue2

February 2025

Pages 300-309

Impact of convective clearance on intra-dialytic potassium removal in chronic dialysis patients