Modifiable and Non-Modifiable Factors Associated With Increased COVID-19 Related Mortality Among Dialysis Patients

BACKGROUND AND AIMS Patients with end-stage kidney disease (ESKD) face higher risk for severe outcomes from COVID-19 infection. Moreover, it is not well known to which extent potentially modifiable risk factors contribute to mortality risk. In this study, we investigated the incidence and risk factors for 30-day case-fatality of COVID-19 in haemodialysis patients treated in the European Fresenius Medical Care (FMC) Nephrocare network. METHOD In this historical cohort study, we included unvaccinated adult dialysis patients with a first documented SARS-CoV-2 infection between 1 February 2020 and 31 March 2021 (study period) registered in the European Clinical Database (EuCliD®). The first SARS-CoV-2 suspicion date for all documented infections was considered the index date for the analysis. Patients were followed for up to 30 days. Follow-up time was defined from the index date until the date of death, end of follow-up period or lost to follow-up, whichever occurred first. We ascertained patients’ characteristics in the 6-month period prior to index date. We used logistic regression and XGBoost to assess risk factors for 30-day mortality. RESULTS We included 9211 patients meeting the inclusion criteria for the study (Table 1). Age was 65.4 ± 13.7 years, dialysis vintage was 4.2 ± 3.7 years. In the follow up period, 1912 patients died within 30 days (20.8%, 95% confidence interval: 19.9%–21.6%). Correlates of COVID-19 related mortality are summarized in Table 2. Several potentially modifiable factors were associated with increased risk of death: patients on HD compared with online haemodiafiltration had shorter survival after presentation with COVID-19 as well as those who did not achieve the therapeutic targets for serum albumin, erythropoietin resistance index, protein catabolic rate, haemodynamic status, C-reactive protein, single-pool Kt/V, hydration status and serum sodium in the months before infection. The discrimination accuracy of prediction models developed with XGBoost was similar to that observed for main-effect logistic regression (AUC 0.69 and 0.71, respectively) suggesting that no major cross-interaction and non-linear effect could improve prediction accuracy. CONCLUSION We observed high 30-day COVID-19 related mortality among unvaccinated dialysis patients. Older patients, men and those with greater comorbidities had higher risk of death after COVID-19 infection. Derangement in potentially modifiable factors in the 6 months prior to COVID-19 infection was independently associated with increased mortality. Whether achievement of clinical therapeutic targets is associated with improved survival after COVID-19 infection is a matter of further research.

Effectiveness of Covid-19 Vaccines in a Large European Haemodialysis Cohort

BACKGROUND AND AIMS To date, no large-scale study has evaluated the effectiveness of COVID-19 vaccines in hemodialysis patients. We sought to evaluate the effectiveness of vaccines against SARS-CoV-2 infections and death in haemodialysis patients registered in the Fresenius Medical Care (FMC) Nephrocare network. METHOD In this historical, 1:1 matched cohort study, we analysed electronic health records (EHR) of individuals receiving in-center haemodialysis therapy in FMC European dialysis clinics from 1 December 2020, to 31 May 2021 (study period). For each vaccinated patient, an unvaccinated patient was selected among patients registered in the same country and attending a dialysis session within +/–3 days from the vaccination date. Matching without replacement was based on demographics, clinical characteristics, past COVID-19 infections and a risk score representing the local (dialysis centre) background risk of infection at each vaccination date. The infection risk score was calculated from an artificial Intelligence model predicting the risk of COVID-19 outbreak in each clinic over a 2-week prediction horizon. The infection risk score was based on trends in regional COVID-19 epidemic metrics, FMC COVID-19 reporting system and clinical practice patterns. The index date was the date of the first vaccination for the vaccinated and the matching treatment date for the unvaccinated controls. To overcome violation of the proportional hazard assumption, we estimated the effectiveness of the COVID-19 vaccines in preventing infection and mortality rates as 1—hazard ratio estimated from a time-dependent extended Cox regression stratified by country and vaccine type. RESULTS We included 44 458 patients, 22 229 vaccinated and matched 22 229 unvaccinated. Distribution of covariates was balanced across study arms after matching (Figure 1A). In the effectiveness analysis on mRNA vaccines, we observed 850 SARS-CoV-2 infections and 201 COVID19-related deaths among the 28 110 patients (14 055 vaccinated and 14 055 unvaccinated) during a mean follow up time of 44 ± 40 days. In the effectiveness analysis of viral-vector vaccines, we observed 297 SARS-CoV-2 infections and 64 COVID19-related deaths among 12 888 patients (6444 vaccinated and 6444 unvaccinated) during a mean a follow-up time of 48 ± 32 days (Figure 1B). We observed 18.5/100 patient-year and 8.5/100 patient-year fewer infections and 5.4/100 patient-year and 5.2/100 patient-year fewer COVID-19-related deaths among patients vaccinated with mRNA and viral-vector vaccines respectively, as compared to matched unvaccinated controls. The effectiveness of COVID-19 vaccines concerning both symptomatic infections and COVID-related death along the follow up period is shown in Figure 2. CONCLUSION In this matched, historical cohort study, we observed a strong reduction in both SARS-CoV-2 symptomatic infection and COVID-19-related death among dialysis patients receiving an mRNA vaccine. Despite seemingly less protective against symptomatic infections, we observed similar reduction in COVID-19 mortality rate among patients receiving a viral-carrier vaccine.FIGURE 1A: Forest Plot demonstrating covariate distribution balance between exposure groups. Effect Sizes calculated as Cohen's d or Cromer's Negative coefficient indicates that mean or relative frequency was greater among vaccinated patients. Effect Size 0.12 negligible Effect Size-0.1-0.2: small.FIGURE 1B: Absolute frequency and incidence density (95% confidence intervall of events across exposure groups.FIGURE 2: Effectiveness (1-HR) estimates by vaccine type concerning symptomatic, documented infection and COVID-19 related death. Estimates were obtained from extended, cox regression with time-varying covariate.

Transmission of SARS-CoV-2 considering shared chairs in outpatient dialysis: a real-world case-control study.

BACKGROUND: SARS-CoV-2 can remain transiently viable on surfaces. We examined if use of shared chairs in outpatient hemodialysis associates with a risk for indirect patient-to-patient transmission of SARS-CoV-2. METHODS: We used data from adults treated at 2,600 hemodialysis facilities in United States between February 1st and June 8th, 2020. We performed a retrospective case-control study matching each SARS-CoV-2 positive patient (case) to a non-SARS-CoV-2 patient (control) treated in the same dialysis shift. Cases and controls were matched on age, sex, race, facility, shift date, and treatment count. For each case-control pair, we traced backward 14 days to assess possible prior exposure from a 'shedding' SARS-CoV-2 positive patient who sat in the same chair immediately before the case or control. Conditional logistic regression models tested whether chair exposure after a shedding SARS-CoV-2 positive patient conferred a higher risk of SARS-CoV-2 infection to the immediate subsequent patient. RESULTS: Among 170,234 hemodialysis patients, 4,782 (2.8 %) tested positive for SARS-CoV-2 (mean age 64 years, 44 % female). Most facilities (68.5 %) had 0 to 1 positive SARS-CoV-2 patient. We matched 2,379 SARS-CoV-2 positive cases to 2,379 non-SARS-CoV-2 controls; 1.30 % (95 %CI 0.90 %, 1.87 %) of cases and 1.39 % (95 %CI 0.97 %, 1.97 %) of controls were exposed to a chair previously sat in by a shedding SARS-CoV-2 patient. Transmission risk among cases was not significantly different from controls (OR = 0.94; 95 %CI 0.57 to 1.54; p = 0.80). Results remained consistent in adjusted and sensitivity analyses. CONCLUSIONS: The risk of indirect patient-to-patient transmission of SARS-CoV-2 infection from dialysis chairs appears to be low.

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.

Arterial oxygen saturation and hypoxemia in hemodialysis patients with COVID-19.

BACKGROUND: Maintenance hemodialysis (MHD) patients are particularly vulnerable to coronavirus disease 2019 (COVID-19), a viral disease that may cause interstitial pneumonia, impaired alveolar gas exchange and hypoxemia. We ascertained the time course of intradialytic arterial oxygen saturation (SaO2) in MHD patients between 4 weeks pre-diagnosis and the week post-diagnosis of COVID-19. METHODS: We conducted a quality improvement project in confirmed COVID-19 in-center MHD patients from 11 dialysis facilities. In patients with an arterio-venous access, SaO2 was measured 1×/min during dialysis using the Crit-Line monitor (Fresenius Medical Care, Waltham, MA, USA). We extracted demographic, clinical, treatment and laboratory data, and COVID-19-related symptoms from the patients' electronic health records. RESULTS: Intradialytic SaO2 was available in 52 patients (29 males; mean ± standard deviation age 66.5 ± 15.7 years) contributing 338 HD treatments. Mean time between onset of symptoms indicative of COVID-19 and diagnosis was 1.1 days (median 0; range 0-9). Prior to COVID-19 diagnosis the rate of HD treatments with hypoxemia, defined as treatment-level average SaO2 <90%, increased from 2.8% (2-4 weeks pre-diagnosis) to 12.2% (1 week) and 20.7% (3 days pre-diagnosis). Intradialytic O2 supplementation increased sharply post-diagnosis. Eleven patients died from COVID-19 within 5 weeks. Compared with patients who recovered from COVID-19, demised patients showed a more pronounced decline in SaO2 prior to COVID-19 diagnosis. CONCLUSIONS: In HD patients, hypoxemia may precede the onset of clinical symptoms and the diagnosis of COVID-19. A steep decline of SaO2 is associated with poor patient outcomes. Measurements of SaO2 may aid the pre-symptomatic identification of patients with COVID-19.