Background An integrated kidney disease healthcare company implemented a peritoneal dialysis (PD) remote treatment monitoring (RTM) application in 2016. We assessed if RTM utilization associates with hospitalization and technique failure rates.Methods We used data from adult (age $18 years) patients on PD treated from October 2016 through May 2019 who registered online for the RTM. Patients were classified by RTM use during a 30-day baseline after registration. Groups were: nonusers (never entered data), moderate users (entered one to 15 treatments), and frequent users (entered .15 treatments). We compared hospital admission/day and sustained technique failure (required .6 consecutive weeks of hemodialysis) rates over 3, 6, 9, and 12 months of follow-up using Poisson and Cox models adjusted for patient/clinical characteristics.Results Among 6343 patients, 65% were nonusers, 11% were moderate users, and 25% were frequent users. Incidence rate of hospital admission was 22% (incidence rate ratio [IRR]50.78; P50.002), 24% (IRR50.76; P,0.001), 23% (IRR50.77; P#0.001), and 26% (IRR50.74; P#0.001) lower in frequent users after 3, 6, 9, and 12 months, respectively, versus nonusers. Incidence rate of hospital days was 38% (IRR50.62; P50.013), 35% (IRR50.65; P50.001), 34% (IRR50.66; P#0.001), and 32% (IRR50.68; P,0.001) lower in frequent users after 3, 6, 9, and 12 months, respectively, versus nonusers. Sustained technique failure risk at 3, 6, 9, and 12 months was 33% (hazard ratio [HR]50.67; P50.020), 31% (HR50.69; P50.003), 31% (HR50.69; P50.001), and 27% (HR50.73; P50.001) lower, respectively, in frequent users versus nonusers. Among a subgroup of survivors of the 12-month follow-up, sustained technique failure risk was 26% (HR50.74; P50.023) and 21% (HR50.79; P50.054) lower after 9 and 12 months, respectively, in frequent users versus nonusers.Conclusions Our findings suggest frequent use of an RTM application associates with less hospital admissions, shorter hospital length of stay, and lower technique failure rates. Adoption of RTM applications may have the potential to improve timely identification/intervention of complications.

Abnormal decreases in blood pressure during hemodialysis are frequent in end stage renal disease (ESRD) patients treated with hemodialysis, and thought to be largely due to an inadequate cardiovascular response to the rapid blood volume decline. Intradialytic hypotension (IDH) and cardiac instability during dialysis can increase risks for negative health consequences and is possibly preventable though several types of interventions. One intervention that holds promise for prevention of IDH in hemodialysis patients is to reduce the temperature of the dialysate to or below the patient's core temperature. A considerable number of randomized studies have demonstrated a short term benefit of using a cooler dialysate temperature for the prevention of IDH and improved cardiac stability. Despite this, a key observational study was not able to show long term improvements with lower dialysate temperatures utilized in routine clinical practice, albeit possibly confounded by indication. It appears that cooling the dialysate may be reasonable to consider on an individual basis for patients who suffer from persistent IDH if they can tolerate the adjustment and it is effective. However, careful assessment of the etiology of IDH should be performed when considering treatment options. In this review, we detail the current body of evidence on the effectiveness of using low dialysate temperatures for prevention of IDH in ESRD patients, and suggest areas where further research is needed.

Systemic ethanol (EtOH) administration activates the hypothalamic-pituitary-adrenal (HPA) axis of rats in a sexually dimorphic manner. The present studies tested the role played by the CNS in this phenomenon. In order to localize the effects of the drug to the brain, we utilized an EtOH administration paradigm whereby a small, non-toxic amount of the drug was delivered intracerebroventricularly (icv). Icv EtOH rapidly diffuses throughout the CSF and brain, and does not cause neuronal damage or have any long-term physiological or behavioral effects. Experimental groups included intact males, intact cycling females, and ovariectomized (OVX) animals with or without replacement estradiol (E2). Icv EtOH-induced HPA hormonal activation was determined by measuring plasma adrenocorticotropin (ACTH) levels. Activation of brain areas that both regulate HPA function and are responsive to gonadal hormones was determined using expression of the transcription factor c-fos (Fos) as a marker of neuronal activity. We observed sex-and estrous cycle-dependent differences in HPA activation by EtOH as measured by both these parameters. ACTH secretion was highest in females in proestrus or estrus, just prior to and after the endogenous peak of E2, as was Fos expression in the paraventricular nucleus of the hypothalamus (PVN) and the locus coreuleus (LC) of the brainstem. In OVX animals, E2 replacement caused an increase in PVN and LC Fos expression in response to icv EtOH as compared to OVX controls, but a decrease in ACTH secretion. Taken together these results indicate that at the level of the CNS, EtOH stimulates HPA activity more robustly at times when the effects of E2 are high, but that E2 alone is not responsible for the effect. The data further suggest that the LC plays an important role in the circuitry, which appears to be different from that activated following the systemic administration of EtOH.

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.

Background and objectives High‐volume online hemodiafiltration (OL‐HDF) associates with improved outcomes compared to hemodialysis (HD), provided adequate dosing is achieved as estimated from convective volume (CV). Achievement of high CV and its impact on biochemical indicators following a standardized protocol converting HD patients to OL‐HDF has not been systematically reported. We assessed the success of implementation of OL‐HDF in clinics naïve to the modality. Design, setting, participants, and measurements We analyzed the results of the implementation of postdilution OL‐HDF in patients randomized to the HDF arm of a clinical trial (impact of hemoDiaFIlTration on physical activity and self‐reported outcomes: a randomized controlled trial (HDFit) trial [http://clinicaltrials.gov:NCT02787161]). The day before randomization of the first patient to OL‐HDF at each clinic staff started a 3‐day in‐person training module on operation of Fresenius 5008 CorDiax machine in HDF mode. Patients were converted from high‐flux HD to OL‐HDF under oversight of trainers. OL‐HDF was performed over a 6‐months follow‐up with a CV target of 22 L/treatment. We characterized median achieved CV >22 L/treatment record and analyzed the impact of HDF on biochemical variables. Results Ninety‐seven patients (mean age 53 ± 16 years, 29% with diabetes, and 11% had a catheter) from 13 clinics randomized to the OL‐HDF arm of the trial were converted from HD to HDF. Median CV > 22 L/treatment was achieved in 99% (94/95) of OL‐HDF patients throughout follow‐up. Monthly mean CV ranged from 27.1 L to 27.5 L. OL‐HDF provided an increased single pool Kt/V at 3‐months (0.2 [95% CI: 0.1–0.3]) and 6‐months (0.2 [95% CI: 0.1–0.4]) compared to baseline, and reduced phosphate at 3‐months (−0.4 mg/dL [95% CI: −0.8 to −0.12]) of follow‐up. Conclusions High‐volume online hemodiafiltration was successfully implemented with 99% of patients achieving protocol defined CV target. Monthly mean CV was consistently >22 L/treatment during follow‐up. Kt/V increased, and phosphate decreased with OL‐HDF. Findings resulting from a short training period in several dialysis facilities appear to suggest HDF is an easily implementable technique.

Background/Aims: Neighborhood walkability is associated with indicators of health in the general population. We explored the association between neighborhood walkability and daily steps in hemodialysis (HD) patients. Methods: We measured daily steps over 5 weeks using Fitbit Flex (Fitbit, San Francisco, CA, USA) and retrieved Walk Score® (WS) data by patient’s home ZIP code (www.walkscore.com; 0 = poorest walkability; 100 = greatest walkability). Results: HD patients took a mean of 6,393 ± 3,550 steps/day (n = 46). Median WS of the neighborhood where they resided was 28. Patients in an above-median WS (n = 27) neighborhood took significantly more daily steps compared to those (n = 19) in a below-median WS neighborhood (7,514 ± 3,900 vs. 4,800 ± 2,228 steps/day; p < 0.001, t test). Daily steps and WS were directly correlated (R = 0.425; p = 0.0032, parametric test; R = 0.359, p = 0.0143, non-parametric test). Conclusion: This is the first study conducted among HD patients to indicate a direct relationship between neighborhood walkability and the actual steps taken. These results should be considered when designing initiatives to increase and improvise exercise routines in HD populations.

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.

BackgroundHealth-related quality of life (HrQoL) varies among dialysis patients. However, little is known about the association of dialysis modality with HrQoL over time. We describe longitudinal patterns of HrQoL among chronic dialysis patients by treatment modality.MethodsNational retrospective cohort study of adult patients who initiated in-center dialysis or a home modality (peritoneal or home hemodialysis) between 1/2013 and 6/2015. Patients remained on the same modality for the first 120 days of the first two years. HrQoL was assessed by the Kidney Disease and Quality of Life-36 (KDQOL) survey in the first 120 days of the first two years after dialysis initiation. Home modality patients were matched to in-center patients in a 1:5 fashion.ResultsIn-center (n=4234) and home modality (n=880) patients had similar demographic and clinical characteristics. In-center dialysis patients had lower mean KDQOL scores across several domains compared to home modality patients. For patients who remained on the same modality, there was no change in HrQoL. However, there were trends towards clinically meaningful changes in several aspects of HrQoL for patients who switched modalities. Specifically, physical functioning decreased for patients who switched from home to in-center dialysis (p< 0.05).ConclusionsAmong a national cohort of chronic dialysis patients, there was a trend towards different patterns of HrQoL life that were only observed among patients who changed modality. Patients who switched from home to in-center modalities had significant lower physical functioning over time. Providers and patients should be mindful of HrQoL changes that may occur with dialysis modality change.Electronic supplementary materialThe online version of this article (10.1186/s12882-018-1198-5) contains supplementary material, which is available to authorized users.