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Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.

RATIONALE & OBJECTIVE: People with end-stage kidney disease (ESKD) have very low physical activity, and the degree of inactivity is strongly associated with morbidity and mortality. We assessed the feasibility and effectiveness of a 12-week intervention coupling a wearable activity tracker (FitBit) and structured feedback coaching versus wearable activity tracker alone on changes in physical activity in hemodialysis patients. STUDY DESIGN: Randomized controlled trial. SETTING & PARTICIPANTS: 55 participants with ESKD receiving hemodialysis who were able to walk with or without assistive devices recruited from a single academic hemodialysis unit between January 2019 and April 2020. INTERVENTIONS: All participants wore a Fitbit Charge 2 tracker for a minimum of 12 weeks. Participants were randomly assigned 1:1 to a wearable activity tracker plus a structured feedback intervention versus the wearable activity tracker alone. The structured feedback group was counseled weekly on steps achieved after randomization. OUTCOME: The outcome was step count, and the main parameter of interest was the absolute change in daily step count, averaged per week, from baseline to completion of 12 weeks intervention. In the intention-to-treat analysis, mixed-effect linear regression analysis was used to evaluate change in daily step count from baseline to 12-weeks in both arms. RESULTS: Out of 55 participants, 46 participants completed the 12-week intervention (23 per arm). The mean age was 62 (± 14 SD) years; 44% were Black, and 36% were Hispanic. At baseline, step count (structured feedback intervention: 3,704 [1,594] vs wearable activity tracker alone: 3,808 [1,890]) and other participant characteristics were balanced between the arms. We observed a larger change in daily step count in the structured feedback arm at 12 weeks relative to use of the wearable activity tracker alone arm (Δ 920 [±580 SD] versus Δ 281 [±186 SD] steps; between-group difference Δ 639 [±538 SD] steps; P

IntroductionInflammation is highly prevalent among patients with end-stage kidney disease and is associated with adverse outcomes. We aimed to investigate longitudinal changes in inflammatory markers in a diverse international incident hemodialysis patient population.MethodsThe MONitoring Dialysis Outcomes (MONDO) Consortium encompasses hemodialysis databases from 31 countries in Europe, North America, South America, and Asia. The MONDO database was queried for inflammatory markers (total white blood cell count [WBC], neutrophil count, lymphocyte count, serum albumin, and C-reactive protein [CRP]) and hemoglobin levels in incident hemodialysis patients. Laboratory parameters were measured every month. Patients were stratified by survival time (≤6 months, >6 to 12 months, >12 to 18 months, >18 to 24 months, >24 to 30 months, >30 to 36 months, and >36 months) following dialysis initiation. We used cubic B-spline basis function to evaluate temporal changes in inflammatory parameters in relationship with patient survival.ResultsWe studied 18,726 incident hemodialysis patients. Their age at dialysis initiation was 71.3 ± 11.9 years; 10,802 (58%) were males. Within the first 6 months, 2068 (11%) patients died, and 12,295 patients (67%) survived >36 months (survivor cohort). Hemodialysis patients who died showed a distinct biphasic pattern of change in inflammatory markers where an initial decline of inflammation was followed by a rapid rise that was consistently evident approximately 6 months before death. This pattern was similar in all patients who died and was consistent across the survival time intervals. In contrast, in the survivor cohort, we observed initial decline of inflammation followed by sustained low levels of inflammatory biomarkers.ConclusionOur international study of incident hemodialysis patients highlights a temporal relationship between serial measurements of inflammatory markers and patient survival. This finding may inform the development of prognostic models, such as the integration of dynamic changes in inflammatory markers for individual risk profiling and guiding preventive and therapeutic interventions.

IntroductionThe clinical impact of COVID-19 has not been established in the dialysis population. We evaluated the trajectories of clinical and laboratory parameters in hemodialysis (HD) patients.MethodsWe used data from adult HD patients treated at an integrated kidney disease company who received a reverse transcription polymerase chain reaction (RT-PCR) test to investigate suspicion of a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection between May 1 and September 1, 2020. Nonparametric smoothing splines were used to fit data for individual trajectories and estimate the mean change over time in patients testing positive or negative for SARS-CoV-2 and those who survived or died within 30 days of first suspicion or positive test date. For each clinical parameter of interest, the difference in average daily changes between COVID-19 positive versus negative group and COVID-19 survivor versus nonsurvivor group was estimated by fitting a linear mixed effects model based on measurements in the 14 days before (i.e., Day -14 to Day 0) Day 0.ResultsThere were 12,836 HD patients with a suspicion of COVID-19 who received RT-PCR testing (8895 SARS-CoV-2 positive). We observed significantly different trends (p

IntroductionThe clinical impact of COVID-19 has not been established in the dialysis population. We evaluated the trajectories of clinical and laboratory parameters in hemodialysis (HD) patients.MethodsWe used data from adult HD patients treated at an integrated kidney disease company who received a reverse transcription polymerase chain reaction (RT-PCR) test to investigate suspicion of a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection between May 1 and September 1, 2020. Nonparametric smoothing splines were used to fit data for individual trajectories and estimate the mean change over time in patients testing positive or negative for SARS-CoV-2 and those who survived or died within 30 days of first suspicion or positive test date. For each clinical parameter of interest, the difference in average daily changes between COVID-19 positive versus negative group and COVID-19 survivor versus nonsurvivor group was estimated by fitting a linear mixed effects model based on measurements in the 14 days before (i.e., Day -14 to Day 0) Day 0.ResultsThere were 12,836 HD patients with a suspicion of COVID-19 who received RT-PCR testing (8895 SARS-CoV-2 positive). We observed significantly different trends (p

BACKGROUND: Hemodialysis initiation using a central venous catheter (CVC) poses an increased risk of death. Conversion to an arterio-venous graft or fistula (AVF, AVG) improves outcomes. The relationship of primary dialysis access and timing of conversion from CVC to either AVF or AVG to all-cause mortality was investigated. METHODS: Two retrospective analyses in incident hemodialysis patients commencing treatment from January 2010 to December 2014 in dialysis clinics in the United States were conducted. Analysis 1 stratified as per access at initiation and those commencing with CVC were further stratified into (a) those that had a CVC, AVF, or AVG the entire year; (b) those that were converted to either AVF or AVG within either (i) the first or (ii) the second 6 months. Kaplan Meier analysis and Cox regression analysis were employed. Analysis 2 included all CVC patients investigating the relationship between access conversion time and mortality risk using a Cox proportional hazards model depicting the hazard ratio (HR) as a spline function over time. RESULTS: Two subsets from initial 78,871 patients were studied. In Analysis 1 both AVF (referent) and AVG [HR 1.12 (0.97 to 1.30)] associated with a better outcome than CVC [HR 1.55 (1.38 to 1.74)] during follow-up. Lower mortality risk was seen for early switch from a CVC to AV access within the first 6 months [HR = 1.04 (0.97-1.13)] compared to a later switch [HR = 1.23 (1.10-1.38)]. Analysis 2 indicated that a CVC to AVF switch resulted in improved survival. Analysis 2 indicated early conversion to confer a survival benefit for CVC to AVG switch. DISCUSSION AND CONCLUSION: AVF and AVG show a survival benefit over CVC. Early conversion from CVC to either access improves survival. This emphasizes the importance of early preparation for dialysis by creation of an AVF or AVG and to convert CVCs early.

Cardiovascular (CV) events are increased 36-fold in patients with end-stage renal disease. However, randomized controlled trials to lower LDL cholesterol (LDL-C) and serum total cholesterol (TC) have not shown significant mortality improvements. An inverse association of TC and LDL-C with all-cause and CV mortality has been observed in patients on chronic dialysis. Lipoproteins also may protect against infectious diseases. We used data from 37,250 patients in the international Monitoring Dialysis Outcomes (MONDO) database to evaluate the association between lipids and infection-related or CV mortality. The study began on the first day of lipid measurement and continued for up to 4 years. We applied Cox proportional models with time-varying covariates to study associations of LDL-C, HDL cholesterol (HDL-C), and triglycerides (TGs) with all-cause, CV, infectious, and other causes of death. Overall, 6,147 patients died (19.2% from CV, 13.2% from infection, and 67.6% from other causes). After multivariable adjustment, higher LDL-C, HDL-C, and TGs were independently associated with lower all-cause death risk. Neither LDL-C nor TGs were associated with CV death, and HDL-C was associated with lower CV risk. Higher LDL-C and HDL-C were associated with a lower risk of death from infection or other non-CV causes. LDL-C was associated with reduced all-cause and infectious, but not CV mortality, which resulted in the inverse association with all-cause mortality.

The decision to convert from catheter to arteriovenous access is difficult yet very important. The ability to accurately predict fistula survival prior to surgery would significantly improve the decision making process. Many previously investigated demographic and clinical features have been associated with fistula failure. However, it is not conclusively understood how reliable predictions based on these parameters are at an individual level. The aim of this study was to investigate the probability of arteriovenous fistula maturation and survival after conversion using machine learning workflows. A retrospective cohort study on multicentre data from a large North American dialysis organisation was conducted. The study population comprised 73 031 chronic in centre haemodialysis patients. The dataset included 49 variables including demographic and clinical features. Two distinct feature selection and prediction pipelines were used: LASSO regression and Boruta followed by a random forest classifier. Predictions were facilitated for re-conversion to catheter within one year. Additionally, all cause mortality predictions were conducted to serve as a comparator. In total, 38 151 patients (52.2%) had complete data and made up the main cohort. Sensitivity analyses were conducted in 67 421 patients (92.3%) after eliminating variables with a high proportion of missing data points. Selected features diverged between datasets and workflows. A previously failed arteriovenous access appeared to be the most stable predictor for subsequent failure. Prediction of re-conversion based on the demographic and clinical information resulted in an area under the receiver operating characteristic curve (ROCAUC) between 0.541 and 0.571, whereas models predicting all cause mortality performed considerably better (ROCAUC 0.662 – 0.683). While group level depiction of major adverse outcomes after catheter to arteriovenous fistula or graft conversion is possible using the included variables, patient level predictions are associated with limited performance. Factors during and after fistula creation as well as biomolecular and genetic biomarkers might be more relevant predictors of fistula survival than baseline clinical conditions. [ABSTRACT FROM AUTHOR]

Evidence-informed decision making in clinical care and policy in nephrology is undermined by trials that selectively report a large number of heterogeneous outcomes, many of which are not patient centered. The Standardized Outcomes in Nephrology-Hemodialysis (SONG-HD) Initiative convened an international consensus workshop on November 7, 2015, to discuss the identification and implementation of a potential core outcome set for all trials in hemodialysis. The purpose of this article is to report qualitative analyses of the workshop discussions, describing the key aspects to consider when establishing core outcomes in trials involving patients on hemodialysis therapy. Key stakeholders including 8 patients/caregivers and 47 health professionals (nephrologists, policymakers, industry, and researchers) attended the workshop. Attendees suggested that identifying core outcomes required equitable stakeholder engagement to ensure relevance across patient populations, flexibility to consider evolving priorities over time, deconstruction of language and meaning for conceptual consistency and clarity, understanding of potential overlap and associations between outcomes, and an assessment of applicability to the range of interventions in hemodialysis. For implementation, they proposed that core outcomes must have simple, inexpensive, and validated outcome measures that could be used in clinical care (quality indicators) and trials (including pragmatic trials) and endorsement by regulatory agencies. Integrating these recommendations may foster acceptance and optimize the uptake and translation of core outcomes in hemodialysis, leading to more informative research, for better treatment and improved patient outcomes.

BackgroundSeasonal mortality differences have been reported in US hemodialysis (HD) patients. Here we examine the effect of seasons on mortality, clinical and laboratory parameters on a global scale.MethodsDatabases from the international Monitoring Dialysis Outcomes (MONDO) consortium were queried to identify patients who received in-center HD for at least 1 year. Clinics were stratified by hemisphere and climate zone (tropical or temperate). We recorded mortality and computed averages of pre-dialysis systolic blood pressure (pre-SBP), interdialytic weight gain (IDWG), serum albumin, and log C-reactive protein (CRP). We explored seasonal effects using cosinor analysis and adjusted linear mixed models globally, and after stratification.ResultsData from 87,399 patients were included (northern temperate: 63,671; northern tropical: 7,159; southern temperate: 13,917; southern tropical: 2,652 patients). Globally, mortality was highest in winter. Following stratification, mortality was significantly lower in spring and summer compared to winter in temperate, but not in tropical zones. Globally, pre-SBP and IDWG were lower in summer and spring as compared to winter, although less pronounced in tropical zones. Except for southern temperate zone, serum albumin levels were higher in winter. CRP levels were highest in winter.ConclusionSignificant global seasonal variations in mortality, pre-SBP, IDWG, albumin and CRP were observed. Seasonal variations in mortality were most pronounced in temperate climate zones.

BackgroundBioimpedance analysis (BIA) is well established to assess body composition. Agreements between single- and multi-frequency bioimpedance (SF-BIA, MF-BIS) measurements in subjects undergoing 6 or 3 times/week hemodialysis (HD) were analyzed.MethodsTotal body water (TBW) and intra- and extracellular fluid (ICF, ECF) of subjects enrolled in the Frequent Hemodialysis Network (FHN) Daily Trial (www.clinicaltrials.gov No. NCT00264758) were measured with a Hydra 4200 at baseline (BL) and at 5 months (M5). Volumes were computed using SF (at 50 kHz) and MF approaches. Agreement was assessed by means of linear regression and Bland-Altman analysis and treatment effects by t test.Results35 subjects (17 on the more frequent regimen, 26 males, 20 African-American, 48 ± 9 years, pre-HD weight 84 ± 19 kg) were studied. Assessments with SF-BIA and MF-BIS correlated significantly at BL and M5 in both arms. No proportional errors, but systematic biases over the entire range of values were found at BL and M5. Agreement did not differ between subjects randomized to either HD treatment arm at both time points. MF-BIS appears to have better precision than SF-BIA allowing the observation of a significant treatment effect by the intervention [-1.5 (95% CI -2.5 to -0.5) l] on ECF, not found for ECF SF-BIA. Precision also affected the statistical power of the SF-BIA data in the current analysis.ConclusionBoth methods showed agreement without significant proportional errors regardless of HD frequency and can be used for longitudinal analyses. SF-BIA has lower precision which needs thorough consideration in the design of future trials with similar outcomes.

Predialysis volume overload is the sum of interdialytic weight gain (IDWG) and residual postdialysis volume overload. It results mostly from failure to achieve an adequate volume status at the end of the dialysis session. Recent developments in bioimpedance spectroscopy and possibly relative plasma volume monitoring permit noninvasive volume status assessment in hemodialysis patients. A large proportion of patients have previously been shown to be chronically volume overloaded predialysis (defined as >15% above 'normal' extracellular fluid volume, equivalent to >2.5 liters on average), and to exhibit a more than twofold increased mortality risk. By contrast, the magnitude of the mortality risk associated with IDWG is much smaller and only evident with very large weight gains. Here we review the available evidence on volume overload and IDWG, and question the use of IDWG as an indicator of 'nonadherence' by describing its association with postdialysis volume depletion. We also demonstrate the relationship between IDWG, volume overload and predialysis serum sodium concentration, and comment on salt intake. Discriminating between volume overload and IDWG will likely lead to a more appropriate management of fluid withdrawal during dialysis. Consensually, the present authors agree that this discrimination should be among the primary goals for dialysis caretakers today. In consequence, we recommend objective measures of volume status beyond mere evaluations of IDWG.

ObjectiveIncreased body mass index (BMI) is associated with reduced all-cause and cardiovascular (CV) mortality in hemodialysis (HD) patients, whereas CV risk increases with BMI in the general population. In the general population, obesity is associated with inflammation, decreased high-density lipoprotein (HDL) cholesterol, increased low-density lipoprotein (LDL) cholesterol, and triglycerides (TGs), all risk factors for CV disease. Low-density lipoprotein cholesterol does not predict CV risk in HD, whereas increased C-reactive protein and interleukin-6 (IL-6), low HDL and apolipoprotein (apo) AI, and increased fasting TGs do predict risk. Renal failure is associated with dyslipidemia and inflammation in normal-weight patients. We hypothesized that the effects of obesity may be obscured by renal failure in HD.MethodsWe explored the relationship between adipose tissue pools and distribution, i.e., subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) (measured by magnetic resonance imaging) and measures of inflammation (C-reactive protein, IL-6, ceruloplasmin, and alpha1 acid glycoprotein), HDL and LDL cholesterol, total TGs, apo AI, apo B, apo CII (an activator of lipoprotein lipase), apo CIII (an inhibitor of lipoprotein lipase), and the adipokines, leptin and adiponectin, in 48 patients with prevalent HD.Results and conclusionsTotal TG concentrations were positively correlated with VAT controlled for age, sex, and weight. Both apo CII and apo CIII were correlated only with VAT. Adiponectin was inversely correlated with VAT, and leptin was positively associated with SAT. C-reactive protein and alpha1 acid glycoprotein were weakly associated with SAT, whereas ceruloplasmin was strongly associated with VAT according to multiple regression analysis. In contrast, apo B, LDL, apo AI, HDL, and IL-6 were not correlated with any measure of body composition, potentially mitigating the effects of obesity in HD.