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.

Machine Learning for Prediction of Patients on Hemodialysis with an Undetected SARS-CoV-2 Infection.

Background: We developed a machine learning (ML) model that predicts the risk of a patient on hemodialysis (HD) having an undetected SARS-CoV-2 infection that is identified after the following ≥3 days. Methods: As part of a healthcare operations effort, we used patient data from a national network of dialysis clinics (February-September 2020) to develop an ML model (XGBoost) that uses 81 variables to predict the likelihood of an adult patient on HD having an undetected SARS-CoV-2 infection that is identified in the subsequent ≥3 days. We used a 60%:20%:20% randomized split of COVID-19-positive samples for the training, validation, and testing datasets. Results: We used a select cohort of 40,490 patients on HD to build the ML model (11,166 patients who were COVID-19 positive and 29,324 patients who were unaffected controls). The prevalence of COVID-19 in the cohort (28% COVID-19 positive) was by design higher than the HD population. The prevalence of COVID-19 was set to 10% in the testing dataset to estimate the prevalence observed in the national HD population. The threshold for classifying observations as positive or negative was set at 0.80 to minimize false positives. Precision for the model was 0.52, the recall was 0.07, and the lift was 5.3 in the testing dataset. Area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) for the model was 0.68 and 0.24 in the testing dataset, respectively. Top predictors of a patient on HD having a SARS-CoV-2 infection were the change in interdialytic weight gain from the previous month, mean pre-HD body temperature in the prior week, and the change in post-HD heart rate from the previous month. Conclusions: The developed ML model appears suitable for predicting patients on HD at risk of having COVID-19 at least 3 days before there would be a clinical suspicion of the disease.

Relevance of VEGF and CD147 in different SARS-CoV-2 positive digestive tracts characterized by thrombotic damage.

Several evidence suggests that, in addition to the respiratory tract, also the gastrointestinal tract is a main site of severe acute respiratory syndrome CoronaVirus 2 (SARS-CoV-2) infection, as an example of a multi-organ vascular damage, likely associated with poor prognosis. To assess mechanisms SARS-CoV-2 responsible of tissue infection and vascular injury, correlating with thrombotic damage, specimens of the digestive tract positive for SARS-CoV-2 nucleocapsid protein were analyzed deriving from three patients, negative to naso-oro-pharyngeal swab for SARS-CoV-2. These COVID-19-negative patients came to clinical observation due to urgent abdominal surgery that removed different sections of the digestive tract after thrombotic events. Immunohistochemical for the expression of SARS-CoV-2 combined with a panel of SARS-CoV-2 related proteins angiotensin-converting enzyme 2 receptor, cluster of differentiation 147 (CD147), human leukocyte antigen-G (HLA-G), vascular endothelial growth factor (VEGF) and matrix metalloproteinase-9 was performed. Tissue samples were also evaluated by electron microscopy for ultrastructural virus localization and cell characterization. The damage of the tissue was assessed by ultrastructural analysis. It has been observed that CD147 expression levels correlate with SARS-CoV-2 infection extent, vascular damage and an increased expression of VEGF and thrombosis. The confirmation of CD147 co-localization with SARS-CoV-2 Spike protein binding on gastrointestinal tissues and the reduction of the infection level in intestinal epithelial cells after CD147 neutralization, suggest CD147 as a possible key factor for viral susceptibility of gastrointestinal tissue. The presence of SARS-CoV-2 infection of gastrointestinal tissue might be consequently implicated in abdominal thrombosis, where VEGF might mediate the vascular damage.

Enhanced Sentinel Surveillance System for COVID-19 Outbreak Prediction in a Large European Dialysis Clinics Network.

Accurate predictions of COVID-19 epidemic dynamics may enable timely organizational interventions in high-risk regions. We exploited the interconnection of the Fresenius Medical Care (FMC) European dialysis clinic network to develop a sentinel surveillance system for outbreak prediction. We developed an artificial intelligence-based model considering the information related to all clinics belonging to the European Nephrocare Network. The prediction tool provides risk scores of the occurrence of a COVID-19 outbreak in each dialysis center within a 2-week forecasting horizon. The model input variables include information related to the epidemic status and trends in clinical practice patterns of the target clinic, regional epidemic metrics, and the distance-weighted risk estimates of adjacent dialysis units. On the validation dates, there were 30 (5.09%), 39 (6.52%), and 218 (36.03%) clinics with two or more patients with COVID-19 infection during the 2-week prediction window. The performance of the model was suitable in all testing windows: AUC = 0.77, 0.80, and 0.81, respectively. The occurrence of new cases in a clinic propagates distance-weighted risk estimates to proximal dialysis units. Our machine learning sentinel surveillance system may allow for a prompt risk assessment and timely response to COVID-19 surges throughout networked European clinics.

Bowel ischemia as onset of COVID-19 in otherwise asymptomatic patients with persistently negative swab.

BACKGROUND: Asymptomatic patients with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can develop hypercoagulable conditions and acute vascular events. The objective of this study is to determine whether SARS-CoV-2 was present in resected specimens from patients with acute bowel ischemia, but asymptomatic for Coronavirus Disease 2019 (COVID-19) and with persistently real-time polymerase chain reaction negative pharyngeal swab. METHODS: Three consecutive patients presented severe abdominal symptoms due to extensive ischemia and necrosis of the bowel, with co-existent thrombosis of abdominal blood vessels. None had the usual manifestations of COVID-19, and repeated pharyngeal swabs tested negative. They underwent emergency surgery with intestinal resection. Immunohistochemical testing for SARS-CoV-2 on resected tissue was performed. RESULTS: All tested samples were strongly positive for SARS-CoV-2. CONCLUSIONS: This is the first case report in which patients with severe intestinal symptoms presented a marked SARS-CoV-2 positivity in the resected tissues, without any usual clinical manifestations of COVID-19. These results suggest that the patients might be infected with SARS-CoV-2 presenting acute abdominal distress but without respiratory or constitutional symptoms.

Trajectories of clinical and laboratory characteristics associated with COVID-19 in hemodialysis patients by survival.

INTRODUCTION: The clinical impact of COVID-19 has not been established in the dialysis population. We evaluated the trajectories of clinical and laboratory parameters in hemodialysis (HD) patients. METHODS: We used data from adult HD patients treated at an integrated kidney disease company who received a reverse transcription polymerase chain reaction (RT-PCR) test to investigate suspicion of a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection between May 1 and September 1, 2020. Nonparametric smoothing splines were used to fit data for individual trajectories and estimate the mean change over time in patients testing positive or negative for SARS-CoV-2 and those who survived or died within 30 days of first suspicion or positive test date. For each clinical parameter of interest, the difference in average daily changes between COVID-19 positive versus negative group and COVID-19 survivor versus nonsurvivor group was estimated by fitting a linear mixed effects model based on measurements in the 14 days before (i.e., Day -14 to Day 0) Day 0. RESULTS: There were 12,836 HD patients with a suspicion of COVID-19 who received RT-PCR testing (8895 SARS-CoV-2 positive). We observed significantly different trends (p < 0.05) in pre-HD systolic blood pressure (SBP), pre-HD pulse rate, body temperature, ferritin, neutrophils, lymphocytes, albumin, and interdialytic weight gain (IDWG) between COVID-19 positive and negative patients. For COVID-19 positive group, we observed significantly different clinical trends (p < 0.05) in pre-HD pulse rate, lymphocytes, neutrophils, and albumin between survivors and nonsurvivors. We also observed that, in the group of survivors, most clinical parameters returned to pre-COVID-19 levels within 60-90 days. CONCLUSION: We observed unique temporal trends in various clinical and laboratory parameters among HD patients who tested positive versus negative for SARS-CoV-2 infection and those who survived the infection versus those who died. These trends can help to define the physiological disturbances that characterize the onset and course of COVID-19 in HD patients.

Multi-organ point-of-care ultrasound for COVID-19 (PoCUS4COVID): international expert consensus.

COVID-19 has caused great devastation in the past year. Multi-organ point-of-care ultrasound (PoCUS) including lung ultrasound (LUS) and focused cardiac ultrasound (FoCUS) as a clinical adjunct has played a significant role in triaging, diagnosis and medical management of COVID-19 patients. The expert panel from 27 countries and 6 continents with considerable experience of direct application of PoCUS on COVID-19 patients presents evidence-based consensus using GRADE methodology for the quality of evidence and an expedited, modified-Delphi process for the strength of expert consensus. The use of ultrasound is suggested in many clinical situations related to respiratory, cardiovascular and thromboembolic aspects of COVID-19, comparing well with other imaging modalities. The limitations due to insufficient data are highlighted as opportunities for future research.