Associations of between- and within-day patterns of physical activity accumulation with arterial stiffness and indices of microvascular health-Evidence from The Maastricht study.

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std ß = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std ß = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std ß = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

Digital Health Support: Current Status and Future Development for Enhancing Dialysis Patient Care and Empowering Patients.

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments.

Differences in Cardiac Troponin T Composition in Myocardial Infarction and End-Stage Renal Disease Patients: A Blood Tube Effect?

BACKGROUND: Cardiac troponin T (cTnT) is key in diagnosing myocardial infarction (MI) but is also elevated in end-stage renal disease (ESRD) patients. Specific larger cTnT proteoforms were identified for the acute phase of MI, while in serum of ESRD patients solely small cTnT fragments were found. However, others allocated this to a pre-analytic effect due to abundant thrombin generation in serum. Therefore, we investigated the effect of various anticoagulation methods on cTnT composition and concentration and compared the cTnT composition of MI and ESRD patients. METHODS: The agreement of cTnT concentrations between simultaneously collected serum, lithium-heparin (LH) plasma, and ethylenediaminetetraacetic acid (EDTA) plasma was studied using the high-sensitivity (hs-)cTnT immunoassay. cTnT proteoform composition was investigated in a standardized time-dependent manner through spike experiments and in simultaneously collected blood matrixes of MI and ESRD patients. RESULTS: Excellent hs-cTnT concentration agreements were observed across all blood matrixes (slopes > 0.98; 95% CI, 0.96-1.04). Time-dependent degradation (40 kDa intact:29 kDa fragment:15 to 18 kDa fragments) was found in LH plasma and EDTA plasma, and serum in ratios (%) of 90:10:0, 0:5:95, and 0:0:100, respectively (48 h after blood collection). Moreover, gel filtration chromatography (GFC) profiles illustrated mainly larger cTnT proteoforms in MI patients, while in ESRD patients mainly 15 to 18 kDa fragments were found for all matrices. CONCLUSIONS: The extent of cTnT degradation in vitro is dependent on the (anti)coagulation method, without impacting hs-cTnT concentrations. Furthermore, mainly larger cTnT proteoforms were present in MI patients, while in ESRD patients mainly small 15 to 18 kDa cTnT fragments were found. These insights are essential when developing a novel hs-cTnT assay targeting larger cTnT proteoforms.

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.

The Feasibility of Semi-Continuous and Multi-Frequency Thoracic Bioimpedance Measurements by a Wearable Device during Fluid Changes in Hemodialysis Patients.

Repeated single-point measurements of thoracic bioimpedance at a single (low) frequency are strongly related to fluid changes during hemodialysis. Extension to semi-continuous measurements may provide longitudinal details in the time pattern of the bioimpedance signal, and multi-frequency measurements may add in-depth information on the distribution between intra- and extracellular fluid. This study aimed to investigate the feasibility of semi-continuous multi-frequency thoracic bioimpedance measurements by a wearable device in hemodialysis patients. Therefore, thoracic bioimpedance was recorded semi-continuously (i.e., every ten minutes) at nine frequencies (8-160 kHz) in 68 patients during two consecutive hemodialysis sessions, complemented by a single-point measurement at home in-between both sessions. On average, the resistance signals increased during both hemodialysis sessions and decreased during the interdialytic interval. The increase during dialysis was larger at 8 kHz (∆ 32.6 Ω during session 1 and ∆ 10 Ω during session 2), compared to 160 kHz (∆ 29.5 Ω during session 1 and ∆ 5.1 Ω during session 2). Whereas the resistance at 8 kHz showed a linear time pattern, the evolution of the resistance at 160 kHz was significantly different (p < 0.0001). Measuring bioimpedance semi-continuously and with a multi-frequency current is a major step forward in the understanding of fluid dynamics in hemodialysis patients. This study paves the road towards remote fluid monitoring.

Sarcopenia diagnosed by ultrasound-assessed quadriceps muscle thickness and handgrip strength predicts mortality in patients on hemodialysis.

BACKGROUND: Estimation of muscle mass is a pivotal component in the diagnosis of protein-energy wasting and sarcopenia. While bioimpedance spectroscopy is a widely  accepted technique for the assessment of lean tissue related to the diagnosis of sarcopenia, to date skeletal muscle ultrasound (US) has not gained full acceptance for this purpose. The aim of this study was to assess the predictive value for mortality of the indexed thickness of the quadriceps vastus intermedius, as measured by US, compared to lean tissue index as estimated by bioimpedance spectroscopy, both combined with handgrip strength in a group of patients with end-stage kidney disease (ESKD) on maintenance hemodialysis (HD). METHODS: The cut-off values for low handgrip strength were < 27 kg for males and < 16 kg for females. The cut-off value for low lean tissue index was obtained from an age-matched healthy control group, with low lean tissue index being defined as values below the 10th percentile of the distribution of healthy subjects. The cut-off values for low quadriceps vastus intermedius thickness index were < 3.44 mm/m2 for males and < 3.52 mm/m2 for females. RESULTS: Ultrasound and bioimpedance spectroscopy were performed in 99 patients, and handgrip strength was assessed in 64 patients, all on maintenance HD. After a median follow-up of 28 months (interquartile range 19-41 months) 38 patients died. Lean tissue index was not associated with mortality, while low quadriceps vastus intermedius thickness index and low handgrip strength were associated with an increased hazard of death. In the fully adjusted model, only the combination of low handgrip strength and low quadriceps vastus intermedius thickness index was significantly associated with higher mortality. CONCLUSION: When combined with low handgrip strength, low quadriceps muscle US outperformed low lean tissue index as assessed by bioimpedance spectroscopy in predicting mortality in a cohort of patients on maintenance HD. Ultrasound may be a useful and convenient technique for the assessment of sarcopenia and protein-energy wasting in this patient population.

Digital health technology to support care and improve outcomes of chronic kidney disease patients: as a case illustration, the Withings toolkit health sensing tools.

Cardiovascular disease (CVD) is a major burden in dialysis-dependent chronic kidney disease (CKD5D) patients. Several factors contribute to this vulnerability including traditional risk factors such as age, gender, life style and comorbidities, and non-traditional ones as part of dialysis-induced systemic stress. In this context, it appears of utmost importance to bring a closer attention to CVD monitoring in caring for CKD5D patients to ensure early and appropriate intervention for improving their outcomes. Interestingly, new home-used, self-operated, connected medical devices offer convenient and new tools for monitoring in a fully automated and ambulatory mode CKD5D patients during the interdialytic period. Sensoring devices are installed with WiFi or Bluetooth. Some devices are also available in a cellular version such as the Withings Remote Patient Monitoring (RPM) solution. These devices analyze the data and upload the results to Withings HDS (Hybrid data security) platform servers. Data visualization can be viewed by the patient using the Withings Health Mate application on a smartphone, or with a web interface. Health Care Professionals (HCP) can also visualize patient data via the Withings web-based RPM interface. In this narrative essay, we analyze the clinical potential of pervasive wearable sensors for monitoring ambulatory dialysis patients and provide an assessment of such toolkit digital medical health devices currently available on the market. These devices offer a fully automated, unobtrusive and remote monitoring of main vital functions in ambulatory subjects. These unique features provide a multidimensional assessment of ambulatory CKD5D patients covering most physiologic functionalities, detecting unexpected disorders (i.e., volume overload, arrhythmias, sleep disorders) and allowing physicians to judge patient's response to treatment and recommendations. In the future, the wider availability of such pervasive health sensing and digital technology to monitor patients at an affordable cost price will improve the personalized management of CKD5D patients, so potentially resulting in improvements in patient quality of life and survival.

Comparison of whole body versus thoracic bioimpedance in relation to ultrafiltration volume and systolic blood pressure during hemodialysis.

In contrast to whole body bioimpedance, which estimates fluid status at a single point in time, thoracic bioimpedance applied by a wearable device could enable continuous measurements. However, clinical experience with thoracic bioimpedance in patients on dialysis is limited. To test the reproducibility of whole body and thoracic bioimpedance measurements and to compare their relationship with hemodynamic changes during hemodialysis, these parameters were measured pre- and end-dialysis in 54 patients during two sessions. The resistance from both bioimpedance techniques was moderately reproducible between two dialysis sessions (intraclass correlations of pre- to end-dialysis whole body and thoracic resistance between session 1 and 2 were 0.711 [0.58-0.8] and 0.723 [0.6-0.81], respectively). There was a very high to high correlation between changes in ultrafiltration volume and changes in whole body thoracic resistance. Changes in systolic blood pressure negatively correlated to both bioimpedance techniques. Although the relationship between changes in ultrafiltration volume and changes in resistance was stronger for whole body bioimpedance, the relationship with changes in blood pressure was at least comparable for thoracic measurements. These results suggest that thoracic bioimpedance, measured by a wearable device, may serve as an interesting alternative to whole body measurements for continuous hemodynamic monitoring during hemodialysis.NEW & NOTEWORTHY We examined the role of whole body and thoracic bioimpedance in hemodynamic changes during hemodialysis. Whole body and thoracic bioimpedance signals were strongly related to ultrafiltration volume and moderately, negatively, to changes in blood pressure. This work supports the further development of a wearable device measuring thoracic bioimpedance longitudinally in patients on hemodialysis. As such, it may serve as an innovative tool for continuous hemodynamic monitoring during hemodialysis in hospital or in a home-based setting.

Branched-chain ketoacid co-ingestion with protein lowers amino acid oxidation during hemodialysis: A randomized controlled cross-over trial.

BACKGROUND & AIMS: Hemodialysis removes amino acids from the circulation, thereby stimulating muscle proteolysis. Protein ingestion during hemodialysis can compensate for amino acid removal but may also increase uremic toxin production. Branched-chain ketoacid (BCKA) co-ingestion may provide an additional anabolic stimulus without adding to uremic toxin accumulation. In the present study we assessed the impact of BCKA co-ingestion with protein on forearm amino acid balance and amino acid oxidation during hemodialysis. METHODS: Nine patients (age: 73 ± 10 y) on chronic hemodialysis participated in this crossover trial. During two 4-h hemodialysis sessions, patients ingested 18 g protein with (PRO + BCKA) or without (PRO) 9 g BCKAs in a randomized order. Test beverages were labeled with L-[ring-13C6]-phenylalanine and provided throughout the last 3 h of hemodialysis as 18 equal sips consumed with 10-min intervals. Arterial and venous plasma as well as breath samples were collected frequently throughout hemodialysis. RESULTS: Arterial plasma total amino acid (TAA) concentrations during PRO and PRO + BCKA treatments were significantly lower after 1 h of hemodialysis (2.6 ± 0.3 and 2.6 ± 0.3 mmol/L, respectively) when compared to pre-hemodialysis concentrations (4.2 ± 1.0 and 4.0 ± 0.5 mmol/L, respectively; time effect: P < 0.001). Arterial plasma TAA concentrations increased throughout test beverage ingestion (time effect: P = 0.027) without differences between treatments (time∗treatment: P = 0.62). Forearm arteriovenous TAA balance during test beverage ingestion did not differ between timepoints (time effect: P = 0.31) or treatments (time∗treatment: P = 0.34). Whole-body phenylalanine oxidation was 33 ± 16% lower during PRO + BCKA when compared to PRO treatments (P < 0.001). CONCLUSIONS: BCKA co-ingestion with protein during hemodialysis does not improve forearm net protein balance but lowers amino acid oxidation.

Interactions between intradialytic central venous oxygen saturation, relative blood volume, and all-cause mortality in maintenance hemodialysis patients.

INTRODUCTION: In maintenance hemodialysis (HD) patients, low central venous oxygen saturation (ScvO2 ) and small decline in relative blood volume (RBV) have been associated with adverse outcomes. Here we explore the joint association between ScvO2 and RBV change in relation to all-cause mortality. METHODS: We conducted a retrospective study in maintenance HD patients with central venous catheters as vascular access. During a 6-month baseline period, Crit-Line (Fresenius Medical Care, Waltham, MA) was used to measure continuously intradialytic ScvO2 and hematocrit-based RBV. We defined four groups per median change of RBV and median ScvO2 . Patients with ScvO2 above median and RBV change below median were defined as reference. Follow-up period was 3 years. We constructed Cox proportional hazards model with adjustment for age, diabetes, and dialysis vintage to assess the association between ScvO2 and RBV and all-cause mortality during follow-up. FINDINGS: Baseline comprised 5231 dialysis sessions in 216 patients. The median RBV change was -5.5% and median ScvO2 was 58.8%. During follow-up, 44 patients (20.4%) died. In the adjusted model, all-cause mortality was highest in patients with ScvO2 below median and RBV change above median (HR 6.32; 95% confidence interval [CI] 1.37-29.06), followed by patients with ScvO2 below median and RBV change below median (HR 5.04; 95% CI 1.14-22.35), and ScvO2 above median and RBV change above median (HR 4.52; 95% CI 0.95-21.36). DISCUSSION: Concurrent combined monitoring of intradialytic ScvO2 and RBV change may provide additional insights into a patient's circulatory status. Patients with low ScvO2 and small changes in RBV may represent a specifically vulnerable group of patients at particularly high risk for adverse outcomes, possibly related to poor cardiac reserve and fluid overload.

The association of prediabetes and type 2 diabetes with hippocampal subfields volume: The Maastricht study.

AIMS/HYPOTHESIS: We investigated whether prediabetes, type 2 diabetes, and continuous measures of hyperglycemia are associated with tissue volume differences in specific subfields of the hippocampus. METHODS: We used cross-sectional data from 4,724 participants (58.7 ± 8.5 years, 51.5% women) of The Maastricht Study, a population-based prospective cohort. Glucose metabolism status was assessed with an oral glucose tolerance test, and defined as type 2 diabetes (n = 869), prediabetes (n = 671), or normal glucose metabolism (n = 3184). We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1w and FLAIR 3T MRI images. We used multiple linear regression and linear trend analysis, and adjusted for total intracranial volume, demographic, lifestyle, and cardiovascular risk factors. RESULTS: Type 2 diabetes was significantly associated with smaller volumes in the hippocampal subfield fimbria (standardized beta coefficient ± standard error (ß ± SE) = -0.195 ± 0.04, p-value < 0.001), the hippocampus proper, i.e. Cornu Ammonis (CA) 1, CA2/3, CA4, dentate gyrus, subiculum and presubiculum (ß ± SE < -0.105 ± 0.04, p-value < 0.006); as well as the hippocampal tail (ß ± SE = -0.162 ± 0.04, p-value < 0.001). Prediabetes showed no significant associations. However, linear trend analysis indicated a dose-response relation from normal glucose metabolism, to prediabetes, to type 2 diabetes. Multiple continuous measures of hyperglycemia were associated with smaller volumes of the subfields fimbria (ß ± SE < -0.010 ± 0.011, p-value < 0.001), dentate gyrus (ß ± SE < -0.013 ± 0.010, p-value < 0.002), CA3 (ß ± SE < -0.014 ± 0.011, p-value < 0.001), and tail (ß ± SE < -0.006 ± 0.012, p-value < 0.003). CONCLUSIONS/INTERPRETATION: Type 2 diabetes and measures of hyperglycemia are associated with hippocampal subfield atrophy, independently of lifestyle and cardiovascular risk factors. We found evidence for a dose-response relationship from normal glucose metabolism, to prediabetes, to type 2 diabetes. Prediabetes stages could give a window of opportunity for the early prevention of brain disease.

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.

Hyponatraemia and fluid overload are associated with higher risk of mortality in dialysis patients.

BACKGROUND: The 5-year mortality rate for haemodialysis patients is over 50%. Acute and chronic disturbances in salt and fluid homeostasis contribute to poor survival and are established as individual mortality risk factors. However, their interaction in relation to mortality is unclear. METHODS: We used the European Clinical Database 5 to investigate in a retrospective cohort analysis the relationship between transient hypo- and hypernatremia, fluid status and mortality risk of 72 163 haemodialysis patients from 25 countries. Incident haemodialysis patients with at least one valid measurement of bioimpedance spectroscopy were followed until death or administrative censoring from 1 January 2010 to 4 December 2019. Fluid overload and depletion were defined as >2.5 L above, and -1.1 L below normal fluid status, respectively. N = 2 272 041 recorded plasma sodium and fluid status measurements were available over a monthly time grid and analysed in a Cox regression model for time-to-death. RESULTS: Mortality risk of hyponatremia (plasma sodium <135 mmol/L) was slightly increased when fluid status was normal [hazard ratio (HR) 1.26, 95% confidence interval (CI) 1.18-1.35], increased by half when patients were fluid depleted (HR 1.56, 95% CI 1.27-1.93) and accelerated during fluid overload (HR 1.97, 95% CI 1.82-2.12). CONCLUSIONS: Plasma sodium and fluid status act independently as risk factors on mortality. Patient surveillance of fluid status is especially important in the high-risk subpopulation of patients with hyponatremia. Prospective patient-level studies should examine the effects of chronic hypo- and hypernatremia, risk determinants, and their outcome risk.

Wearables in Nephrology: Fanciful Gadgetry or Prêt-à-Porter?

Telemedicine and digitalised healthcare have recently seen exponential growth, led, in part, by increasing efforts to improve patient flexibility and autonomy, as well as drivers from financial austerity and concerns over climate change. Nephrology is no exception, and daily innovations are underway to provide digitalised alternatives to current models of healthcare provision. Wearable technology already exists commercially, and advances in nanotechnology and miniaturisation mean interest is also garnering clinically. Here, we outline the current existing wearable technology pertaining to the diagnosis and monitoring of patients with a spectrum of kidney disease, give an overview of wearable dialysis technology, and explore wearables that do not yet exist but would be of great interest. Finally, we discuss challenges and potential pitfalls with utilising wearable technology and the factors associated with successful implementation.

Deep Learning for Image Analysis in Kidney Care.

Analysis of medical images, such as radiological or tissue specimens, is an indispensable part of medical diagnostics. Conventionally done manually, the process may sometimes be time-consuming and prone to interobserver variability. Image classification and segmentation by deep learning strategies, predominantly convolutional neural networks, may provide a significant advance in the diagnostic process. In renal medicine, most evidence has been generated around the radiological assessment of renal abnormalities and histological analysis of renal biopsy specimens' segmentation. In this article, the basic principles of image analysis by convolutional neural networks, brief descriptions of convolutional neural networks, and their system architecture for image analysis are discussed, in combination with examples regarding their use in image analysis in nephrology.