The details of four measures of "equivalent" clearances based on urea that have been proposed to monitor hemodialysis adequacy are reviewed. These measures fall into two groups: one based on urea nitrogen generation rate divided by the time-averaged serum urea nitrogen concentration, and the other based on urea nitrogen generation rate divided by the average predialysis serum urea nitrogen concentration. After the original variants were proposed, a potential problem regarding relative weights of dialysis and residual kidney clearances was identified, and revised equivalent urea clearances were proposed that give a higher weight to residual kidney clearance relative to dialysis clearance. These measures suggest that the target dialysis dose should be set to achieve dialysis solute concentrations typically found in patients at the point of needing dialysis, e.g., with a glomerular filtration rate of around 10 mL/min, corresponding to a urea clearance of approximately 6 mL/min and a creatinine clearance of 14. Despite the theoretical attractiveness of equivalent urea clearances to monitor hemodialysis adequacy, their utility has not been conclusively demonstrated in observational studies of incremental or more frequent hemodialysis.

BACKGROUND:Studies suggest increased phosphate removal when using hemodiafiltration (HDF) compared with hemodialysis (HD), but a complete analytic comparison has not been reported. METHODS:We analyzed data from a 6-month prospective, multicenter, cross-sectional study that enrolled patients treated with high-flux HD or HDF and in whom residual kidney phosphate clearances (KrPhos) were measured. Modeling data and dietary survey data were available from 115 patients (59 treated with HD and 56 treated with HDF). RESULTS:Predialysis (midweek) serum phosphate values averaged 4.37 ± 1.00 and 4.60 ± 1.18 mg/dL in the HD and HDF groups (p = NS). Mean prescribed phosphate binder equivalent dose (PBED) (including zero values) was 3.33 ± 2.94 g/day in HD and 2.64 ± 2.68 g/day in HDF (p = 0.19). Mean modeled phosphate ingestion was similar in HD and HDF (911 ± 231 vs. 911 ± 300 mg/day, p = NS), but phosphate ingestion by dietary survey was higher in HDF vs. HD (1119 ± 520 vs. 801 ± 420 mg/day, p < 0.001). Mean predialysis serum phosphate values in patients with residual kidney function (defined as KrPhosWater > 1.0 mL/min) and anuric patients were similar (4.43 ± 0.73 vs. 4.50 ± 1.20 mg/dL, respectively), whereas mean prescribed PBED was lower in patients with KrPhosWater > 1.0 mL/min (1.83 ± 2.02 vs. 3.40 ± 2.96 g/day, p < 0.01). CONCLUSIONS:Predialysis serum phosphate is not always lower in patients treated with HDF compared with HD, and this can possibly be explained by a trend to a lower prescribed PBED and/or by a higher dietary phosphate intake.

The author describes his experience using several artificial intelligence programs to assist in the process of editing or preparing manuscripts for publication. While the programs were very useful to increase clarity and optimize the English of previously written text, problems arose when asked to review the literature to describe or expand on concepts, and then to cite references to support those statements. Citations were sometimes fabricated. The artificial intelligence program would even provide PubMed identification (PMID) numbers for references cited, which sometimes pointed to completely different publications. In references that were correctly cited, a request to extract data from their abstracts yielded data that were completely fabricated or incorrect. The newer versions of these artificial intelligence programs appear to be enormously helpful in helping with the process of scientific writing, but one needs to assiduously verify every statement made with regard to their interpretation of the medical literature and double-check any citations by retrieving and reading those references. Because statements made by these agents are proffered with great confidence and using excellent writing skills, the resulting errors can be difficult to anticipate. The motivations behind such errors are unknown, but appear to be related to a desire of AI to please the user at any cost. Programmers who create these tools somehow managed to allow such errors, and this issue must be addressed in future versions of AI. Also, it would help greatly if AI had access to the full text of medical scientific articles, which might be achieved by contractual agreements with the main medical publishers.

INTRODUCTION: Process evaluation provides insight into how interventions are delivered across varying contexts and why interventions work in some contexts and not in others. This manuscript outlines the protocol for a process evaluation embedded in a hybrid type 1 effectiveness-implementation randomised clinical trial of incremental-start haemodialysis (HD) versus conventional HD delivered to patients starting chronic dialysis (the TwoPlus Study). The trial will simultaneously assess the effectiveness of incremental-start HD in real-world settings and the implementation strategies needed to successfully integrate this intervention into routine practice. This manuscript describes the rationale and methods used to capture how incremental-start HD is implemented across settings and the factors influencing its implementation success or failure within this trial. METHODS AND ANALYSIS: We will use the Consolidated Framework for Implementation Research (CFIR) and the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) frameworks to inform process evaluation. Mixed methods include surveys conducted with treating providers (physicians) and dialysis personnel (nurses and dialysis administrators); semi-structured interviews with patient participants, caregivers of patient participants, treating providers (physicians and advanced practice practitioners), dialysis personnel (nurses, dieticians and social workers); and focus group meetings with study investigators and stakeholder partners. Data will be collected on the following implementation determinants: (a) organisational readiness to change, intervention acceptability and appropriateness; (b) inner setting characteristics underlying barriers and facilitators to the adoption of HD intervention at the enrollment centres; (c) external factors that mediate implementation; (d) adoption; (e) reach; (f) fidelity, to assess adherence to serial timed urine collection and HD treatment schedule; and (g) sustainability, to assess barriers and facilitators to maintaining intervention. Qualitative and quantitative data will be analysed iteratively and triangulated following a convergent parallel and pragmatic approach. Mixed methods analysis will use qualitative data to lend insight to quantitative findings. Process evaluation is important to understand factors influencing trial outcomes and identify potential contextual barriers and facilitators for the potential implementation of incremental-start HD into usual workflows in varied outpatient dialysis clinics and clinical practices. The process evaluation will help interpret and contextualise the trial clinical outcomes' findings. ETHICS AND DISSEMINATION: The study protocol was approved by the Wake Forest University School of Medicine Institutional Review Board (IRB). Findings from this study will be disseminated through peer-reviewed journals and scientific conferences. TRIAL REGISTRATION NUMBER: NCT05828823.

BACKGROUND:Knowledge of residual kidney function is potentially useful in patients receiving hemodialysis for risk stratification, adjusting the dialysis prescription, and early identification of renal function recovery. However, periodic urine collection is problematic. We examined the potential of predicting residual kidney creatinine (water) clearance (KrCrW) without urine collection using a creatinine kinetic model, which allows KrCrW to be estimated based on previously measured or anthropometrically estimated creatinine generation rate (GCr), volume of distribution (VdCr), and measured predialysis serum creatinine. METHODS:Studies were done in 12 patients receiving once weekly hemodialysis and 12 other patients being dialyzed twice a week in whom KrCrW was measured by collection of urine. GCr and VdCr were taken either from the modeling outputs or were estimated from anthropometric values. RESULTS:The mean modeled GCr was 1091 ± 377 (SD) mg/day, similar to the value predicted by an anthropometric equation suggested by Ix et al. (1198 ± 304). The mean kinetically modeled VdCr was 22.7 ± 2.4 L, somewhat lower than expected. The KrCrW from urine collection was 7.43 ± 4.07 mL/min. Predicted KrCrW from modeled GCr, modeled VdCr, and measured predialysis serum creatinine was similar (7.35 ± 4.01, r2 = 0.987) with an average error less than 1%. When anthropometric estimates of GCr and VdCr were used as inputs, the mean modeled KrCrW was somewhat higher (8.66 ± 4.27, y = 1.09x, R2 = 0.585) and the mean error was 1.23 ± 2.6 mL/min. CONCLUSIONS:Residual kidney creatinine clearance (KrCrW) can be estimated in patients receiving one or two dialysis treatments weekly based on creatinine kinetic modeling. Using anthropometric estimates of GCr and VdCr in the modeling equations yields similar values of KrCrW to those when modeled GCr and VdCr inputs are used, but with a substantial error. A strategy of using a baseline modeled values of GCr and VdCr for future KrCrW change prediction may be promising, but the stability of GCr over time needs to be confirmed.

Attention is increasingly turning toward the individualization of hemodialysis prescriptions through an incremental start. This approach prioritizes the patient's clinical needs over rigid metrics like dialysis urea depuration, begins with fewer sessions (1 or 2 per week), and gradually increases in frequency and/or duration based on the patient's evolving clinical condition. Clinical manifestations related to uremia are managed through a combination of residual kidney function, dialysis, dietary modification, and medications. Treatment adequacy is evaluated using clinical assessment, blood tests, and measurement of residual kidney function. Many observational studies and a number of pilot trials have shown that clinical outcomes with incremental-start hemodialysis are not inferior to the standard approach of hemodialysis initiation with 3 sessions per week. Consequently, some centers have adopted incremental-start hemodialysis as routine care. However, most centers apply the standardized practice of thrice-weekly hemodialysis as soon as dialysis is introduced in patient care and afterward, regardless of the patient's individual characteristics. This article does not prescribe a specific approach but rather describes the current practice of incremental-start hemodialysis. We seek to advance the practice of incremental-start hemodialysis by addressing critical gaps in knowledge, practice models, and supportive infrastructure with a view to more widespread implementation. Drawing on the Consolidated Framework for Implementation Research, we identify foundational factors at individual, organizational, and systemic levels that need development to facilitate broader adoption. Finally, we propose actionable items to ensure that incremental-start hemodialysis becomes a viable, patient-centered option accessible to all who might benefit.

Introduction Process evaluation provides insight into how interventions are delivered across varying contexts and why interventions work in some contexts and not in others. This manuscript outlines the protocol for a process evaluation embedded in a hybrid type 1 effectiveness-implementation randomised clinical trial of incremental-start haemodialysis (HD) versus conventional HD delivered to patients starting chronic dialysis (the TwoPlus Study). The trial will simultaneously assess the effectiveness of incremental-start HD in real-world settings and the implementation strategies needed to successfully integrate this intervention into routine practice. This manuscript describes the rationale and methods used to capture how incremental-start HD is implemented across settings and the factors influencing its implementation success or failure within this trial.Methods and analysis We will use the Consolidated Framework for Implementation Research (CFIR) and the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) frameworks to inform process evaluation. Mixed methods include surveys conducted with treating providers (physicians) and dialysis personnel (nurses and dialysis administrators); semi-structured interviews with patient participants, caregivers of patient participants, treating providers (physicians and advanced practice practitioners), dialysis personnel (nurses, dieticians and social workers); and focus group meetings with study investigators and stakeholder partners. Data will be collected on the following implementation determinants: (a) organisational readiness to change, intervention acceptability and appropriateness; (b) inner setting characteristics underlying barriers and facilitators to the adoption of HD intervention at the enrollment centres; (c) external factors that mediate implementation; (d) adoption; (e) reach; (f) fidelity, to assess adherence to serial timed urine collection and HD treatment schedule; and (g) sustainability, to assess barriers and facilitators to maintaining intervention. Qualitative and quantitative data will be analysed iteratively and triangulated following a convergent parallel and pragmatic approach. Mixed methods analysis will use qualitative data to lend insight to quantitative findings. Process evaluation is important to understand factors influencing trial outcomes and identify potential contextual barriers and facilitators for the potential implementation of incremental-start HD into usual workflows in varied outpatient dialysis clinics and clinical practices. The process evaluation will help interpret and contextualise the trial clinical outcomes’ findings.Ethics and dissemination The study protocol was approved by the Wake Forest University School of Medicine Institutional Review Board (IRB). Findings from this study will be disseminated through peer-reviewed journals and scientific conferences.Trial registration number NCT05828823.

BACKGROUND:Most patients starting chronic in-center hemodialysis (HD) receive conventional hemodialysis (CHD) with three sessions per week targeting specific biochemical clearance. Observational studies suggest that patients with residual kidney function can safely be treated with incremental prescriptions of HD, starting with less frequent sessions and later adjusting to thrice-weekly HD. This trial aims to show objectively that clinically matched incremental HD (CMIHD) is non-inferior to CHD in eligible patients. METHODS:An unblinded, parallel-group, randomized controlled trial will be conducted across diverse healthcare systems and dialysis organizations in the USA. Adult patients initiating chronic hemodialysis (HD) at participating centers will be screened. Eligibility criteria include receipt of fewer than 18 treatments of HD and residual kidney function defined as kidney urea clearance ≥3.5 mL/min/1.73 m2 and urine output ≥500 mL/24 h. The 1:1 randomization, stratified by site and dialysis vascular access type, assigns patients to either CMIHD (intervention group) or CHD (control group). The CMIHD group will be treated with twice-weekly HD and adjuvant pharmacologic therapy (i.e., oral loop diuretics, sodium bicarbonate, and potassium binders). The CHD group will receive thrice-weekly HD according to usual care. Throughout the study, patients undergo timed urine collection and fill out questionnaires. CMIHD will progress to thrice-weekly HD based on clinical manifestations or changes in residual kidney function. Caregivers of enrolled patients are invited to complete semi-annual questionnaires. The primary outcome is a composite of patients' all-cause death, hospitalizations, or emergency department visits at 2 years. Secondary outcomes include patient- and caregiver-reported outcomes. We aim to enroll 350 patients, which provides ≥85% power to detect an incidence rate ratio (IRR) of 0.9 between CMIHD and CHD with an IRR non-inferiority of 1.20 (α = 0.025, one-tailed test, 20% dropout rate, average of 2.06 years of HD per patient participant), and 150 caregiver participants (of enrolled patients). DISCUSSION:Our proposal challenges the status quo of HD care delivery. Our overarching hypothesis posits that CMIHD is non-inferior to CHD. If successful, the results will positively impact one of the highest-burdened patient populations and their caregivers. TRIAL REGISTRATION:Clinicaltrials.gov NCT05828823. Registered on 25 April 2023.

Background A kinetic model for beta-2-microglobulin removal and generation was used to explore the impact of adding hemodiafiltration on predialysis and time-averaged serum values. Methods The model was tested on data from the HEMO study and on a sample of patients undergoing high-flux hemodialysis. The impact of hemodiafiltration on beta-2-microglobulin levels was evaluated by modeling four randomized studies of hemodiafiltration versus hemodialysis. The impact of residual kidney function on beta-2-microglobulin was tested by comparing results of previously reported measured data with model predictions. Results In the low-flux and high-flux arms of the HEMO study, measured median beta-2-microglobulin reduction ratios could be matched by dialyzer clearances of 5.9 and 29 ml/min, respectively. Median predialysis serum beta-2-microglobulin levels were matched if generation rates of beta-2-microglobulin were set to approximately 235 mg/d. In another group of patients treated with dialyzers with increased beta-2-microglobulin clearances, measured cross-dialyzer clearances (57 +/- 28 ml/min) were used as inputs. In these studies, the kinetic model estimates of intradialysis and early postdialysis serum beta-2-microglobulin levels were similar to median measured values. The model was able to estimate the changes in predialysis serum beta-2-microglobulin in each of four published randomized comparisons of hemodiafiltration with hemodialysis, although the model predicted a greater decrease in predialysis serum beta-2-microglobulin with hemodiafiltration than was reported in two of the studies. The predicted impact of residual kidney clearance on predialysis serum beta-2-microglobulin concentrations was similar to that reported in one published observational study. Modeling predicted that postdilution hemodiafiltration using 25 L/4 hours replacement fluid would lower serum time-averaged concentration of beta-2-microglobulin by about 18.2%, similar to the effect of 1.50 ml/min residual kidney GFR. Conclusions A two-pool kinetic model of beta-2-microglobulin yielded values of reduction ratio and predialysis serum concentration that were consistent with measured values with various hemodiafiltration and hemodialysis treatment regimens.

This special article describes the achievements and impact of Dr. Todd Siu-Toa Ing, MBBS, (1933-2023) on the field of nephrology as recounted by a colleague from Hong Kong, a U.S. nephrologist ex-trainee, and the daughter of an important mentor. Dr. Ing was a founding member of the International Society for Hemodialysis. He made important discoveries regarding the diagnosis of renal tubular acidosis and electrolyte transport in the gastrointestinal tract and published many innovative findings relating to peritoneal and hemodialysis. He was especially interested in nephrology and dialysis education and was co-editor of a Handbook of Dialysis that has been in publication in five editions since 1988 with translation into many foreign languages. Dr. Ing was very supportive of nephrology in China as well as Chinese nephrologists practicing in the United States, and was a founding member of the Chinese American Society of Nephrology.

It is well known that some degree of preserved residual kidney function (RKF) in end-stage kidney disease (ESKD) patients is associated with higher rates of survival.1Termorshuizen F, Dekker FW, van Manen JG, Korevaar JC, Boeschoten EW, Krediet RT; NECOSAD Study Group. Relative contribution of residual renal function and different measures of adequacy to survival in hemodialysis patients: an analysis of the Netherlands Cooperative Study on the Adequacy of Dialysis (NECOSAD)-2. J Am Soc Nephrol. 2004 Apr;15(4):1061-1070. doi: 10.1097/01.asn.0000117976.29592.93. PMID: 15034110.Google Scholar,2Vilar E. Wellsted D. Chandna S.M. Greenwood R.N. Farrington K. Residual renal function improves outcome in incremental haemodialysis despite reduced dialysis dose.Nephrol Dial Transplant. 2009 Aug; 24 (Epub 2009 Feb 24. PMID: 19240122): 2502-2510https://doi.org/10.1093/ndt/gfp071Crossref PubMed Scopus (121) Google Scholar Also, it has been demonstrated that loss of residual kidney function is associated with a high mortality rate.3Obi Y, Rhee CM, Mathew AT, Shah G, Streja E, Brunelli SM, Kovesdy CP, Mehrotra R, Kalantar-Zadeh K. Residual Kidney Function Decline and Mortality in Incident Hemodialysis Patients. J Am Soc Nephrol. 2016 Dec;27(12):3758-3768. doi: 10.1681/ASN.2015101142. Epub 2016 May 11. PMID: 27169576; PMCID: PMC5118484.Google Scholar There are several questions in this area that have remain unanswered: 1) is the reduced mortality with RKF seen with all-cause deaths or is the association limited to deaths due to cardiovascular disease or infection? Is the presence of RKF associated with reduction in sudden cardiac deaths? 2) what is the “dose-response” relationship between the level of RKF and survival benefit? ; 3) what are the possible mechanisms for the higher survival rate when RKF is present? Is there lowering of cardiovascular stress because of the lower ultrafiltration rates typically seen in patients with RKF? Do patients with RKF have a lesser degree of fluid overload than their anuric counterparts? Is the survival benefit of RKF linked to less exposure to very high levels of serum potassium and phosphate, each of which has been associated with mortality, and in the case of potassium, with sudden death? 4) does presence of RKF allow for a more liberal diet, leading to improved nutrition and a lower prevalence of protein-energy wasting?, and 5) does increased removal by RKF of high molecular weight and protein-bound uremic toxins meaningfully lower serum levels and thereby reduce inflammation and mitigate other pathology involved in the uremic syndrome? No one study can answer all of these questions, but the observational study by Okazaki and colleagues4Okazaki M. Obi Y. Shafi T. Rhee C.M. Kovesdy C.P. Kalantar-Zadeh K. Residual kidney function and cause-specific mortality among incident hemodialysis patients.Kidney Int Rep. 2023; (in press)Abstract Full Text Full Text PDF Google Scholar published in this issue of Kidney International Reports provides important and useful new insights. These investigators were able to identify 39,000 incident hemodialysis patients in whom residual kidney clearance of urea and urine volume had been measured approximately 60 days after starting hemodialysis. In one-third, repeat measurements were available, allowing for assessment of associations between the extent of decline in RKF or urine volume (over a 6-month period after enrollment) and mortality . Okazaki et al confirmed multiple previous reports, showing that death rate was lower in patients who had retained some residual kidney clearance of urea at baseline. This survival association was seen with non-cardiovascular deaths as well as with sudden cardiac deaths (SCD) and with non-SCD cardiovascular deaths. With respect to a “dose-response” relationship for these associations, for non-cardiovascular deaths, the data suggested a monotonically higher death rate in subgroups with renal clearance of urea below 6 ml/min per 1.73 m2, with a more pronounced higher death rate when this value was below 1.5. A plethora of adjustments, including case-mix, ultrafiltration rate, and a packet of laboratory values had little affect on the observed “dose-response” association. For SCD and non-SCD cardiovascular deaths, the dose-response relationship between renal urea clearance at baseline and mortality risk depended strongly on whether an adjustment for “laboratory values” was made. These included the normalized protein catabolic rate (nPCR), predialysis blood hemoglobin, and predialysis serum levels of albumin, creatinine, phosphorus, iron saturation, bicarbonate, alkaline phosphatase, and ferritin, as well as the highest predialysis serum potassium level measured during the initial 3-month observation period. Body mass index was included in the “laboratory values” adjustment packet. Adjustment for ultrafiltration rate did not seem to affect any of the renal urea clearance vs. mortality dose-response relationships, whether or not the packet of laboratory values was included. If the “laboratory values” adjustments were excluded, the dose-response relationship between renal clearance of urea and cardiovascular deaths seemed to differ slightly from that observed with non-cardiovascular deaths. Compared to patients with renal urea clearance >6.0 ml/min per 1.73 m2, the non-cardiovascular death rate was already higher when renal urea clearance was less than 6.0, whereas for non-sudden (non-SCD) cardiovascular deaths, the risk of death was higher only in the subgroups with renal urea clearance below 1.5 ml/min per 1.73 m2. For sudden cardiac death (SCD) the death risk was higher in subgroups with renal urea clearances below 3.0 (including those in the 1.5–3.0 ml/min range). The authors then did a similar “dose-response” analysis for the three categories of cause-specific mortality vs. daily urine volume. Here mortality risk seemed to be higher in subgroups in whom daily urine volume was below 900 ml/day. Results were similar for non-cardiovascular death, SCD, and non-SCD cardiovascular death. When examining the effect of a change in urine volume over the 6-month period after enrollment, and increase in urine volume was associated with a reduced death risk for all 3 mortality categories, while a reduction in urine volume was associated with increase in death risk for non-cardiovascular death and for SCD, while for non-SCD cardiovascular death, a reduction in urine volume was not clearly associated with increased risk of death. When trying to analyze mechanistic variables, including ultrafiltration rate, nutrition, potassium, and phosphate, the study made several interesting observations. In their supplemental data table S4, ultrafiltration rate, nPCR, and serum potassium and phosphorus are compared in subgroups based on different levels of daily urine output at baseline. The renal clearances of urea tracked daily urine output, as expected. One of the potential “benefits” of a high daily urine volume is a lower ultrafiltration rate during dialysis. When a given volume of fluid is ingested or generated from food during the week, fluid excreted by the kidneys no longer has to be removed during dialysis and the ultrafiltration rate is proportionately lowered. In this S4 data table, we see that in the subgroup with urine output was < 300 ml/day, ultrafiltration rate averaged 8.0 ml/hr per kg, whereas in the subgroup with urine output was > 1200 ml/day, the average ultrafiltration rate was only 6.5. Similar differences were found among the urine volume subgroups for values of weekday and weekend interdialytic weight gains. With regard to nutrition/ inflammation, serum albumin was slightly higher in the subgroups with higher daily urine output. The normalized protein catabolic rate was substantially higher in the subgroups with higher urine volume, averaging 0.80 g/kg per day when urine volume was < 300 ml/day, vs. 1.11 when urine volume was > 1200, with relatively monotonically increased catabolic rate value for the urine volume subgroups in between. One might have expected the predialysis serum potassium and phosphate values to be lower in the subgroups with higher urine volume, but they were not. Also, the incidences of high predialysis serum potassium levels (>6.0 or > 6.5 mmol/L) during the 3-month baseline period were similar in the different urine volume subgroups. The most logical explanation for this is, that patients in the subgroups with higher urine volume were eating more, and the increased food intake overrode any increased removal of potassium and phosphate due to residual kidney function. So, were the benefits of increased renal clearance of urea at baseline on subsequent survival mediated by ultrafiltration, nutrition, potassium, or phosphate? Adjusting the mortality analyses for baseline ultrafiltration rate or incidence of high baseline serum potassium levels did not meaningfully change the associations between baseline renal urea clearance and the 3 categories of mortality. In summary, the results of the study by Okazaki et al are primarily confirmatory and suggest a broad-based benefit of increased residual kidney function on survival. The association was not limited to a reduced rate of sudden cardiac deaths or of non-SCD cardiovascular deaths, but was as or more prominent with non-cardiovascular mortality. Slightly higher nPCR and serum albumin levels suggest that patients with higher RKF may have been somewhat healthier at the outset. The exact mechanism whereby residual kidney function reduces death risk remains incompletely defined, but most likely is related to reduced serum levels of potential uremic toxins as opposed to reduced need for ultrafiltration or reductions in incidence of hyperkalemia. Even small amounts of residual kidney function can substantially lower serum levels of higher molecular weight toxins such as beta-2-microglobulin5Vilar E, Boltiador C, Wong J, Viljoen A, Machado A, Uthayakumar A, Farrington K. Plasma Levels of Middle Molecules to Estimate Residual Kidney Function in Haemodialysis without Urine Collection. PLoS One. 2015 Dec 2;10(12):e0143813. doi: 10.1371/journal.pone.0143813. PMID: 26629900; PMCID: PMC4668015.Google Scholar as well as protein-bound uremic toxins, which are not well removed by hemodialysis. Future exploration of the role of RKF and urine volume on hard outcomes should ideally include measurement of serum levels such uremic toxins. Residual Kidney Function and Cause-Specific Mortality Among Incident Hemodialysis PatientsKidney International ReportsPreviewThe survival benefit of residual kidney function (RKF) in patients on hemodialysis is presumably due to enhanced fluid management and solute clearance. However, data are lacking on the association of renal urea clearance (CLurea) with specific causes of death. Full-Text PDF Open Access

Objectives: Substantial levels of residual renal clearance and urine output may occur in patients treated with hemodialysis or hemo-diafiltration. However, the relationships among residual renal urea, creatinine, and phosphate clearances, respectively, and between clearances and urine volume have not been well described. Methods: We performed a prospective, cross-sectional study which enrolled hemodialysis and hemodiafiltration patients with a urine volume of .100 mL/day, in whom at least 2 residual renal clearances were obtained over a 6-month observation period. Urine was collected for 24 hours prior to the midweek treatment session and concentrations of urea, creatinine, and phosphate were measured. Results: Thirty-eight patients (24 men, 14 women) with a mean age of 70.4 +/- 12.4 (SD) years were included in this analysis. All patients were dialyzed 3 times per week with mean treatment duration of 243 +/- 7.89 minutes. Twenty patients were undergoing hemodiafiltration and 18 patients high-flux hemodialysis. In total, 102 dialysis sessions, of which 52 were hemodiafiltration, and urine collections were analyzed. Mean urine volume was 457 +/- 254 mL per 24 hours. Residual renal clearance rates of urea (Kr Urea), creatinine (Kr Cr), and phosphate (Kr Phos) were 1.60 +/- 0.979, 4.69 +/- 3.79, and 1.98 +/- 1.36 mL/minute, respectively. Mean ratios of Kr Cr/Kr Urea, Kr Phos/Kr Urea, and Kr Phos/Kr Cr were 2.83 +/- 1.21, 1.23 +/- 0.387, and 0.477 +/- 0.185, respectively. There was a modest correlation be-tween Kr Phos and daily urine volume (r = 0.605, P = .001). Conclusions: In maintenance hemodialysis and hemodiafiltration patients, residual renal phosphate clearance is approximately 23% higher than residual renal urea clearance. Urine volume is a modestly accurate surrogate for estimating residual renal phosphate clear-ance, but only when urine volume is ,300 mL/day.

BACKGROUND:We hypothesized that the association of ultrafiltration rate with mortality in hemodialysis patients was differentially affected by weight and sex and sought to derive a sex- and weight-indexed ultrafiltration rate measure that captures the differential effects of these parameters on the association of ultrafiltration rate with mortality. METHODS:Data were analyzed from the US Fresenius Kidney Care (FKC) database for 1 year after patient entry into a FKC dialysis unit (baseline) and over 2 years of follow-up for patients receiving thrice-weekly in-center hemodialysis. To investigate the joint effect of baseline-year ultrafiltration rate and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions and constructed contour plots of weight-specific mortality hazard ratios over the entire range of ultrafiltration rate values and postdialysis weights (W). RESULTS:In the studied 396,358 patients, the average ultrafiltration rate in ml/h was related to postdialysis weight (W) in kg: 3W+330. Ultrafiltration rates associated with 20% or 40% higher weight-specific mortality risk were 3W+500 and 3W+630 ml/h, respectively, and were 70 ml/h higher in men than in women. Nineteen percent or 7.5% of patients exceeded ultrafiltration rates associated with a 20% or 40% higher mortality risk, respectively. Low ultrafiltration rates were associated with subsequent weight loss. Ultrafiltration rates associated with a given mortality risk were lower in high-body weight older patients and higher in patients on dialysis for more than 3 years. CONCLUSIONS:Ultrafiltration rates associated with various levels of higher mortality risk depend on body weight, but not in a 1:1 ratio, and are different in men versus women, in high-body weight older patients, and in high-vintage patients.

Like many others involved in the written word, I decided to test OpenAI's ChatGPT in my job as editor for a journal related to dialysis. It has become difficult to find reviewers for certain articles, so I was hoping that the newly available "Chat Generative Pre-Trained Transformer" (ChatGPT) might be able to give me a hand. At least the price (free) was right.

We compared predictions of phosphate removal by a 2‐pool kinetic model with measured phosphate removal in spent dialysate as reported by others.