Kidney disease and all-cause mortality in patients with COVID-19 hospitalized in Genoa, Northern Italy
- PDF / 935,917 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 28 Downloads / 169 Views
ORIGINAL ARTICLE
Kidney disease and all‑cause mortality in patients with COVID‑19 hospitalized in Genoa, Northern Italy Elisa Russo1 · Pasquale Esposito1 · Lucia Taramasso2 · Laura Magnasco2 · Michela Saio1 · Federica Briano2 · Chiara Russo2 · Silvia Dettori2 · Antonio Vena2 · Antonio Di Biagio2 · Giacomo Garibotto1 · Matteo Bassetti2 · Francesca Viazzi1 on behalf of GECOVID working group Received: 24 July 2020 / Accepted: 23 September 2020 © The Author(s) 2020
Abstract Background The prevalence of kidney involvement during SARS-CoV-2 infection has been reported to be high. Nevertheless, data are lacking about the determinants of acute kidney injury (AKI) and the combined effect of chronic kidney disease (CKD) and AKI in COVID-19 patients. Methods We collected data on patient demographics, comorbidities, chronic medications, vital signs, baseline laboratory test results and in-hospital treatment in patients with COVID-19 consecutively admitted to our Institution. Chronic kidney disease was defined as eGFR 1.5 times baseline. We did not consider the urine output criteria to define AKI because of missing data due to the retrospective nature of the study. AKI was calculated at three different time-points: (a) at hospital admission, comparing creatinine with the median value of serum creatinine calculated from all available values within 180 days before admission, (b) within the first week, and (c) after a week of hospitalization, comparing creatinine with values at admission.
Normally distributed variables are presented as mean ± SD and compared using an independent or paired t-test, as appropriate. Nonparametric continuous variables are presented as median with interquartile range (IQR). Logarithmically transformed values of skewed variables were used for the statistical analysis. Comparisons between groups were made by analysis of variance. Comparisons of proportions were made using the χ2-test or Fisher’s exact test, as appropriate. To identify risk factors associated with the development of AKI, we performed a logistic regression model, with adjustment for risk factors that differed between subjects who developed AKI and those who did
13
Journal of Nephrology
not. Kaplan–Meier and log-rank test methods were used to estimate and compare survival curves. Cox proportional regression models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) for the relationship between the occurrence of death and the presence of AKI with or without preexisting CKD and several potential confounding factors with biological plausibility. In model 1, age, sex, and Charlson morbidity index are added to AKI as covariates. In model 2, CKD, history of hypertension, treatment with RAAS-I and C-reactive protein (CRP) are also included. In model 3, AKI and CKD are replaced by the four possible combinations of AKI and CKD and treatment with hydroxychloroquine (HCQ) and corticosteroids are also included. Statistical analyses were performed using StatView for Windows (version 5.0.1; SAS Institute, Cary, NC,
Data Loading...
