SARS-CoV-2 neutralizing antibody response after three doses of mRNA1273 vaccine and COVID-19 in hemodialysis patients.

Background: In hemodialysis patients, a third vaccination is frequently administered to augment protection against coronavirus disease 2019 (COVID-19). However, the newly emerged B.1.1.159 (Omicron) variant may evade vaccinal protection more easily than previous strains. It is of clinical interest to better understand the neutralizing activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants after booster vaccine or COVID-19 infection in these mostly immunocompromised patients. Methods: Hemodialysis patients from four dialysis centers were recruited between June 2021 and February 2022. Each patient provided a median of six serum samples. SARS-CoV-2 neutralizing antibodies (nAbs) against wild type (WT) or Omicron were measured using the GenScript SARS-CoV-2 Surrogate Virus Neutralization Test Kit. Results: Forty-two patients had three doses of mRNA1273. Compared to levels prior to the third dose, nAb-WT increased 18-fold (peak at day 23) and nAb-Omicron increased 23-fold (peak at day 24) after the third dose. Peak nAb-WT exceeded peak nAb-Omicron 27-fold. Twenty-one patients had COVID-19 between December 24, 2021, and February 2, 2022. Following COVID-19, nAb-WT and nAb-Omicron increased 12- and 40-fold, respectively. While levels of vaccinal and post-COVID nAb-WT were comparable, post-COVID nAb-Omicron levels were 3.2 higher than the respective peak vaccinal nAb-Omicron. Four immunocompromised patients having reasons other than end-stage kidney disease have very low to no nAb after the third dose or COVID-19. Conclusions: Our results suggest that most hemodialysis patients have a strong humoral response to the third dose of vaccination and an even stronger post-COVID-19 humoral response. Nevertheless, nAb levels clearly decay over time. These findings may inform ongoing discussions regarding a fourth vaccination in hemodialysis patients.

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.

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.

SARS-CoV-2 in Spent Dialysate from Chronic Peritoneal Dialysis Patients with COVID-19.

Background: To date, it is unclear whether SARS-CoV-2 is present in spent dialysate from patients with COVID-19 on peritoneal dialysis (PD). Our aim was to assess the presence or absence of SARS-CoV-2 in spent dialysate from patients on chronic PD who had a confirmed diagnosis of COVID-19. Methods: Spent PD dialysate samples from patients on PD who were positive for COVID-19 were collected between March and August 2020. The multiplexed, real-time RT-PCR assay contained primer/probe sets specific to different SARS-CoV-2 genomic regions and to bacteriophage MS2 as an internal process control for nucleic acid extraction. Demographic and clinical data were obtained from patients' electronic health records. Results: A total of 26 spent PD dialysate samples were collected from 11 patients from ten dialysis centers. Spent PD dialysate samples were collected, on average, 25±13 days (median, 20; range, 10-45) after the onset of symptoms. The temporal distance of PD effluent collection relative to the closest positive nasal-swab RT-PCR result was 15±11 days (median, 14; range, 1-41). All 26 PD effluent samples tested negative at three SARS-CoV-2 genomic regions. Conclusions: Our findings indicate the absence of SARS-CoV-2 in spent PD dialysate collected at ≥10 days after the onset of COVID-19 symptoms. We cannot rule out the presence of SARS-CoV-2 in spent PD dialysate in the early stage of COVID-19.

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.

Patient perception of vitality and measured physical activity in patients receiving haemodialysis.

AIM: Fatigue in haemodialysis (HD) patients can be captured in quality of life questionnaires and by the dialysis recovery time (DRT) question. The associations between fatigue and measured physical activity has not been explored until the present. We tested our hypothesis that the patient perception of chronic and post dialysis fatigue would be associated with lower physical activity. METHODS: This study was a cross sectional evaluation of baseline data from HD patients recruited in the HDFIT trial. Vitality scores from the Kidney Disease Quality of Life (KDQOL-36) and the dialysis recovery time (DRT) question were used as indicators of chronic and post dialysis fatigue, respectively. Granular physical activity was measured by accelerometers as part of the study protocol. RESULTS: Among 176 patients, Vitality score was 63 ± 21 and the DRT was ≤30 minutes in 57% of patients. The mean number of steps was 5288 ± 3540 in 24 hours after HD and 953 ± 617 in the 2-hour post-HD period. The multivariable analysis confirmed Vitality scores were associated with physical activity in the 24-hour post-HD period. In contrast, DRT was not associated with physical activity captured by the accelerometer in the period immediately (2 hours) after the HD session. CONCLUSION: Chronic fatigue was negatively associated with step counts, while patient perception of post-dialysis fatigue was not associated with physical activity. These patterns indicate limitations in interpretation of DRT. Since physical activity is an important component of a healthy life, our results may partially explain the associations between fatigue and poor outcomes in HD patients.

Impact of hemodialysis and post-dialysis period on granular activity levels.

BACKGROUND: Physical activity (PA) is typically lower on hemodialysis (HD) days. Albeit intradialytic inactivity is expected, it is unknown whether recovery after HD contributes to low PA. We investigated the impact of HD and post-HD period on granular PA relative to HD timing. METHODS: We used baseline data from the HDFIT trial conducted from August 2016 to October 2017. Accelerometry measured PA over 1 week in patients who received thrice-weekly high-flux HD (vintage 3 to 24 months), were clinically stable, and had no ambulatory limitations. PA was assessed on HD days (0 to ≤24 h after start HD), first non-HD days (> 24 to ≤48 h after start HD) and second non-HD day (> 48 to ≤72 h after start HD). PA was recorded in blocks/slices: 4 h during HD, 0 to ≤2 h post-HD (30 min slices), and > 2 to ≤20 h post-HD (4.5 h slices). Blocks/slices of PA were captured at concurrent/parallel times on first/second non-HD days compared to HD days. RESULTS: Among 195 patients (mean age 53 ± 15 years, 71% male), step counts per 24-h were 3919 ± 2899 on HD days, 5308 ± 3131 on first non-HD days (p < 0.001), and 4926 ± 3413 on second non-HD days (p = 0.032). During concurrent/parallel times to HD on first and second non-HD days, patients took 1308 and 1128 more steps (both p < 0.001). Patients took 276 more steps and had highest rates of steps/hour 2-h post-HD versus same times on first non-HD days (all p < 0.05). Consistent findings were observed on second non-HD days. CONCLUSIONS: PA was higher within 2-h of HD versus same times on non-HD days. Lower PA on HD days was attributable to intradialytic inactivity. The established PA profiles are of importance to the design and development of exercise programs that aim to increase activity during and between HD treatments. TRIAL REGISTRATION: HDFIT was prospectively registered 20 April 2016 on ClinicalTrials.gov (NCT02787161).

Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in turn, may make 4P medicine (predictive, precise, preventive and personalized) a more attainable goal within dialysis patient care. This article discusses different use cases where WHD could be of relevance for dialysis patient care, i.e. measurement of heart rate, arrhythmia detection, blood pressure, hyperkalaemia, fluid overload and physical activity. After adequate validation of the different WHD in this specific population, data obtained from WHD could form part of a body area network (BAN), which could serve different purposes such as feedback on actionable parameters like physical inactivity, fluid overload, danger signalling or event prediction. For a BAN to become clinical reality, not only must technical issues, cybersecurity and data privacy be addressed, but also adequate models based on artificial intelligence and mathematical analysis need to be developed for signal optimization, data representation, data reliability labelling and interpretation. Moreover, the potential of WHD and BAN can only be fulfilled if they are part of a transformative healthcare system with a shared responsibility between patients, healthcare providers and the payors, using a step-up approach that may include digital assistants and dedicated 'digital clinics'. The coming decade will be critical in observing how these developments will impact and transform dialysis patient care and will undoubtedly ask for an increased 'digital literacy' for all those implicated in their care.

Effect of Hemodiafiltration on Self-Reported Sleep Duration: Results from a Randomized Controlled Trial.

INTRODUCTION: Dialysis patients suffer from poor sleep duration and quality. We examined the self-reported sleep duration in patients randomized to either high-volume hemodiafiltration (HDF) or high flux hemodialysis (HD). METHODS: Patients from 13 Brazilian dialysis clinics were enrolled in the HDFIT randomized controlled trial (RCT) investigating the impact of HDF on physical activity and self-reported outcomes. Self-reported sleep duration was taken from patient diaries recording sleep start and end time over a week during baseline, months 3 and 6, respectively. Sleep duration was analyzed by shift and nights relative to dialysis. RESULTS: The HDFIT study enrolled 197 patients; sleep data were available in 173 patients (87 HD; 86 HDF). Patients' age was 53 ± 15 years, 57% were white, 72% were male, 34% had diabetes, Kt/V was 1.54 ± 0.40, and albumin 3.97 ± 0.36 g/dL. Most patients reported sleeping 510-530 min/night. At 3 months, HDF patients slept 513 ± 71 min/night, HD patients 518 ± 76 min/night. At 6 months, HDF patients slept 532 ± 74 min/night, HD patients 519 ± 80 min/night. At baseline, 1st shift patients slept 406 ± 86 min the night before HD, 534 ± 64 min the night after HD, and 496 ± 99 min the night between 2 non-HD days. Compared to patients in the 2nd and 3rd shifts, patients dialyzed in the 1st shift slept less in the night before dialysis. Similar patterns were seen after 3 and 6 months. CONCLUSION: In our RCT, the dialysis modality (HDF vs. HD) had no effect on self-reported sleep duration. In both groups, dialysis in the 1st shift adversely affected self reported sleep duration.

Relationships between Neighborhood Walkability and Objectively Measured Physical Activity Levels in Hemodialysis Patients.

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.

Physical Activity and Sleep Patterns in Hemodialysis Patients in a Suburban Environment.

BACKGROUND/AIMS: Hemodialysis (HD) patients are less active than their healthy counterparts. They are often plagued with sleep disorders that affect the quality of their sleep. Our aim was to objectively quantify activity and sleep quality among HD patients in a suburban HD population. METHODS: Activity and sleep parameters were measured using a commercially available activity tracker in 29 HD patients from Baton Rouge, LA, USA. Patients in the feedback group received their activity and sleep data at each dialysis treatment. In addition, questionnaires were administered at the beginning and end of the study period. Patients were stratified based on activity levels and sleep quality. RESULTS: Patients walked an average of 5,281 steps/day and slept 370.5 min/night. Informing patients about their daily number of steps taken, did not increase activity. Only 3% of the population followed were active, defined as walking more than 10,000 steps per day. Patients walked significantly less on dialysis days compared to the other days of the week. Many of the patients experienced poor sleep quality, with patients in the first shift experiencing the greatest disturbance to their sleep/wake cycle. CONCLUSION: Patients in a suburban environment walked much less than those in a previously studied urban population. They rarely met the recommended goal of 10,000 steps/day, even on non-dialysis days. Interventions to increase physical activity may target any day of the week, particularly HD days. Prospective, long-term studies are needed to evaluate the use of activity trackers in dialysis patients and their impact on physical activity.

Quantifying Physical Activity Levels and Sleep in Hemodialysis Patients Using a Commercially Available Activity Tracker.

BACKGROUND/AIMS: Hemodialysis (HD) patients are less active than their healthy counterparts and frequently experience poor sleep. Our aims were to objectively quantify activity and sleep quality in HD patients of an urban population and to determine the effect of providing feedback on activity. METHODS: Activity parameters and sleep parameters were collected by a commercially available activity tracker in 29 chronic HD patients. Patients in the feedback group were provided with their activity and sleep data during each HD treatment. Questionnaires were administered at the beginning and at the end of the study. RESULTS: On average, patients walked 8,454 steps/day and slept 349 min/night. Only 28% of the patients were sedentary, defined as walking <5,000 steps/day. Providing feedback did not increase the activity in this urban population. Patients walked significantly less on Sundays compared to other days of the week: 7,024 steps on Sundays vs. 8,633 steps on HD days and 8,732 on non-HD days. It was also found that patients experienced poor sleep quality. HD treatments during shift 1 (6 a.m. to 10 a.m.) interfered with sleep patterns. Most patients reported that physical activity became more important to them after the 5-week period. The tracking device was very well accepted. CONCLUSION: Interventions to increase physical activity on Sundays could improve physical activity levels overall. Prospective studies are necessary to further explore the use of tracking devices to identify patients at risk and to implement targeted interventions.

It's a non-dialysis day Do you know how your patient is doing? A case for research into interdialytic activity.

Hemodialysis (HD) patients are less active than their healthy counterparts; this is associated with higher mortality. Healthcare workers observe their patients only during HD, which accounts for about 7% of the week. Knowing more about what occurs in between sessions, particularly with respect to physical activity, may improve patient care and prognosis. Yet without a standard method to measure interdialytic activity, it is difficult to compare the effect of interventions. However, it is unclear how interdialytic activity can be accurately measured. Since activity associated with quality of life is multi-dimensional, objective and subjective tools should be used in conjunction. While commercially available tracking devices can be seamlessly incorporated into everyday life and can increase awareness of user's activity, their validation is needed in the HD population. Fertile topics for research should include the relationship between objective and subjective measures in HD patients, and the investigation of physical activity in non-ambulatory HD patients.