key: cord-0830679-x46jtu8y
authors: Paranjpe, I.; Jayaraman, P.; Su, C.-Y.; Zhou, S.; Chen, S.; Thompson, R.; Del Valle, D. M.; Kenigsberg, E.; Zhao, S.; Jaladanki, S.; Chaudhary, K.; Ascolillo, S.; Vaid, A.; Kumar, A.; Paranjpe, M.; O Hagan, R.; Kamat, S.; Gulamali, F. F.; Xie, H.; Harris, J.; Patel, M.; Argueta, K.; Batchelor, C.; Nie, K.; Dellepiane, S.; Scott, L.; Levin, M. A.; He, J. C.; Coca, S. G.; Chan, L.; Azeloglu, E. U.; Schadt, E.; Beckmann, N.; Gnjatic, S.; Merad, M.; Kim-Schulze, S.; Richards, B.; Glicksberg, B. S.; Charney, A. W.; Nadkarni, G. N.
title: Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection
date: 2021-12-11
journal: nan
DOI: 10.1101/2021.12.09.21267548
sha: 69defbd2f37b2ba7421af7dfc711e6dfa48104ed
doc_id: 830679
cord_uid: x46jtu8y

Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using longitudinally collected biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Using longitudinal measurements of ~4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 upregulated and 40 downregulated proteins associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Using longitudinal clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that has caused the coronavirus disease 2019 (COVID- 19) pandemic.

Although effective vaccines are available, novel variants that may evade neutralizing antibodies exist in the population and have led to high case counts and periodic case surges. COVID-19 most commonly presents with fever, cough, and dyspnea 1,2 and is associated with acute respiratory distress syndrome (ARDS). However, the clinical syndrome resulting from SARS-CoV-2 infection is broad, ranging from asymptomatic infection to severe disease with extrapulmonary manifestations 3 , including acute kidney injury 4 , acute myocardial injury 5, 6 and thrombotic complications [7] [8] [9] [10] [11] .

Acute kidney injury (AKI) is a particularly prominent complication. The rates of AKI vary greatly based on patient population, but evidence suggests that at least 30% of hospitalized patients and 50% of patients in the intensive care unit (ICU) develop AKI 1, 4, [12] [13] [14] [15] . Although the rate of AKI in hospitalized COVID-19 patients has decreased since the initial surge in 2020, the incidence remains high 16 . Like community-acquired pneumonia 17 , AKI is increasingly recognized as a common complication of COVID-19 in the hospitalized setting and confers significantly increased morbidity and mortality 18 .

However, unlike AKI secondary to sepsis or other viral organisms, there remains a limited understanding of the pathophysiology of COVID-19-associated AKI.

Histopathological reports from autopsy specimens have provided conflicting insights into the pathological changes in the kidney in COVID-19. A report of 26 patients who died with COVID-19 AKI revealed acute tubular injury as a prominent mechanism 19 .

Additionally, the presence of viral particles in the tubular epithelium and podocytes in autopsy specimens has been reported 19, 20 , which is evidence of direct viral invasion of the kidney. In addition, coagulopathy and endothelial dysfunction are hallmarks of COVID-19 21 and may also contribute to AKI. Finally, SARS-CoV-2 may directly activate the complement system 22 . In addition to these mechanisms, systemic effects of critical illness (hypovolemia, mechanical ventilation) and derangements in cardiac function and volume may also contribute to COVID-19 AKI.

In addition to morbidity and mortality in the acute setting, COVID-19 is also associated with long term manifestations i.e., the post-acute sequelae of SARS-CoV2 (PASC) 23 . Kidney function decline is a major component of PASC and a study of more than 1 million individuals found that survivors of COVID-19 had an elevated risk of postacute eGFR decline 24 , suggesting long term kidney dysfunction may occur following the acute infection.

Given the high incidence of COVID-19 associated kidney dysfunction, the unknown pathophysiology, and the urgent need for better approaches for risk stratification for long term kidney function decline we aimed to characterize the proteomic changes associated with COVID associated AKI and long-term kidney function. We measured protein expression of more than 4000 proteins from serum samples collected in a diverse large cohort of hospitalized patients with COVID-19 and validated significant results in an independent cohort and identified proteins that are significantly different between patients with and without AKI. We then determined whether these proteomic perturbations also characterize post-discharge kidney function decline as measured by estimated glomerular filtration rate (eGFR). All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

An overview of the discovery cohort selection process is provided in Fig 1. We prospectively enrolled patients hospitalized with COVID-19 between March 24, and August 26, 2020, at five hospitals of a large urban, academic hospital system in New York City, NY into a cohort as previously described 25 . The cohort enrolled patients who were admitted to the health care system with a COVID-19 infection and had broad inclusion criteria without specific exclusion criteria. The Mount Sinai Institutional Review Board approved this study under a regulatory approval allowing for access to patient level data and biospecimen collection. Peripheral blood specimens were collected at various points during the hospital admission for each patient.

The validation cohort included a prospective biobank from Quebec, Canada that enrolled patients hospitalized with COVID-19, as previously described 26 .   P  a  t  i  e  n  t  s  w  e  r  e   r  e  c  r  u  i  t  e  d  f  r  o  m  t  h  e  J  e  w  i  s  h  G  e  n  e  r  a  l  H  o  s  p  i  t  a  l  a  n  d  C  e  n  t  r  e  H  o  s  p  i  t  a  l  i  e  r  d  e  l  '  U  n  i  v  e  r  s  i  t  é  d  e   M  o  n  t  r  é  a  l . Peripheral blood specimens were collected at multiple time points after admission.

We defined an AKI cohort using proteomic data acquired at the last available timepoint during the hospital course for all individuals. Patients who developed AKI after the last specimen collection timepoint were excluded. Controls were defined as individuals who developed AKI stage 1 or did not develop AKI during their hospital course.

All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint Blood samples were collected in Serum Separation Tubes with a polymer gel for serum separation. Samples were centrifuged at 1200 g for 10 minutes at 20°C. After centrifugation, serum was pipetted to a 15 mL conical tube. Serum was then aliquoted into cryovials and stored at -80°C.

We defined AKI (stage 2 or 3) as per Kidney Disease Improving Global Outcomes (KDIGO) criteria: an increase in serum creatinine of at least 2.0 times the baseline creatinine 27 . For patients with previous serum creatinine measurement available in the 365 days prior to admission, the minimum value in this period was considered the baseline creatinine. For patients without a baseline creatinine in this period, a baseline value was calculated based on an estimated glomerular filtration rate (eGFR) of 75 ml/min per 1.73 m 2 as per the KDIGO AKI guidelines.

We collected demographic and laboratory data collected as part of standard medical care from an institutional electronic health record (EHR) database. We defined clinical comorbidities using diagnostic codes recorded in the EHR before the current hospital admission. To account for disease severity at the time of specimen collection, we defined supplemental oxygen requirement as 0 if the patient was not receiving supplemental oxygenation or on nasal cannula, 1 if the patient was receiving noninvasive mechanical ventilation (CPAP, BIPAP), or 2 if the person was receiving invasive mechanical ventilation. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

We used the SomaScan discovery platform to quantify levels of protein expression. The SomaScan platform is a highly multiplexed aptamer based proteomic assay based on modified single-stranded DNA aptamers capable of simultaneously detecting 4497 proteins in biological samples. The assay was run using the standard 12 hybridization normalization control sequences to assess for variability in the Agilent plate quantification process, five human calibrator control pooled replicates, and 3 quality control pooled replicates to control for batch effects. Standard preprocessing as per Somalogic's guidelines were applied. Briefly, the data was first normalized using the 12 hybridization controls to remove hybridization variation within a run. Then, median signal normalization is performed with calibrator samples across plates to remove variation in sample-to-sample differences attributable to variations due to pipetting, reagent concentrations, assay timings and other technical aspects. Data was then calibrated to remove assay differences between runs. Standard Somalogic acceptance criteria for quality control metrics were used (plate scale factor between 0.4 and 2.5 and 85% of QC ratios between 0.8 and 1.2). Samples with intrinsic issues such as reddish appearance or low sample volume were also removed as part of the Somalogic quality control protocol. After quality control and normalization procedures, the resulting relative fluorescence unit (RFU) values were log2 transformed.

Principal component analysis (PCA) was performed using log2 transformed RFU values of all proteins. Pairwise plots of the top three principal components were plotted. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

Using data from the AKI cohort, linear regression models were fit independently for each protein using the Limma package in R using the log 2 transformed protein values as the dependent variable. Models were adjusted for age, sex, history of chronic kidney disease (CKD), and supplemental oxygen requirement (0,1, or 2 [see above]) at the time of specimen collection. P values were adjusted using the Benjamin-Hochberg procedure to control the false discovery rate (FDR) at 5%.

Outpatient creatinine values measured after discharge were used to compute estimated glomerular filtration rate (eGFR) values the CKD-EPI equation. To determine whether AKI associated protein expression correlated with post-discharge kidney function, we fit a mixed effects linear regression model with random intercept and slope.

Using the discovery cohort, protein expression of AKI-associated proteins measured at the last available timepoint during admission was used. The dependent variable was eGFR and the model was adjusted for age, sex, baseline creatinine, history of CKD, maximum AKI stage during the hospital admission, and day of eGFR measurement after hospital discharge. Models included a random effect of patient ID to adjust for correlation between eGFR values taken from the same individuals. Significance was evaluated using a F-test with Sattherwaite degrees of freedom implemented in the lmerTest 28 R package. P values were adjusted using the Benjamin-Hochberg procedure to control the false discovery rate (FDR) at 5%. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint

We performed all statistical analysis using R version 4.0.3. Protein-protein interaction (PPI) network was constructed using the Network X package in Python to display a Minimum Spanning Tree (MST) using Prim's algorithm. Network clustering was conducted using the MCL cluster algorithm and functional enrichment was carried out using the STRING Database in Cytoscape 29 .

Data is available by contacting the senior author, Girish Nadkarni (girish.nadkarni@mountsinai.org).

Code is available at https://github.com/Nadkarni-Lab/aki_covid_proteomics

To discover proteins associated with COVID-AKI, we enrolled a prospective cohort of patients hospitalized with COVID-19 admitted between March 24, 2020 and August 26, 2020 into a biobank as previously described 25 . Cases were defined as patients who developed AKI (stage 2 or 3) during their hospital admission and controls included all other patients (Fig 1) . Characteristics of cases and controls in the discovery cohort are provided in Table 1 . Patients who developed AKI were significantly older (67 vs. 60 years, p <0.001), more commonly Hispanic/Latino (48% vs 37%, p =0.012), and had a greater prevalence of atrial fibrillation (17% vs 8%, p =0.008), diabetes (37% vs 20%, p <0.001), and chronic kidney disease (20% vs 4%, p< 0.001). We then validated these associations in an external cohort from Quebec, Canada. Characteristics of the All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

In the discovery cohort, serum levels of 4496 proteins were quantified using the SomaScan platform using samples collected at multiple timepoints during the hospital course (Supplementary Table 2 ) as previously described 25 . We first identified proteins associated with prevalent AKI using measurements taken after the onset of AKI in cases and the last available measurement in controls (Fig 1, 71 cases and 366 controls). The top three principal components (PCs) distinctly separate samples by case status (Fig 2A) . We fit a multivariate linear regression model adjusted for age, sex, history of chronic kidney disease (CKD), and maximum oxygen requirement at the time of blood draw. We identified 413 upregulated and 30 downregulated proteins (Supplementary Table 3 ).

We then performed an external validation of AKI-associated proteins in a prospective biobank cohort from Quebec, Canada. Of the 443 proteins significantly associated with AKI in the discovery cohort, 62 were also associated with AKI in the validation cohort (p <0.05, Table 2 ). All validated proteins were associated with an increased risk of AKI. The fold changes of validated proteins in the discovery and validation cohort were highly correlated with a Pearson correlation of 0.71 (Fig 2B) . The 62-protein signature distinctly separated AKI cases from cohorts in the discovery cohort All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint (Fig 2C) . Protein-protein interaction (PPI) network analysis revealed enrichment of several highly connected proteins, including LCN2 (alternative name: NGAL), REG3A, and MB (Fig 4A) . The AKI-associated protein network also included a cluster of cardiac structural proteins (Fig 4B) , TNNT2, TTN, MYL3, SRL, and NPPB (alternative name: BNP).

Given the previously reported association of COVID-19 AKI with long-term eGFR decline 30 , we hypothesized that significant proteomic markers associated with COVID-19 AKI are also associated with post-discharge eGFR. We included all outpatient eGFR measurements taken after discharge from patients in the Mount Sinai biobank cohort.

Of the 437 patients in the cohort, 181 patients had at least one outpatient postdischarge eGFR measurement. The median number of eGFR measurements was 4 with an interquartile of 9.

We used a mixed effects linear model accounting for baseline creatinine, AKI stage during the COVID admission and repeated eGFR measurements to associate the 62 protein AKI signature with long-term eGFR trend. Of the 62 AKI-associated proteins, 25 were significantly (adjusted P <0.05) associated with eGFR trend (Fig 3, Fig 5A) . All 25 eGFR-associated proteins were negatively correlated with eGFR ( Table 3) . However, the strength of association with AKI was not significantly associated with the strength of association with post-discharge eGFR. Proteins most strongly associated (by P value) with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C (Fig 5B) .

All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

Using longitudinal proteomic profiling in two large groups of patients hospitalized with COVID-19, we report several observations. First, we identified specific protein markers of AKI and post-discharge kidney dysfunction, both well-documented sequelae of COVID-19 4, 30 . Second, in the acute phase, tubular injury and hemodynamic perturbation seem to be likely mechanisms. Third, tubular injury is a predominant mechanism of long-term kidney function decline. Thus, proteomic characterization reveals potentially different mechanisms of AKI and long-term eGFR decline with implications for more specific prognostic models and targeted therapeutic development.

Our data suggest that in the acute setting, COVID AKI is characterized by two broad mechanisms: 1) tubular injury and 2) hemodynamic perturbation. First, we found significant upregulation of NGAL (LCN2), a canonical marker of tubular injury. NGAL is secreted by circulating neutrophils and kidney tubular epithelium in response to systemic inflammation or ischemia. Since renal tubular epithelial cells express the angiotensin-converting enzyme 2 (ACE2) receptor which enables SARS-CoV2 viral entry into cells, direct tubular infection may cause the release of NGAL into the serum and urine. This potential mechanism is supported by our results and remains a testable hypothesis. Although NGAL is a known marker for intrinsic AKI accompanied by tubular injury, it is relatively insensitive to pre-renal AKI caused by hemodynamic disturbance 31,32 . However, our results demonstrate upregulation of BNP, a protein All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint released in the setting of volume overload as well as several cardiac structural proteins (cardiac troponin T, titin, myosin light chain 1, and sarcalumenin). This proteomic signature may represent an impaired crosstalk between the cardiovascular system and kidney in which myocardial injury leads to decreased renal perfusion and eventual AKI.

Myocardial injury has been previously reported in patients hospitalized with COVID-19 6 and thus may contribute to the multifactorial nature of COVID-AKI.

Since COVID-AKI increases the risk of long-term eGFR decline 30 , we then sought to determine whether these two phenomena shared common proteomic markers.

Surprisingly, we found that although almost half of the AKI-associated proteins were also significantly associated with post-discharge eGFR decline, the strengths of associations were not correlated. While COVID-AKI is likely caused by a combination of intrinsic tubular injury and hemodynamic disturbance in the setting of critical illness, long term eGFR decline was associated with increased expression of trefoil factor 3 (TFF3), a known prognostic marker for incident CKD 33 . Trefoil factors are a class of small peptides expressed in colonic and urinary tract epithelia that play essential roles in regeneration and repair of epithelial tissue 34,35 . Immunohistochemistry reveals TFF3 expression is localized to the tubular epithelial cells in kidney specimens from patients with CKD 33 , suggesting that long term eGFR decline may be associated with renal tubular epithelial damage. The exact pathological role of TFF3 in the renal tubules is unclear but it has been hypothesized to play a role in repair of kidney damage 36 .

Additionally, TFF3 release from the renal interstitium has also been hypothesized to direct the epithelial-to-mesenchymal transition (EMT) in renal interstitial fibrosis, a main pathway that leads to ESKD 33 . Our results implicate tubular damage in both AKI and All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint long term eGFR decline suggesting that SARS-CoV2 may preferentially target this region of the nephron. While AKI in the acute setting may be a result of ischemia and decreased renal perfusion associated with critical illness, the specific elevation of TFF3 associated with eGFR decline implicates a more general pattern of tubular injury that underlies COVID mediated kidney dysfunction. Since the ACE2, is preferentially However, the timepoints were not systematic due to logistical challenges during the peak of the COVID-19 pandemic and thus are not standardized between patients. Since a subset of patients had AKI at the time of admission, these patients were excluded from our analysis since specimens were collected after admission. Thus, our AKI cases may be biased towards less severe presentations. Second, since kidney injury is usually not an isolated phenomenon in critically ill patients, the protein expression changes observed may have been partially due to damage to other organs, such as the lung, liver, and heart. However, we accounted for non-kidney damage by adjusting for the highest level of ventilatory support and thus our results are likely a reflection of kidney injury. However, our results do show the importance of crosstalk between the cardiac system and the kidneys. Finally, our cohort did not include autopsy or kidney biopsy All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint specimens. Histopathological analysis of kidney specimens is necessary to determine the mechanism of AKI and whether viral particles are present in the kidney.

In conclusion, we provide the first comprehensive characterization of the plasma proteome of AKI and long term eGFR decline in hospitalized COVID-19 patients. Our results suggest that COVID-AKI and post-discharge kidney dysfunction may be caused by tubular damage but that in the acute setting, several factors including hemodynamic disturbance and myocardial injury also play a role. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. External validation of AKI associated proteins in the discovery cohort shows high correlation with increased risk of AKI with significance of p<0.05. C. Expression heatmap shows a distinct separation of the cases and controls using the 62 significant proteins identified from the validation cohort in the discovery cohort. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint Tables   Table 1: Demographic and clinical comorbidities of patients hospitalized with COVID-19 in the discovery cohort separated by the development of AKI (stage 2 or 3) during their hospital course. and validation cohort (P <0.05) are provided. Significance was determined by fitting a All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint linear model adjusted for age, sex, history of CKD, and maximum oxygen requirement at the time of blood draw. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ;  Clin. Pract. 2012; preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint Cardiac structure protein network AKI associated protein network

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The copyright holder for this this version posted December 11, 2021. ; https://doi.org/10.1101/2021.12.09.21267548 doi: medRxiv preprint

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