Temporal Reduction in COVID-19-Associated Fatality Among Kidney Transplant Recipients: The Brazilian COVID-19 Registry Cohort Study.

Data from the general population suggest that fatality rates declined during the course of the pandemic. This analysis, using data extracted from the Brazilian Kidney Transplant COVID-19 Registry, seeks to determine fatality rates over time since the index case on March 3rd, 2020. Data from hospitalized patients with RT-PCR positive SARS-CoV-2 infection from March to August 2020 (35 sites, 878 patients) were compared using trend tests according to quartiles (Q1: <72 days; Q2: 72-104 days; Q3: 105-140 days; Q4: >140 days after the index case). The 28-day fatality decreased from 29.5% (Q1) to 18.8% (Q4) (pfor-trend = 0.004). In multivariable analysis, patients diagnosed in Q4 showed a 35% reduced risk of death. The trend of reducing fatality was associated with a lower number of comorbidities (20.7-10.6%, p for-trend = 0.002), younger age (55-53 years, pfor-trend = 0.062), and better baseline renal function (43.6-47.7 ml/min/1.73 m2, pfor-trend = 0.060), and were confirmed by multivariable analysis. The proportion of patients presenting dyspnea (pfor-trend = 0.001) and hypoxemia (pfor-trend < 0.001) at diagnosis, and requiring intensive care was also found reduced (pfor-trend = 0.038). Despite possible confounding variables and time-dependent sampling differences, we conclude that COVID-19-associated fatality decreased over time. Differences in demographics, clinical presentation, and treatment options might be involved.

Development and validation of a simple web-based tool for early prediction of COVID-19-associated death in kidney transplant recipients.

This analysis, using data from the Brazilian kidney transplant (KT) COVID-19 study, seeks to develop a prediction score to assist in COVID-19 risk stratification in KT recipients. In this study, 1379 patients (35 sites) were enrolled, and a machine learning approach was used to fit models in a derivation cohort. A reduced Elastic Net model was selected, and the accuracy to predict the 28-day fatality after the COVID-19 diagnosis, assessed by the area under the ROC curve (AUC-ROC), was confirmed in a validation cohort. The better calibration values were used to build the applicable ImAgeS score. The 28-day fatality rate was 17% (n = 235), which was associated with increasing age, hypertension and cardiovascular disease, higher body mass index, dyspnea, and use of mycophenolate acid or azathioprine. Higher kidney graft function, longer time of symptoms until COVID-19 diagnosis, presence of anosmia or coryza, and use of mTOR inhibitor were associated with reduced risk of death. The coefficients of the best model were used to build the predictive score, which achieved an AUC-ROC of 0.767 (95% CI 0.698-0.834) in the validation cohort. In conclusion, the easily applicable predictive model could assist health care practitioners in identifying non-hospitalized kidney transplant patients that may require more intensive monitoring. Trial registration: ClinicalTrials.gov NCT04494776.