Mechanisms of hemoglobin cycling in anemia patients treated with erythropoiesis-stimulating agents.

Patients with renal anemia are frequently treated with erythropoiesis-stimulating agents (ESAs), which are dynamically dosed in order to stabilize blood hemoglobin levels within a specified target range. During typical ESA treatments, a fraction of patients experience hemoglobin 'cycling' periods during which hemoglobin levels periodically over- and undershoot the target range. Here we report a specific mechanism of hemoglobin cycling, whereby cycles emerge from the patient's delayed physiological response to ESAs and concurrent ESA dose adjustments. We introduce a minimal theoretical model that can explain dynamic hallmarks of observed hemoglobin cycling events in clinical time series and elucidates how physiological factors (such as red blood cell lifespan and ESA responsiveness) and treatment-related factors (such as dosing schemes) affect cycling. These results show that in general, hemoglobin cycling cannot be attributed to patient physiology or ESA treatment alone but emerges through an interplay of both, with consequences for the design of ESA treatment strategies.

Challenges of Predicting Arteriovenous Access Survival Prior to Conversion from Catheter.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

The Impact of a Wearable Activity Tracker and Structured Feedback Program on Physical Activity in Hemodialysis Patients: The Step4Life Pilot Randomized Controlled Trial.

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<0.05). LIMITATIONS: Single-center study and small sample size. CONCLUSION: This pilot randomized controlled trial demonstrated that structured feedback coupled with a wearable activity tracker led to a greater daily step count that was sustained over 12 weeks relative to a wearable activity tracker alone. Future studies are required to determine longer-term sustainability of the intervention and potential health benefits in hemodialysis patients. FUNDING: Grants from industry (Satellite Healthcare) and government (National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK). TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study number NCT05241171.

Real-time prediction of intradialytic hypotension using machine learning and cloud computing infrastructure.

BACKGROUND: In maintenance hemodialysis patients, intradialytic hypotension (IDH) is a frequent complication that has been associated with poor clinical outcomes. Prediction of IDH may facilitate timely interventions and eventually reduce IDH rates. METHODS: We developed a machine learning model to predict IDH in in-center hemodialysis patients 15-75 min in advance. IDH was defined as systolic blood pressure (SBP) <90 mmHg. Demographic, clinical, treatment-related and laboratory data were retrieved from electronic health records and merged with intradialytic machine data that were sent in real-time to the cloud. For model development, dialysis sessions were randomly split into training (80%) and testing (20%) sets. The area under the receiver operating characteristic curve (AUROC) was used as a measure of the model's predictive performance. RESULTS: We utilized data from 693 patients who contributed 42 656 hemodialysis sessions and 355 693 intradialytic SBP measurements. IDH occurred in 16.2% of hemodialysis treatments. Our model predicted IDH 15-75 min in advance with an AUROC of 0.89. Top IDH predictors were the most recent intradialytic SBP and IDH rate, as well as mean nadir SBP of the previous 10 dialysis sessions. CONCLUSIONS: Real-time prediction of IDH during an ongoing hemodialysis session is feasible and has a clinically actionable predictive performance. If and to what degree this predictive information facilitates the timely deployment of preventive interventions and translates into lower IDH rates and improved patient outcomes warrants prospective studies.

Assessing proximate intermediates between ambient temperature, hospital admissions, and mortality in hemodialysis patients.

BACKGROUND: Typical thermoregulatory responses to elevated temperatures among healthy individuals include reduced blood pressure and perspiration. Individuals with end-stage kidney disease (ESKD) are susceptible to systemic fluctuations caused by ambient temperature changes that may increase morbidity and mortality. We investigated whether pre-dialysis systolic blood pressure (preSBP) and interdialytic weight gain (IDWG) can independently mediate the association between ambient temperature, all-cause hospital admissions (ACHA), and all-cause mortality (ACM). METHODS: The study population consisted of ESKD patients receiving hemodialysis treatments at Fresenius Medical Care facilities in Philadelphia County, PA, from 2011 to 2019 (n = 1981). Within a time-to-event framework, we estimated the association between daily maximum dry-bulb temperature (TMAX) and, as separate models, ACHA and ACM during warmer calendar months. Clinically measured preSBP and IDWG responses to temperature increases were estimated using linear mixed effect models. We employed the difference (c-c') method to decompose total effect models for ACHA and ACM using preSBP and IDWG as time-dependent mediators. Covariate adjustments for exposure-mediator and total and direct effect models include age, race, ethnicity, blood pressure medication use, treatment location, preSBP, and IDWG. We considered lags up to two days for exposure and 1-day lag for mediator variables (Lag 2-Lag 1) to assure temporality between exposure-outcome models. Sensitivity analyses for 2-day (Lag 2-only) and 1-day (Lag 1-only) lag structures were also conducted. RESULTS: Based on Lag 2- Lag 1 temporal ordering, 1 °C increase in daily TMAX was associated with increased hazard of ACHA by 1.4% (adjusted hazard ratio (HR), 1.014; 95% confidence interval, 1.007-1.021) and ACM 7.5% (adjusted HR, 1.075, 1.050-1.100). Short-term lag exposures to 1 °C increase in temperature predicted mean reductions in IDWG and preSBP by 0.013-0.015% and 0.168-0.229 mmHg, respectively. Mediation analysis for ACHA identified significant indirect effects for all three studied pathways (preSBP, IDWG, and preSBP + IDWG) and significant indirect effects for IDWG and conjoined preSBP + IDWG pathways for ACM. Of note, only 1.03% of the association between temperature and ACM was mediated through preSBP. The mechanistic path for IDWG, independent of preSBP, demonstrated inconsistent mediation and, consequently, potential suppression effects in ACHA (-15.5%) and ACM (-6.3%) based on combined pathway models. Proportion mediated estimates from preSBP + IDWG pathways achieved 2.2% and 0.3% in combined pathway analysis for ACHA and ACM outcomes, respectively. Lag 2 discrete-time ACM mediation models exhibited consistent mediation for all three pathways suggesting that 2-day lag in IDWG and preSBP responses can explain 2.11% and 4.41% of total effect association between temperature and mortality, respectively. CONCLUSION: We corroborated the previously reported association between ambient temperature, ACHA and ACM. Our results foster the understanding of potential physiological linkages that may explain or suppress temperature-driven hospital admissions and mortality risks. Of note, concomitant changes in preSBP and IDWG may have little intermediary effect when analyzed in combined pathway models. These findings advance our assessment of candidate interventions to reduce the impact of outdoor temperature change on ESKD patients.

Effect of hypoxia and uremia on oxidative stress on erythrocytes from hemodialysis patients.

Oxidative stress (OS) is essential in uremia-associated comorbidities, including renal anemia. Complications experienced by hemodialysis (HD) patients, such as hypoxemia and uremic toxins accumulation, induce OS and premature death of red blood cells (RBC). We aimed to characterize reactive oxygen species (ROS) production and antioxidant pathways in HD-RBC and RBC from healthy controls (CON-RBC) and evaluate the role of uremia and hypoxia in these pathways. ROS production, xanthine oxidase (XO) and superoxide dismutase (SOD) activities, glutathione (GSH), and heme oxygenase-1 (HO-1) levels were measured using flow cytometry or spectrophotometry in CON-RBC and HD-RBC (pre- and post-HD), at baseline and after 24 h incubation with uremic serum (S-HD) and/or under hypoxic conditions (5% O2 ). Ketoprofen was used to inhibit RBC uremic toxins uptake. HD-RBC showed higher ROS levels and lower XO activity than CON-RBC, particularly post-HD. GSH levels were lower, while SOD activity and HO-1 levels of HD-RBC were higher than control. Hypoxia per se triggered ROS production in CON-RBC and HD-RBC. S-HD, on top of hypoxia, increased ROS levels. Inhibition of uremic toxins uptake attenuated ROS of CON and HD-RBC under hypoxia and uremia. CON-RBC in uremia and hypoxia showed lower GSH levels than cells in normoxia and non-uremic conditions. Redox mechanisms of HD-RBC are altered and prone to oxidation. Uremic toxins and hypoxia play a role in unbalancing these systems. Hypoxia and uremia participate in the pathogenesis of OS in HD-RBC and might induce RBC death and thus compound anemia.

Vascular Access and Clinical Outcomes in Underserved Hemodialysis Patients in Mexico.

INTRODUCTION: Central venous catheter (CVC) as vascular access in hemodialysis (HD) associates with adverse outcomes. Early CVC to fistula or graft conversion improves these outcomes. While socioeconomic disparities between the USA and Mexico exist, little is known about CVC prevalence and conversion rates in uninsured Mexican HD patients. We examined vascular access practice patterns and their effects on survival and hospitalization rates among uninsured Mexican HD patients, in comparison with HD patients who initiated treatment in the USA. METHODS: In this retrospective study of incident HD patients at Hospital Civil (HC; Guadalajara, MX) and the Renal Research Institute (RRI; USA), we categorized patients by the vascular access at the first month of HD and after the following 6 months. Factors associated with continued CVC use were identified by a logistic regression model. We developed multivariate Cox proportional hazards models to investigate the effects of access and conversion on mortality and hospitalization over an 18-month follow-up period. RESULTS: In 1,632 patients from RRI, the CVC prevalence at month 1 was 64% and 97% among 174 HC patients. The conversion rate was 31.7% in RRI and 10.6% in HC. CVC to non-central venous catheter (NON-CVC) conversion reduced the risk of hospitalization in both HC (aHR 0.38 [95% CI: 0.21-0.68], p = 0.001) and RRI (aHR 0.84 [95% CI: 0.73-0.93], p = 0.001). NON-CVC patients had a lower mortality risk in both populations. DISCUSSION/CONCLUSION: CVC prevalence and conversion rates of CVC to NON-CVC differed between the US and Mexican patients. An association exists between vascular access type and hospitalization and mortality risk. Prospective studies are needed to evaluate if accelerated and systematic catheter use reduction would improve outcomes in these populations.

Gut Microbiome-Derived Uremic Toxin Levels in Hemodialysis Patients on Different Phosphate Binder Therapies.

INTRODUCTION: Constipation is prevalent in patients with kidney failure partly due to the use of medication, such as phosphate binders. We hypothesized that serum levels of gut microbiome-derived uremic toxins (UTOX) may be affected by the choice of phosphate binder putatively through its impact on colonic transit time. We investigated two commonly prescribed phosphate binders, sevelamer carbonate (SEV) and sucroferric oxyhydroxide (SFO), and their association with gut microbiome-derived UTOX levels in hemodialysis (HD) patients. METHODS: Weekly blood samples were collected from 16 anuric HD participants during the 5-week observational period. All participants were on active phosphate binder monotherapy with either SFO or SEV for at least 4 weeks prior to enrollment. Eight UTOX (7 gut microbiome-derived) and tryptophan were quantified using liquid chromatography-mass spectrometry. Serum phosphorus, nutritional, and liver function markers were also measured. For each substance, weekly individual levels, the median concentration per participant, and differences between SFO and SEV groups were reported. Patient-reported bowel movements, by the Bristol Stool Scale (BSS), and pill usage were assessed weekly. RESULTS: The SEV group reported a 3.3-fold higher frequency of BSS stool types 1 and 2 (more likely constipated, p < 0.05), whereas the SFO group reported a 1.5-fold higher frequency of BSS stool types 5-7 (more likely loose stool and diarrhea, not significant). Participants in the SFO group showed a trend toward better adherence to phosphate binder therapy (SFO: 87.6% vs. SEV: 66.6%, not significant). UTOX, serum phosphorus, nutritional and liver function markers, and tryptophan were not different between the two groups. CONCLUSION: There was no difference in the gut microbiome-derived UTOX levels between phosphate binders (SFO vs. SEV), despite SFO therapy resulting in fewer constipated participants. This pilot study may inform study design of future clinical trials and highlights the importance of including factors beyond bowel habits and their association with UTOX levels.

Predictors of shorter- and longer-term mortality after COVID-19 presentation among dialysis patients: parallel use of machine learning models in Latin and North American countries.

BACKGROUND: We developed machine learning models to understand the predictors of shorter-, intermediate-, and longer-term mortality among hemodialysis (HD) patients affected by COVID-19 in four countries in the Americas. METHODS: We used data from adult HD patients treated at regional institutions of a global provider in Latin America (LatAm) and North America who contracted COVID-19 in 2020 before SARS-CoV-2 vaccines were available. Using 93 commonly captured variables, we developed machine learning models that predicted the likelihood of death overall, as well as during 0-14, 15-30, > 30 days after COVID-19 presentation and identified the importance of predictors. XGBoost models were built in parallel using the same programming with a 60%:20%:20% random split for training, validation, & testing data for the datasets from LatAm (Argentina, Columbia, Ecuador) and North America (United States) countries. RESULTS: Among HD patients with COVID-19, 28.8% (1,001/3,473) died in LatAm and 20.5% (4,426/21,624) died in North America. Mortality occurred earlier in LatAm versus North America; 15.0% and 7.3% of patients died within 0-14 days, 7.9% and 4.6% of patients died within 15-30 days, and 5.9% and 8.6% of patients died > 30 days after COVID-19 presentation, respectively. Area under curve ranged from 0.73 to 0.83 across prediction models in both regions. Top predictors of death after COVID-19 consistently included older age, longer vintage, markers of poor nutrition and more inflammation in both regions at all timepoints. Unique patient attributes (higher BMI, male sex) were top predictors of mortality during 0-14 and 15-30 days after COVID-19, yet not mortality > 30 days after presentation. CONCLUSIONS: Findings showed distinct profiles of mortality in COVID-19 in LatAm and North America throughout 2020. Mortality rate was higher within 0-14 and 15-30 days after COVID-19 in LatAm, while mortality rate was higher in North America > 30 days after presentation. Nonetheless, a remarkable proportion of HD patients died > 30 days after COVID-19 presentation in both regions. We were able to develop a series of suitable prognostic prediction models and establish the top predictors of death in COVID-19 during shorter-, intermediate-, and longer-term follow up periods.

The oxygen cascade in patients treated with hemodialysis and native high-altitude dwellers: lessons from extreme physiology to benefit patients with end-stage renal disease.

Patients treated with hemodialysis (HD) repeatedly undergo intradialytic low arterial oxygen saturation and low central venous oxygen saturation, reflecting an imbalance between upper body systemic oxygen supply and demand, which are associated with increased mortality. Abnormalities along the entire oxygen cascade, with impaired diffusive and convective oxygen transport, contribute to the reduced tissue oxygen supply. HD treatment impairs pulmonary gas exchange and reduces ventilatory drive, whereas ultrafiltration can reduce tissue perfusion due to a decline in cardiac output. In addition to these factors, capillary rarefaction and reduced mitochondrial efficacy can further affect the balance between cellular oxygen supply and demand. Whereas it has been convincingly demonstrated that a reduced perfusion of heart and brain during HD contributes to organ damage, the significance of systemic hypoxia remains uncertain, although it may contribute to oxidative stress, systemic inflammation, and accelerated senescence. These abnormalities along the oxygen cascade of patients treated with HD appear to be diametrically opposite to the situation in Tibetan highlanders and Sherpa, whose physiology adapted to the inescapable hypobaric hypoxia of their living environment over many generations. Their adaptation includes pulmonary, vascular, and metabolic alterations with enhanced capillary density, nitric oxide production, and mitochondrial efficacy without oxidative stress. Improving the tissue oxygen supply in patients treated with HD depends primarily on preventing hemodynamic instability by increasing dialysis time/frequency or prescribing cool dialysis. Whether dietary or pharmacological interventions, such as the administration of L-arginine, fermented food, nitrate, nuclear factor erythroid 2-related factor 2 agonists, or prolyl hydroxylase 2 inhibitors, improve clinical outcome in patients treated with HD warrants future research.

The time of onset of intradialytic hypotension during a hemodialysis session associates with clinical parameters and mortality.

Intradialytic hypotension (IDH) is a common complication of hemodialysis, but there is no data about the time of onset during treatment. Here we describe the incidence of IDH throughout hemodialysis and associations of time of hypotension with clinical parameters and survival by analyzing data from 21 dialysis clinics in the United States to include 785682 treatments from 4348 patients. IDH was defined as a systolic blood pressure of 90 mmHg or under while IDH incidence was calculated in 30-minute intervals throughout the hemodialysis session. Associations of time of IDH with clinical and treatment parameters were explored using logistic regression and with survival using Cox-regression. Sensitivity analysis considered further IDH definitions. IDH occurred in 12% of sessions at a median time interval of 120-149 minutes. There was no notable change in IDH incidence across hemodialysis intervals (range: 2.6-3.2 episodes per 100 session-intervals). Relative blood volume and ultrafiltration volume did not notably associate with IDH in the first 90 minutes but did thereafter. Associations between central venous but not arterial oxygen saturation and IDH were present throughout hemodialysis. Patients prone to IDH early as compared to late in a session had worse survival. Sensitivity analyses suggested IDH definition affects time of onset but other analyses were comparable. Thus, our study highlights the incidence of IDH during the early part of hemodialysis which, when compared to later episodes, associates with clinical parameters and mortality.

Uremia and Inadequate Oxygen Supply Induce Eryptosis and Intracellular Hypoxia in Red Blood Cells.

BACKGROUND/AIMS: Chronic kidney disease is frequently accompanied by anemia, hypoxemia, and hypoxia. It has become clear that the impaired erythropoietin production and altered iron homeostasis are not the sole causes of renal anemia. Eryptosis is a process of red blood cells (RBC) death, like apoptosis of nucleated cells, characterized by Ca2+ influx and phosphatidylserine (PS) exposure to the outer RBC membrane leaflet. Eryptosis can be induced by uremic toxins and occurs before senescence, thus shortening RBC lifespan and aggravating renal anemia. We aimed to assess eryptosis and intracellular oxygen levels of RBC from hemodialysis patients (HD-RBC) and their response to hypoxia, uremia, and uremic toxins uptake inhibition. METHODS: Using flow cytometry, RBC from healthy individuals (CON-RBC) and HD-RBC were subjected to PS (Annexin-V), intracellular Ca2+ (Fluo-3/AM) and intracellular oxygen (Hypoxia Green) measurements, at baseline and after incubation with uremic serum and/or hypoxia (5% O2), with or without ketoprofen. Baseline levels of uremic toxins were quantified in serum and cytosol by high performance liquid chromatography. RESULTS: Here, we show that HD-RBC have less intracellular oxygen and that it is further decreased post-HD. Also, incubation in 5% O2 and uremia triggered eryptosis in vitro by exposing PS. Hypoxia itself increased the PS exposure in HD-RBC and CON-RBC, and the addition of uremic serum aggravated it. Furthermore, inhibition of the organic anion transporter 2 with ketoprofen reverted eryptosis and restored the levels of intracellular oxygen. Cytosolic levels of the uremic toxins pCS and IAA were decreased after dialysis. CONCLUSION: These findings suggest the participation of uremic toxins and hypoxia in the process of eryptosis and intracellular oxygenation.

Effect of hemodiafiltration on measured physical activity: primary results of the HDFIT randomized controlled trial.

BACKGROUND: Dialysis patients are typically inactive and their physical activity (PA) decreases over time. Uremic toxicity has been suggested as a potential causal factor of low PA in dialysis patients. Post-dilution high-volume online hemodiafiltration (HDF) provides greater higher molecular weight removal and studies suggest better clinical/patient-reported outcomes compared with hemodialysis (HD). METHODS: HDFIT was a randomized controlled trial at 13 clinics in Brazil that aimed to investigate the effects of HDF on measured PA (step counts) as a primary outcome. Stable HD patients (vintage 3-24 months) were randomized to receive HDF or high-flux HD. Treatment effect of HDF on the primary outcome from baseline to 3 and 6 months was estimated using a linear mixed-effects model. RESULTS: We randomized 195 patients (HDF 97; HD 98) between August 2016 and October 2017. Despite the achievement of a high convective volume in the majority of sessions and a positive impact on solute removal, the treatment effect HDF on the primary outcome was +538 [95% confidence interval (CI) -330 to 1407] steps/24 h after dialysis compared with HD, and was not statistically significant. Despite a lack of statistical significance, the observed size of the treatment effect was modest and driven by steps taken between 1.5 and 24.0 h after dialysis, in particular between 20 and 24 h (+197 steps; 95% CI -95 to 488). CONCLUSIONS: HDF did not have a statistically significant treatment effect on PA 24 h following dialysis, albeit effect sizes may be clinically meaningful and deserve further investigation.

Artificial intelligence enabled applications in kidney disease.

Artificial intelligence (AI) is considered as the next natural progression of traditional statistical techniques. Advances in analytical methods and infrastructure enable AI to be applied in health care. While AI applications are relatively common in fields like ophthalmology and cardiology, its use is scarcely reported in nephrology. We present the current status of AI in research toward kidney disease and discuss future pathways for AI. The clinical applications of AI in progression to end-stage kidney disease and dialysis can be broadly subdivided into three main topics: (a) predicting events in the future such as mortality and hospitalization; (b) providing treatment and decision aids such as automating drug prescription; and (c) identifying patterns such as phenotypical clusters and arteriovenous fistula aneurysm. At present, the use of prediction models in treating patients with kidney disease is still in its infancy and further evidence is needed to identify its relative value. Policies and regulations need to be addressed before implementing AI solutions at the point of care in clinics. AI is not anticipated to replace the nephrologists' medical decision-making, but instead assist them in providing optimal personalized care for their patients.

The Predialysis Serum Sodium Level Modifies the Effect of Hemodialysis Frequency on Left-Ventricular Mass: The Frequent Hemodialysis Network Trials.

INTRODUCTION: The Frequent Hemodialysis Network (FHN) Daily and Nocturnal trials aimed to compare the effects of hemodialysis (HD) given 6 versus 3 times per week. More frequent in-center HD significantly reduced left-ventricular mass (LVM), with more pronounced effects in patients with low urine volumes. In this study, we aimed to explore another potential effect modifier: the predialysis serum sodium (SNa) and related proxies of plasma tonicity. METHODS: Using data from the FHN Daily and Nocturnal Trials, we compared the effects of frequent HD on LVM among patients stratified by SNa, dialysate-to-predialysis serum-sodium gradient (GNa), systolic and diastolic blood pressure, time-integrated sodium-adjusted fluid load (TIFL), and extracellular fluid volume estimated by bioelectrical impedance analysis. RESULTS: In 197 enrolled subjects in the FHN Daily Trial, the treatment effect of frequent HD on ∆LVM was modified by SNa. When the FHN Daily Trial participants are divided into lower and higher predialysis SNa groups (less and greater than 138 mEq/L), the LVM reduction in the lower group was substantially higher (-28.0 [95% CI -40.5 to -15.4] g) than in the higher predialysis SNa group (-2.0 [95% CI -15.5 to 11.5] g). Accounting for GNa, TIFL also showed more pronounced effects among patients with higher GNa or higher TIFL. Results in the Nocturnal Trial were similar in direction and magnitude but did not reach statistical significance. DISCUSSION/CONCLUSION: In the FHN Daily Trial, the favorable effects of frequent HD on left-ventricular hypertrophy were more pronounced among patients with lower predialysis SNa and higher GNa and TIFL. Whether these metrics can be used to identify patients most likely to benefit from frequent HD or other dialytic or nondialytic interventions remains to be determined. Prospective, adequately powered studies studying the effect of GNa reduction on mortality and hospitalization are needed.

Artificial Intelligence Methods for Rapid Vascular Access Aneurysm Classification in Remote or In-Person Settings.

BACKGROUND: Innovations in artificial intelligence (AI) have proven to be effective contributors to high-quality health care. We examined the beneficial role AI can play in noninvasively grading vascular access aneurysms to reduce high-morbidity events, such as rupture, in ESRD patients on hemodialysis. METHODS: Our AI instrument noninvasively examines and grades aneurysms in both arteriovenous fistulas and arteriovenous grafts. Aneurysm stages were adjudicated by 3 vascular specialists, based on a grading system that focuses on actions that need to be taken. Our automatic classification of aneurysms builds on 2 components: (a) the use of smartphone technology to capture aneurysm appearance and (b) the analysis of these images using a cloud-based convolutional neural network (CNN). RESULTS: There was a high degree of correlation between our noninvasive AI instrument and the results of the adjudication by the vascular experts. Our results indicate that CNN can automatically classify aneurysms. We achieved a >90% classification accuracy in the validation images. CONCLUSION: This is the first quality improvement project to show that an AI instrument can reliably grade vascular access aneurysms in a noninvasive way, allowing rapid assessments to be made on patients who would otherwise be at risk for highly morbid events. Moreover, these AI-assisted assessments can be made without having to schedule separate appointments and potentially even via telehealth.

Hepatitis B Vaccination Response in Hemodialysis Patients: The Impact of Dialysis Shift.

BACKGROUND/AIMS: Hepatitis B (HB) vaccination in hemodialysis patients is important as they are at a higher risk of contracting HB. However, hemodialysis patients have a lower HB seroconversion rate than their healthy counterparts. As better sleep has been associated with better seroconversion in healthy populations and early hemodialysis start has been linked to significant sleep-wake disturbances in hemodialysis patients, we examined if hemodialysis treatment start time is associated with HB vaccination response. METHODS: Demographics, standard-of-care clinical, laboratory, and treatment parameters, dialysis shift data, HB antigen status, HB vaccination status, and HB titers were collected from hemodialysis patients in Fresenius clinics from January 2010 to December 2015. Patients in our analysis received 90% of dialysis treatments either before or after 8:30 a.m., were negative for HB antigen, and received a complete series of HB vaccination (Engerix B® or Recombivax HB™). Univariate and multivariate regression models examined whether dialysis start time is a predictor of HB vaccination response. RESULTS: Patients were 65 years old, 57% male, and had a HD vintage of 10 months. Patients whose dialysis treatments started before 8:30 a.m. were more likely to be younger, male, and have a greater dialysis vintage. Patients receiving Engerix B® and starting dialysis before 8:30 a.m. had a significantly higher seroconversion rate compared to patients who started dialysis after 8:30 a.m. Early dialysis start was a significant predictor of seroconversion in univariate and multivariate regression including male gender, but not in multivariate regression including age, neutrophil-to-lymphocyte ratio, and vintage. CONCLUSION: While better sleep following vaccination is associated with seroconversion in the general population, this is not the case in hemodialysis patients after multivariate adjustment. In the context of end-stage kidney disease, early dialysis start is not a significant predictor of HB vaccination response. The association between objectively measured postvaccination sleep duration and seroconversion rate should be investigated.

Effect of Statewide Lockdown in Response to COVID-19 Pandemic on Physical Activity Levels of Hemodialysis Patients.

BACKGROUND/OBJECTIVES: On March 22, 2020, a statewide stay-at-home order for nonessential tasks was implemented in New York State. We aimed to determine the impact of the lockdown on physical activity levels (PAL) in hemodialysis patients. METHODS: Starting in May 2018, we are conducting an observational study with a 1-year follow-up on PAL in patients from 4 hemodialysis clinics in New York City. Patients active in the study as of March 22, 2020, were included. PAL was defined by steps taken per day measured by a wrist-based monitoring device (Fitbit Charge 2). Average steps/day were calculated for January 1 to February 13, 2020, and then weekly from February 14 to June 30. RESULTS: 42 patients were included. Their mean age was 55 years, 79% were males, and 69% were African Americans. Between January 1 and February 13, 2020, patients took on average 5,963 (95% CI 4,909-7,017) steps/day. In the week prior to the mandated lockdown, when a national emergency was declared, and in the week of the shutdown, the average number of daily steps had decreased by 868 steps/day (95% CI 213-1,722) and 1,222 steps/day (95% CI 668-2300), respectively. Six patients were diagnosed with COVID-19 during the study period. Five of them exhibited significantly higher PAL in the 2 weeks prior to showing COVID-19 symptoms compared to COVID-19 negative patients. CONCLUSION: Lockdown measures were associated with a significant decrease in PAL in hemodialysis patients. Patients who contracted COVID-19 had higher PAL during the incubation period. Methods to increase PAL while allowing for social distancing should be explored and implemented.

Transmission of SARS-CoV-2 considering shared chairs in outpatient dialysis: a real-world case-control study.

BACKGROUND: SARS-CoV-2 can remain transiently viable on surfaces. We examined if use of shared chairs in outpatient hemodialysis associates with a risk for indirect patient-to-patient transmission of SARS-CoV-2. METHODS: We used data from adults treated at 2,600 hemodialysis facilities in United States between February 1st and June 8th, 2020. We performed a retrospective case-control study matching each SARS-CoV-2 positive patient (case) to a non-SARS-CoV-2 patient (control) treated in the same dialysis shift. Cases and controls were matched on age, sex, race, facility, shift date, and treatment count. For each case-control pair, we traced backward 14 days to assess possible prior exposure from a 'shedding' SARS-CoV-2 positive patient who sat in the same chair immediately before the case or control. Conditional logistic regression models tested whether chair exposure after a shedding SARS-CoV-2 positive patient conferred a higher risk of SARS-CoV-2 infection to the immediate subsequent patient. RESULTS: Among 170,234 hemodialysis patients, 4,782 (2.8 %) tested positive for SARS-CoV-2 (mean age 64 years, 44 % female). Most facilities (68.5 %) had 0 to 1 positive SARS-CoV-2 patient. We matched 2,379 SARS-CoV-2 positive cases to 2,379 non-SARS-CoV-2 controls; 1.30 % (95 %CI 0.90 %, 1.87 %) of cases and 1.39 % (95 %CI 0.97 %, 1.97 %) of controls were exposed to a chair previously sat in by a shedding SARS-CoV-2 patient. Transmission risk among cases was not significantly different from controls (OR = 0.94; 95 %CI 0.57 to 1.54; p = 0.80). Results remained consistent in adjusted and sensitivity analyses. CONCLUSIONS: The risk of indirect patient-to-patient transmission of SARS-CoV-2 infection from dialysis chairs appears to be low.

Real-time prediction of intradialytic relative blood volume: a proof-of-concept for integrated cloud computing infrastructure.

BACKGROUND: Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals. METHOD: We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient's relative blood volume (RBV) decreases at a rate of at least - 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records. RESULTS: Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data. CONCLUSIONS: The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis.