Reduced Complications during Hemodialysis by Automatic Blood Volume Controlled Ultrafiltration

Technical requirements and devices available for long-term hemodialysis in children-mind the gap!

Children requiring long-term kidney replacement therapy are a "rare disease" cohort. While the basic technical requirements for hemodialysis (HD) are similar in children and adults, key aspects of the child's cardiovascular anatomy and hemodynamic specifications must be considered. In this article, we describe the technical requirements for long-term HD therapy for children and the devices that are currently available around the world. We highlight the characteristics and major technical shortcomings of permanent central venous catheters, dialyzers, dialysis machines, and software available to clinicians who care for children. We show that currently available HD machines are not equipped with appropriately small circuits and sensitive control mechanisms to perform safe and effective HD in the youngest patients. Manufacturers limit their liability, and health regulatory agencies permit the use of devices, only in children according to the manufacturers' pre-specified weight limitations. Although registries show that 6-23% of children starting long-term HD weigh less than 15 kg, currently, there is only one long-term HD device that is cleared for use in children weighing 10 to 15 kg and none is available and labelled for use in children weighing less than 10 kg anywhere in the world. Thus, many children are being treated "off-label" and are subject to interventions delivered by medical devices that lack pediatric safety and efficacy data. Moreover, recent improvements in dialysis technology offered to adult patients are denied to most children. We, in turn, advocate for concerted action by pediatric nephrologists, industry, and health regulatory agencies to increase the development of dedicated HD machines and equipment for children.

Feasibility of Dialysate Bolus-Based Absolute Blood Volume Estimation in Maintenance Hemodialysis Patients

BACKGROUND

Absolute blood volume (ABV) is a critical component of fluid status, which may inform target weight prescriptions and hemodynamic vulnerability of dialysis patients. Here, we utilized the changes in relative blood volume (RBV), monitored by ultrasound (BVM) upon intradialytic 240 mL dialysate fluid bolus-infusion 1 h after hemodialysis start, to calculate the session-specific ABV. With the main goal of assessing clinical feasibility, our sub-aims were to (i) standardize the BVM-data read-out; (ii) determine optimal time-points for ABV-calculation, "before-" and "after-bolus"; (iii) assess ABV-variation.

METHODS

We used high-level programming language and basic descriptive statistics in a retrospective study of routinely measured BVM-data from 274 hemodialysis sessions in 98 patients.

RESULTS

Regarding (i) and (ii), we automatized the processing of RBV-data, and determined an algorithm to select the adequate RBV-data points for ABV-calculations. Regarding (iii), we found in 144 BVM-curves from 75 patients, that the average ABV ± standard deviation was 5.2 ± 1.5 L and that among those 51 patients who still had ≥2 valid estimates, the average intra-patient standard deviation in ABV was 0.8 L. Twenty-seven of these patients had an average intra-patient standard deviation in ABV <0.5 L.

CONCLUSIONS

We demonstrate feasibility of ABV-calculation by an automated algorithm after dialysate bolus-administration, based on the BVM-curve. Based on our results from this simple "abridged" calculation approach with routine clinical measurements, we encourage the use of multi-compartment modeling and comparison with reference methods of ABV-determination. Hopes are high that clinicians will be able to use ABV to inform target weight prescription, improving hemodynamic stability.

Integrating Monitoring of Volume Status and Blood Volume-Controlled Ultrafiltration into Extracorporeal Kidney Replacement Therapy

Purpose

Volume management in hemodialysis (HD) requires the ability to assess volume status objectively and determine treatment strategies that achieve euvolemia without compromising hemodynamic stability. The aim of this study was to compare dialysis with and without blood volume-controlled ultrafiltration (UF) in combination with body composition monitoring, and to evaluate indicators for adequate dialysis (Kt/V), ultrafiltration volume, fluid status, and the occurrence of intradialytic morbid events (IME).

Patients and Methods

Patients undergoing hemodialysis or on-line hemodiafiltration with support of a blood volume monitor (BVM) - a feedback control device integrated into the 5008 and 6008 HD systems - were enrolled. Patients received treatment for four weeks using the 6008 CAREsystem and the BVM (6008+). Data on dialysis dose (Kt/V), UF volume and predialysis fluid status were documented. This data was also documented retrospectively for four weeks with (5008+) and without (5008-) the use of the BVM with the 5008 system. Comparisons were analyzed using linear mixed models.

Results

Twenty-four patients were enrolled. Kt/V was unaffected by blood volume-controlled UF (5008- vs 5008+: p=0.230) and was equally achieved with both HD systems (5008+ vs 6008+: p=0.922). The UF volume and fluid status achieved were comparable, independent of the use of UF control with BVM (5008- vs 5008+; UF volume: p=0.166; fluid overload: p=0.390) or the HD system (5008+ vs 6008+: UF volume: p=0.003; fluid overload: p=0.838), except for UF volume being higher in the 6008+ phase. IMEs occurred in less than 3% of treatments, with no difference between study phases.

Conclusion

This study demonstrates that a clinical approach to kidney replacement therapy that tracks volume status and manages intradialytic fluid removal by blood volume-controlled UF delivers adequate dialysis without compromising fluid removal. It maintains volume status and ensures low incidence of IMEs.

Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study

BACKGROUND

Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device-integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD.

OBJECTIVE

We aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner.

METHODS

Three-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD.

RESULTS

Time series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events.

CONCLUSIONS

Our results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

Does Adequate Hemodialysis Prevent Symptoms?: A National Cross-Sectional Survey

The aim of this study was to identify the relationship between dialysis adequacy and the incidence of symptoms in subjects treated with HD. This descriptive and cross-sectional study was conducted at two HD centers. The data were collected with the 'Descriptive Characteristics Form of the Participants' and the 'Dialysis Symptom Index (DSI)'. The study was reported according to the STROBE Declaration. The study was completed with 120 patients. The most common symptom reported was feeling tired or decreased energy and the least common was difficulty concentrating. No statistically significant relationship was found between DSI results and the Kt/V or urea reduction rate levels used to evaluate dialysis adequacy. Dialysis-related symptoms can also be seen in patients with adequate dialysis levels. It is therefore necessary to query the symptoms experienced by the patients at regular intervals.

The relative trending accuracy of noninvasive continuous hemoglobin monitoring during hemodialysis in critically ill patients

The pulse CO-Oximeter (Radical-7; Masimo Corp., Irvine, CA) is a multi-wavelength spectrophotometric method for noninvasive continuous monitoring of hemoglobin (SpHb). Because evaluating the relative change in blood volume (ΔBV) is crucial to avoid hypovolemia and hypotension during hemodialysis, it would be of great clinical benefit if ΔBV could be estimated by measurement of SpHb during hemodialysis. The capability of the pulse CO-Oximeter to monitor ΔBV depends on the relative trending accuracy of SpHb. The purpose of the current study was to evaluate the relative trending accuracy of SpHb by the pulse CO-Oximeter using Crit-Line as a reference device. In 12 patients who received hemodialysis (total 22 sessions) in the intensive care unit, ΔBV was determined from SpHb. Relative changes in blood volume determined from SpHb were calculated according to the equation: ΔBV(SpHb)=[starting SpHb]/[current SpHb] - 1. The absolute values of SpHb and hematocrit measured by Crit-Line (CL-Hct) showed poor correlation. On the contrary, linear regression analysis showed good correlation between ΔBV(SpHb) and the relative change in blood volume measured by Crit-Line [ΔBV(CL-Hct)] (r=0.83; P≤0.001). Bland-Altman analysis also revealed good agreement between ΔBV(SpHb) and ΔBV(CL-Hct) (bias, -0.77%; precision, 3.41%). Polar plot analysis revealed good relative trending accuracy of SpHb with an angular bias of 4.1° and radial limits of agreement of 24.4° (upper) and -16.2° (lower). The results of the current study indicate that SpHb measurement with the pulse CO-Oximeter has good relative trending accuracy.

The Influence of Decreased Low-Molecular-Weight Heparin Nadroparin Dose on Diastolic Blood Pressure in Patients on Hemodialysis

The aim of present study was to assess the impact of decreasing single bolus dose of nadroparin on blood pressure in patients on hemodialysis (HD). Forty HD patients were included in this study. The bolus dose of nadroparin was decreased twice by 25%; this lower dose was maintained for last 4 weeks, during which the dose was adjusted. There were no significant differences between the first and the last predialysis: systolic blood pressure ([pre-SBP]; 131.05 ± 25.58 vs 125.92 ± 25.49 mm Hg; P = .133), diastolic blood pressure ([pre-DBP]; 73.82 ± 11.82 vs 72.89 ± 9.13 mm Hg; P = .653), and pulse pressure ([pre-PP]; 57.24 ± 20.39 vs 53.03 ± 21.20 mm Hg; P = .121). We found correlation between delta nadroparin and pre-DBP in the last HD (rho = 0.310; P = .031) but not between delta nadroparin and pre-SBP and pre-PP values. This is the first report of influence of nadroparin dose lowering on pre-DBP in HD patients.

The rise of hemodialysis machines: new technologies in minimizing cardiovascular complications

Hemodialysis (HD) is a life-saving treatment for more than 1,700,000 patients with chronic kidney disease (CKD) stage V. Every year the HD population becomes increasingly older (average age: 75 years) and more ill due to the associated comorbidities such as cardiovascular disease (heart failure, coronary heart disease and peripheral vascular disease), diabetes, hypertension and peripheral vascular disease. Most of the complications associated with HD involve the cardiovascular system. HD machines have been greatly improved over the last 30 years. We have moved from HD machines simply allowing extracorporeal circulation to high technological medical devices capable of very precisely controlling ultrafiltration, dialysis dose, the patient's core temperature, circulating plasma volume, plasma sodium and producing unlimited volumes of ultrapure dialysate. In this article, we will focus on some of the fundamental achievements in HD machine technology, with particular reference to monitoring tools and bioengineering approaches for biosignal analysis. We propose that along these lines of further development, HD machines in the future will enable a better online identification of patients at higher cardiovascular risk, thus allowing clinicians to select more appropriate treatment modalities and parameters.

Simultaneous Blood Temperature Control and Blood Volume Control Reduces Intradialytic Symptoms

Purpose

Intra-dialytic morbid events (IME; e.g. hypotension, cramps, headaches) are frequent complications during hemodialysis (HD), known to be associated with ultrafiltration-induced hypovolemia and body temperature changes. Feedback control of blood volume adjusts the ultrafiltration rate in order to keep the blood volume above the patient's individual limit; feedback control of blood temperature maintains the mean arterial blood temperature at the individual pre-dialytic level. Each of these methods reduces the frequency of IME.

Methods

In a randomized clinical trial the simultaneous application of both feedback controls was investigated for the first time. In 15 weeks, each patient went through 3 study phases: an observational screening phase, a standard phase (STD), and a blood temperature- and blood volume-control phase (CTL). Patients with at least 5 sessions with IME out of 15 sessions in the screening phase were eligible for the study and randomized either into sequence STD-CTL or CTL-STD.

Results

26 patients completed the study according to protocol, and 778 HD treatments were analyzed. The general treatment parameters were similar in both study phases: treatment duration (STD: 244 min, CTL: 243 min, NS), pre-dialytic weight (STD: 72.3 kg, CTL: 72.2 kg, NS), and weight loss due to ultrafiltration (STD: 3.26 kg, CTL: 3.15 kg, NS). The proportion of HD treatments with IME was 32.8% during STD and 18.0% during CTL (p=0.024).

Conclusions

The frequency of HD sessions with IME was significantly reduced by 45% compared to standard HD in this randomized clinical trial by use of individualized HD treatments with simultaneous feedback control of blood volume and blood temperature.

Patients' perspective of haemodialysis-associated symptoms

Introduction. Patients often report symptoms during haemodialysis (HD). To better understand patients' experience, we surveyed routine HD outpatients, to quantify the burden and duration of dialysis-associated symptoms.

METHODS

Five hundred and eight symptom questionnaires were returned from 550 HD outpatients (92.4%). The symptoms in relation to the HD session were analysed using a visual analogue score. Multivariate logistical regression analysis was used to identify characteristics associated with total symptom burden and time to recover following a HD session.

RESULTS

Fifty-four percent of the cohort were male, median age 64 years, 36% diabetic and median age unadjusted Charlson comorbidity score 3.0 (2-5). Fatigue (82%), intradialytic hypotension (76%), cramps (74%) and dizziness (63%) were the commonest symptoms reported, followed by headache (54%), pruritus (52%) and backache (51%), with fatigue occurring with a median frequency of 50% of dialysis sessions and intradialytic hypotension and cramps in 30%. Some 23% reported recovering from dialysis within minutes, 34% by the time they returned home, 16% by bed time, 24% the following morning and 3% just before the next dialysis session. Symptom burden was associated with female sex, younger age, longer duration of dialysis sessions, ethnicity and dialysis centre practice. The time taken to recover from dialysis varied from minutes to hours and was shorter for men and greater dialysis vintage but longer with increasing session time and those with increased intradialytic symptom burden.

CONCLUSIONS

Despite advances in HD, intradialytic symptoms were frequently reported by our patients. There was substantial unexplained variation in symptom burden across centres, suggesting that clinical practice or policies may play a role in preventing the adverse effects of dialysis. Symptom burden was worse in women, patients of South Asian as opposed to African origin and also in those receiving a longer duration of dialysis. These patients may therefore benefit from a different approach to dialysis prescription.

[Technical advances in haemodialysis]

Survival improvement of our haemodialysis patients is partly due to technologic improvement of the dialysis therapy. High permeability membranes and bicarbonate dialysate were the most relevant of past decades. What are the present technologic innovations that will provide clinical benefit? Acetate-free biofiltration, biofeedback systems, better haemodiafiltration techniques and techniques with adsorption could be part of them.