The Revival of Sorbents in Chronic Dialysis Treatment.

Interest in the use of sorbents in chronic dialysis treatment has undergone a revival in the last decades, for which two major factors are responsible. The first is the potential of sorbents as adjunct therapy for the removal of substances that are difficult to remove by conventional dialysis therapies. The second is their use in regeneration of dialysate, which is of pivotal importance in the design of portable or even wearable treatments, next to the potential for reducing water use during conventional dialysis treatment. Sorbent-enhanced dialysis with synthetic polymers was associated with a reduction in inflammatory parameters as compared to hemodialysis and even associated with improved survival in smaller studies, although this needs to be confirmed in large randomized trials. Incorporation of sorbents within a dialysis membrane (mixed matrix membrane) appears a promising way forward to reduce the complexity and costs of a dual therapy but needs to be tested in vivo. For regeneration of dialysate, at present, a combination of urease, zirconium-based sorbents, and activated charcoal is used. Next to sodium release by the sorbent in exchange for ammonium and the CO2 release by the hydrolysis of urea has been a bottleneck in the design of wearable devices, although short-term trials have been performed. Still, for widespread and flexible application of sorbent-assisted portable or wearable devices, a direct urea sorbent would be a major asset. In the near future, it will likely become apparent whether sorbent-assisted dialysis techniques are feasible for routine implementation in clinical practice.

Modifiable Risk Factors Are Important Predictors of COVID-19-Related Mortality in Patients on Hemodialysis.

Introduction: Patients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques. Methods: We included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality. Results: We included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m2 (OR: 1.28, CI: 1.10-1.50), single-pool Kt/V (OR off-target vs on-target: 1.19, CI: 1.02-1.38), overhydration (OR: 1.15, CI: 1.01-1.32), and both low (<2.5 mg/dl) and high (≥5.5 mg/dl) serum phosphate levels (OR: 1.52, CI: 1.07-2.16 and OR: 1.17, CI: 1.01-1.35). On-line hemodiafiltration was protective in the model using KPIs (OR: 0.86, CI: 0.76-0.97). SHapley Additive exPlanations analysis in XGBoost models shows a high influence on prediction for several modifiable factors as well, including inflammatory parameters, high BMI, and fluid overload. In both LR and XGBoost models, age, gender, and comorbidities were strongly associated with mortality. Conclusion: Both conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.

Wearable sensors: can they benefit patients with chronic kidney disease?

INTRODUCTION: This article ponders upon wearable medical measurement devices in relation to Chronic Kidney Disease (CKD) and its' associated comorbidities - and whether these might benefit CKD-patients. We aimed to map the intersection(s) of nephrology and wearable sensor technology to help technologists understand medical aspects, and clinicians to understand technological possibilities that are available (or soon will become so). Areas covered: A structured literature search on main comorbidities and complications CKD patients suffer from, was used to steer mini-reviews on wearable sensor technologies clustered around 3 themes being: Cardiovascular-related, diabetes-related and physical fitness/frailty. This review excludes wearable dialysis - although also strongly enabled by miniaturization - because that highly important theme deserves separate in-depth reviewing. Expert commentary: Continuous progress in integrated electronics miniaturization enormously lowered price, size, weight and energy consumption of electronic sensors, processing power, memory and wireless connectivity. These combined factors boost opportunities for wearable medical sensors. Such devices can be regarded as enablers for: Remote monitoring, influencing human behaviour (exercise, dietary), enhanced home care, remote consults, patient education and peer networks. However, to make wearable medical devices succeed, the challenge to fit them into health care structures will be dominant over the challenge to realize the bare technologies themselves.