ABSTRACT
Background: Acute kidney injury (AKI) is a known complication of COVID-19 associated with increased in-hospital mortality. Methods: We longitudinally measured serum levels of 4,497 proteins (SomaScan) in 437 COVID-19 patients at multiple timepoints along their hospital course and identified associations with AKI. Using single cell transcriptomic data from healthy human kidney specimens, we identified cell-specific kidney intracellular markers and quantified their leakage in sera from AKI patients. We also investigated whether serum proteomics improves AKI prediction. Results: We identified 408 upregulated and 107 downregulated proteins in COVIDAKI (144 cases, 293 controls, FDR<0.05, Fig 1A). Downregulated proteins included coagulation cascade inhibitors (protein C, heparin cofactor 2) and platelet dysregulation markers (Fig 1B), including platelet factor 4 (PF-4). Given the role of PF-4 in heparin induced thrombocytopenia (HIT), we then retrospectively analyzed 4,035 COVID-19 hospitalizations and found a significant association of HIT suspicion with COVID-AKI (aOR = 12.6, p <0.001). Intracellular AKI associated proteins were enriched for markers of the Loop of Henle, descending vasa recta endothelium, and NK cells (Fig 1C), which all have low ACE2 (Fig 1D) and TMPRSS2 expression (SARS-CoV2 receptor and activator respectively), suggesting bystander damage within the kidney, not direct viral invasion likely drives COVID-AKI. Finally, a random survival forest model incorporating protein levels had lower prediction error for incident AKI than one using only clinical variables (Fig 1E). Conclusions: The COVID-AKI serum proteome is characterized by dysregulated platelets with clinical evidence of HIT, improves prediction of incident AKI in a machine learning model and suggests inflammation mediated renal cell death, rather than direct viral invasion via the renal ACE2 receptor.
ABSTRACT
Background: Acute kidney injury (AKI) is common in COVID-19 and associated with increased adverse outcomes. COVID-associated AKI (COVID-AKI) pathophysiology is heterogenous, and deep learning may discover subphenotypes. Methods: We used data from 5 New York City hospitals from adults admitted between March '20-March '21 with COVID and AKI, excluding patients with kidney failure. An autoencoder compressed 58 features containing comorbidities, the first laboratory values and vital signs within 48 hours of admission for unsupervised K-means clustering. Outcomes were mortality, dialysis, mechanical ventilation, and ICU admission. Results: We identified 1634 patients with COVID-AKI and discovered 3 subphenotypes. Subphenotype one had 576 patients (35%);two had 635 patients (39%), and three had 423 patients (26%) (Table 1). Subphenotype three had the lowest median blood pressures, highest median BMI, and highest rates of all outcomes. (Figure 1) Conclusions: There are distinct subphenotypes in COVID-AKI indicating the heterogeneity of this condition.
ABSTRACT
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the associated Coronavirus Disease 2019 (COVID-19) is a public health emergency. Acute kidney injury (AKI) is a common complication in hospitalized patients with COVID-19 although mechanisms underlying AKI are yet unclear. There may be a direct effect of SARS-CoV-2 virus on the kidney;however, there is currently no data linking SARS-CoV-2 viral load (VL) to AKI. We explored the association of SARS-CoV-2 VL at admission to AKI in a large diverse cohort of hospitalized patients with COVID-19. Methods and findings: We included patients hospitalized between March 13th and May 19th, 2020 with SARS-CoV-2 in a large academic healthcare system in New York City (N = 1,049) with available VL at admission quantified by real-time RT-PCR. We extracted clinical and outcome data from our institutional electronic health records (EHRs). AKI was defined by KDIGO guidelines. We fit a Fine-Gray competing risks model (with death as a competing risk) using demographics, comorbidities, admission severity scores, and log10 transformed VL as covariates and generated adjusted hazard ratios (aHR) and 95% Confidence Intervals (CIs). VL was associated with an increased risk of AKI (aHR = 1.04, 95% CI: 1.01-1.08, p = 0.02) with a 4% increased hazard for each log10 VL change. Patients with a viral load in the top 50th percentile had an increased adjusted hazard of 1.27 (95% CI: 1.02-1.58, p = 0.03) for AKI as compared to those in the bottom 50th percentile. Conclusions: VL is weakly but significantly associated with in-hospital AKI after adjusting for confounders. This may indicate the role of VL in COVID-19 associated AKI. This data may inform future studies to discover the mechanistic basis of COVID-19 associated AKI.
ABSTRACT
Background: Preliminary reports find that patients with end stage renal disease (ESRD) on dialysis who test positive for SARS-CoV-2 have fewer symptoms and require less intensive care than expected. However, there are no reports regarding the outcomes of ESRD patients who are hospitalized with coronavirus disease 2019 (COVID-19). Methods: This is a retrospective observational study of patients aged ≥18 years with laboratory confirmed COVID-19 admitted to the Mount Sinai Health System between February 27 and May 20, 2020. ESRD patients were identified by International Classification of Disease codes for ESRD. ESRD patients were propensity matched (5:1) to non-ESRD patients by age, gender, race/ethnicity, comorbidities, body mass index, and facility and week of hospital admission. Multivariate analysis was performed to test the association of ESRD with mortality after adjustment for age, diabetes, hypertension, stroke, coronary artery disease, and congestive heart failure. Results: 122 ESRD patients were admitted during the study period and matched to 610 non-ESRD patients from the same study period. Patients with ESRD were well matched on age, sex, race/ethnicity and most comorbidities except ESRD patients had a higher prevalence of diabetes (55% vs 43%, P=0.02) and hypertension (66% vs. 55%, P=0.03). ESRD patients had higher inflammatory markers of ferritin and procalcitonin. There was no significant differences in d-dimer, fibrinogen, C reactive protein, or interleukin-6 (Figure 1A). ESRD patients were significantly less likely to receive mechanical ventilation (3% vs. 10%, P=0.01) or be admitted to the intensive care unit (9% vs. 21%), and had similar in-hospital mortality (9% vs 13%, P=0.5). ESRD status was associated with lower odds of intubation and intensive care admission, but not significantly associated with mortality after adjustments for age and comorbidities (Figure 1B). Conclusions: While ESRD patients had higher prevalence of comorbidities and higher inflammatory markers, they had similar in-hospital mortality as matched non- ESRD patients.