Introduction: Inadequate fluid status remains a key driver of cardiovascular morbidity and mortality in chronic hemodialysis (HD) patients. Quantification of fluid overload (FO) using bioimpedance spectroscopy (BIS) has become standard in many countries. To date, no BIS device has been approved in the United States for fluid status assessment in kidney patients. Therefore, no previous quantification of fluid status in US kidney patients using BIS has been reported. Our aim was to conduct a cross-sectional BIS-based assessment of fluid status in an urban US HD population. Methods:We determined fluid status in chronic HD patients using whole body BIS (Body Composition Monitor, BCM). The BCM reports FO in liters; negative FO denotes fluid depletion. Measurements were performed before dialysis. Post-HD FO was estimated by subtracting the intradialytic weight loss from the pre-HD FO.Findings: We studied 170 urban HD patients (age 61 AE 14 years, 60% male). Pre-and post-HD FO (mean AE SD), were 2.2 AE 2.4 and À0.2 AE 2.7 L, respectively. Pre-HD, 43% of patients were fluid overloaded, 53% normally hydrated, and 4% fluid depleted. Post-HD, 12% were fluid overloaded, 55% normohydrated and 32% fluid depleted. Only 48% of fluid overloaded patients were hypertensive, while 38% were normotensive and 14% hypotensive. Fluid status did not differ significantly between African Americans (N = 90) and Caucasians (N = 61). Discussion: While about half of the patients had normal fluid status pre-HD, a considerable proportion of patients was either fluid overloaded or depleted, indicating the need for tools to objectively quantify fluid status.
Background To date it is unclear whether SARS-CoV-2 is present in spent dialysate from peritoneal dialysis (PD) patients with COVID-19. Our aim was to assess the presence or absence of SARS-CoV-2 in spent dialysate from chronic PD patients with confirmed diagnosis of COVID-19. Methods Spent PD dialysate samples from COVID-19 positive PD patients were collected between March and August 2020. The multiplexed real-time reverse transcriptase-polymerase chain reaction assay contained primer/probe sets specific to different SARS-CoV-2 genomic regions and to bacteriophage MS2 as 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 10 dialysis centers. Spent PD dialysate samples were collected on average 25±13 days (median 20, range 10 to 45) after onset of symptoms. The temporal distance of PD effluent collection relative to the closest positive nasal swab RT PCR was 15±11 days (median 14; range 1 to 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 10 days or later after the onset of COVID-19 symptoms. We cannot rule out presence of SARS-CoV-2 in spent PD dialysate in the early stage of COVID-19.
<b><i>Background/Objectives:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> 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. <b><i>Conclusion:</i></b> 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.
Raised levels of the cardiac biomarker, Troponin I, are frequently encountered in hemodialysis patients and appear to be prognostic indicators for cardiovascular risk. Though evidence suggests that control of secondary hyperparathyroidism may reduce cardiac endpoints, the effect of the calcimimetic agent, cinacalcet, remains controversial. This retrospective study aimed at evaluating troponin levels in hemodialysis patients with severe secondary hyper parathyroidism (SHPT) who are on cinacalcet vs controls on conventional treatment. In addition, clinical outcomes including all-cause, cardiovascular morbidity and mortality were compared among both groups. A decline in Troponin I levels was observed in the cinacalcet group, this however was not translated clinically into improved survival. In fact, all-cause and cardiac mortality was similar in the two groups. Conversely, comparison of the incidence of cardiovascular events revealed lower rates in the cinacalcet group including cardiac, cerebral and peripheral vascular complications. Given some of our study limitations, further long-term, placebo-controlled trials are necessary to definitively establish the effect of cinacalet on cardiac biomarkers and ultimately its impact on clinical outcomes.
Background and Aims Pervasive sensing technologies allow healthcare providers to gain additional insights into patient’s status outside the clinical setting. In order to adopt widespread use of remote monitoring devices we must first study the feasibility of their use. We aim to quantify how long patients will use a wearable device before requiring an intervention to maintain the use of the device. Method In-center hemodialysis (HD) patients were enrolled from 4 clinics in New York City starting in May 2018 and followed for a period of up to 1 year. Patients ≥18 years, on HD ≥3 months, able to walk, owning a smartphone, mobile tablet or PC were enrolled. They were provided with a wrist-based monitoring device (Fitbit Charge 2). Participants were instructed on how to use the device, and sync data to their smartphone, mobile tablet, or PC. If a patient failed to sync data for 7 consecutive days, a text message or email reminder was sent from the research staff. We evaluated time to first notification using Kaplan Meier time-to-event analysis. Predictors of time to first intervention was assessed via univariate Cox Regression. Patients were censored at the end of the observation period (January 6, 2020). Socio-economic parameters such as living situation, marriage status, employment status, race, and education level were collected at the beginning of the study. Results 125 patients were enrolled into our study. 7 patients were screen-failed after enrollment. At enrollment patients were 54±12 years old with a dialysis vintage of 5.6±5.8 years. 37% lived alone, 56% were single, 59% unemployed, 64% were African-American, and 42% had an education level of some college or higher. 82% of the patients required a text message reminder to continue wearing/syncing the device. Mean and median time to first reminder were 101 days (95% CI 80 to 123) and 50 days (95% CI 35 to 70 days), respectively. The probability of being on the study without intervention is shown in Figure 1. Predictors of time to first intervention were chosen a priori and included gender, age, living situation, and education level. None of these parameters were significant predictors of time to first intervention. Conclusion We found that most patients will require at least some intervention or counseling to maintain the use of a wrist-based wearable device for remote patient monitoring. While most patients require an intervention before approximately 2 months into wear, the patients who can maintain use independently after that point are likely to do so for longer.
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