Clinical Efficacy of SARS-CoV-2 Vaccination in Hemodialysis Patients.

Introduction: The COVID-19 pandemic is a global public health problem. Patients with end-stage renal disease on hemodialysis are at a higher risk of infection and mortality than the general population. Worldwide, a vaccination campaign has been developed that has been shown to reduce severe infections and deaths in the general population. However, there are currently limited data on the clinical efficacy of vaccinations in the hemodialysis population. Methods: A national multicenter observational cohort was performed in Chile to evaluate the clinical efficacy of anti-SARS-CoV-2 vaccination in end-stage renal disease patients on chronic hemodialysis from February 2021 to August 2021. In addition, the BNT162b2 (Pfizer-BioNTech) and CoronaVac (Sinovac) vaccines were evaluated. The efficacy of vaccination in preventing SARS-CoV-2 infection, hospitalizations, and deaths associated with COVID-19 was determined. Results: A total of 12,301 patients were evaluated; 10,615 (86.3%) received a complete vaccination (2 doses), 490 (4.0%) received incomplete vaccination, and 1196 (9.7%) were not vaccinated. During follow-up, 1362 (11.0%) patients developed COVID-19, and 150 died (case fatality rate: 11.0%). The efficacy of the complete vaccination in preventing infection was 18.1% (95% confidence interval [CI]:11.8-23.8%), and prevention of death was 66.0% (95% CI:60.6-70.7%). When comparing both vaccines, BNT162b2 and CoronaVac were effective in reducing infection and deaths associated with COVID-19. Nevertheless, the BNT162b2 vaccine had higher efficacy in preventing infection (42.6% vs. 15.0%) and deaths (90.4% vs. 64.8%) compared to CoronaVac. Conclusion: The results of our study suggest that vaccination against SARS-CoV-2 in patients on chronic hemodialysis was effective in preventing infection and death associated with COVID-19.

Survival study and factors associated with mortality in Chilean patients on peritoneal dialysis infected with SARS-CoV-2.

The Covid-19 pandemic has been responsible for millions of deaths worldwide. Patients with comorbidities- such as those on peritoneal dialysis (PD)- present higher morbidity and mortality than the general population. We prospectively evaluated all Chilean patients on PD (48 centres) and followed those who had Covid-19 from the beginning of the Covid-19 pandemic in Chile (March 2020) to January 2021 (start of vaccination campaign). We described demographic history, comorbidities, factors related to infection, need for hospitalisation and death due to Covid-19. During the study period, 106 adults on PD were infected by SARS-CoV-2, with a mean age of 53.1 (±16.3) and of which 53.9% were female. From that group, 54.8% required hospitalisation and 24.5% (n = 26) died due to Covid-19. Most of the patients (63.4%) were infected at home and 22.8% during hospitalisation for other reasons. There was a significant association for Covid-19 mortality with: being ≥60 years old, diabetes, time on PD ≥5 years, need for hospitalisation and hospital-acquired infection. At 90 days of follow-up, all deaths associated to Covid-19 occurred before 40 days. We conclude that patients on PD without Covid-19 vaccination have a high mortality and need for hospitalisation associated to Covid-19. To avoid this negative outcome, it is necessary to intensify strategies to avoid contagion, especially in those ≥60 years old, with diabetes and/or ≥5 years spent on PD.

Representative locations from time series of soil water content using time stability and wavelet analysis.

The concept of time stability has been widely used in the design and assessment of monitoring networks of soil moisture, as well as in hydrological studies, because it is as a technique that allows identifying of particular locations having the property of representing mean values of soil moisture in the field. In this work, we assess the effect of time stability calculations as new information is added and how time stability calculations are affected at shorter periods, subsampled from the original time series, containing different amounts of precipitation. In doing so, we defined two experiments to explore the time stability behavior. The first experiment sequentially adds new data to the previous time series to investigate the long-term influence of new data in the results. The second experiment applies a windowing approach, taking sequential subsamples from the entire time series to investigate the influence of short-term changes associated with the precipitation in each window. Our results from an operating network (seven monitoring points equipped with four sensors each in a 2-ha blueberry field) show that as information is added to the time series, there are changes in the location of the most stable point (MSP), and that taking the moving 21-day windows, it is clear that most of the variability of soil water content changes is associated with both the amount and intensity of rainfall. The changes of the MSP over each window depend on the amount of water entering the soil and the previous state of the soil water content. For our case study, the upper strata are proxies for hourly to daily changes in soil water content, while the deeper strata are proxies for medium-range stored water. Thus, different locations and depths are representative of processes at different time scales. This situation must be taken into account when water management depends on soil water content values from fixed locations.