Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection.

BACKGROUND: 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 biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. METHODS: Using 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 higher plasma abundances of protein targets and 30 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p < 0.05). Of these, 62 proteins were validated in an external cohort (p < 0.05, N = 261). RESULTS: 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. CONCLUSIONS: Using 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.

Acute kidney injury (AKI) is a sudden, sometimes fatal, episode of kidney failure or damage. It is a known complication of COVID-19, albeit through unclear mechanisms. COVID-19 is also associated with kidney dysfunction in the long term, or chronic kidney disease (CKD). There is a need to better understand which patients with COVID-19 are at risk of AKI or CKD. We measure levels of several thousand proteins in the blood of hospitalized COVID-19 patients. We discover and validate sets of proteins associated with severe AKI and CKD in these patients. The markers identified suggest that kidney injury in COVID-19 patients involves damage to kidney cells that reabsorb fluid from urine and reduced blood flow to the heart, causing damage to heart muscles. Our findings might help clinicians to predict kidney injury in patients with COVID-19, and to understand its mechanisms.

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19.

BACKGROUND AND OBJECTIVES: AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Using data from adult patients hospitalized with COVID-19 from five hospitals from the Mount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to the Mount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission. RESULTS: A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precision-recall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction. CONCLUSIONS: An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_07_09_CJN17311120.mp3.

Impact of Vaccination on Major Adverse Cardiovascular Events in Patients With COVID-19 Infection.

Taken from the largest U.S. cohort of patients with SARS-CoV2, our results demonstrate the association of even partial vaccination with lower risk of MACE after SARS-CoV-2 infection.

Prevalence and Outcomes Associated with Hyperuricemia in Hospitalized Patients with COVID-19.

INTRODUCTION: Coronavirus 2019 (COVID-19) can increase catabolism and result in hyperuricemia. Uric acid (UA) potentially causes kidney damage by alteration of renal autoregulation, inhibition of endothelial cell proliferation, cell apoptosis, activation of the pro-inflammatory cascade, and crystal deposition. Hyperuricemia in patients with COVID-19 may contribute to acute kidney injury (AKI) and poor outcomes. METHODS: We included 834 patients with COVID-19 who were >18 years old and hospitalized for >24 h in the Mount Sinai Health System and had at least 1 measurement of serum UA. We examined the association between the first serum UA level and development of acute kidney injury (AKI, defined by KDIGO criteria), major adverse kidney events (MAKE, defined by a composite of all-cause in-hospital mortality or dialysis or 100% increase in serum creatinine from baseline), as well as markers of inflammation and cardiac injury. RESULTS: Among the 834 patients, the median age was 66 years, 42% were women, and the median first serum UA was 5.9 mg/dL (interquartile range 4.5-8.8). Overall, 60% experienced AKI, 52% experienced MAKE, and 32% died during hospitalization. After adjusting for demographics, comorbidities, and laboratory values, a doubling in serum UA was associated with increased AKI (odds ratio [OR] 2.8, 95% confidence interval [CI] 1.9-4.1), MAKE (OR 2.5, 95% CI 1.7-3.5), and in-hospital mortality (OR 1.7, 95% CI 1.3-2.3). Higher serum UA levels were independently associated with a higher level of procalcitonin (ß, 0.6; SE 0.2) and troponin I (ß, 1.2; SE 0.2) but were not associated with serum ferritin, C-reactive protein, and interleukin-6. CONCLUSION: In patients admitted to the hospital for COVID-19, higher serum UA levels were independently associated with AKI, MAKE, and in-hospital mortality in a dose-dependent manner. In addition, hyperuricemia was associated with higher procalcitonin and troponin I levels.

Activation of STAT3 signaling pathway in the kidney of COVID-19 patients.

BACKGROUND: Acute kidney injury is common in patients with COVID-19, however mechanisms of kidney injury remain unclear. Since cytokine storm is likely a cause of AKI and glomerular disease, we investigated the two major transcription factors, STAT3 and NF-kB, which are known to be activated by cytokines. METHODS: This is an observational study of the postmortem kidneys of 50 patients who died with COVID-19 in the Mount Sinai Hospital during the first pandemic surge. All samples were reviewed under light microscopy, electron microscopy, and immunofluorescence by trained renal pathologists. In situ hybridization evaluation for SARS-CoV-2 and immunostaining of transcription factors STAT3 and NF-kB were performed. RESULTS: Consistent with previous findings, acute tubular injury was the major pathological finding, together with global or focal glomerulosclerosis. We were not able to detect SARS-CoV-2 in kidney cells. ACE2 expression was reduced in the tubular cells of patients who died with COVID-19 and did not co-localize with TMPRSS2. SARS-CoV-2 was identified occasionally in the mononuclear cells in the peritubular capillary and interstitium. STAT3 phosphorylation at Tyr705 was increased in 2 cases in the glomeruli and in 3 cases in the tubulointerstitial compartments. Interestingly, STAT3 phosphorylation at Ser727 increased in 9 cases but only in the tubulointerstitial compartment. A significant increase in NF-kB phosphorylation at Ser276 was also found in the tubulointerstitium of the two patients with increased p-STAT3 (Tyr705). CONCLUSIONS: Our findings suggest that, instead of tyrosine phosphorylation, serine phosphorylation of STAT3 is commonly activated in the kidney of patients with COVID-19.

Machine Learning Prediction of Death in Critically Ill Patients With Coronavirus Disease 2019.

OBJECTIVES: Critically ill patients with coronavirus disease 2019 have variable mortality. Risk scores could improve care and be used for prognostic enrichment in trials. We aimed to compare machine learning algorithms and develop a simple tool for predicting 28-day mortality in ICU patients with coronavirus disease 2019. DESIGN: This was an observational study of adult patients with coronavirus disease 2019. The primary outcome was 28-day inhospital mortality. Machine learning models and a simple tool were derived using variables from the first 48 hours of ICU admission and validated externally in independent sites and temporally with more recent admissions. Models were compared with a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 using the area under the receiver operating characteristic curve and calibration. SETTING: Sixty-eight U.S. ICUs. PATIENTS: Adults with coronavirus disease 2019 admitted to 68 ICUs in the United States between March 4, 2020, and June 29, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study included 5,075 patients, 1,846 (36.4%) of whom died by day 28. eXtreme Gradient Boosting had the highest area under the receiver operating characteristic curve in external validation (0.81) and was well-calibrated, while k-nearest neighbors were the lowest performing machine learning algorithm (area under the receiver operating characteristic curve 0.69). Findings were similar with temporal validation. The simple tool, which was created using the most important features from the eXtreme Gradient Boosting model, had a significantly higher area under the receiver operating characteristic curve in external validation (0.78) than the Sequential Organ Failure Assessment score (0.69), National Early Warning Score (0.60), and CURB-65 (0.65; p < 0.05 for all comparisons). Age, number of ICU beds, creatinine, lactate, arterial pH, and Pao2/Fio2 ratio were the most important predictors in the eXtreme Gradient Boosting model. CONCLUSIONS: eXtreme Gradient Boosting had the highest discrimination overall, and our simple tool had higher discrimination than a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 on external validation. These models could be used to improve triage decisions and clinical trial enrichment.

Prone Positioning and Survival in Mechanically Ventilated Patients With Coronavirus Disease 2019-Related Respiratory Failure.

OBJECTIVES: Therapies for patients with respiratory failure from coronavirus disease 2019 are urgently needed. Early implementation of prone positioning ventilation improves survival in patients with acute respiratory distress syndrome, but studies examining the effect of proning on survival in patients with coronavirus disease 2019 are lacking. Our objective was to estimate the effect of early proning initiation on survival in patients with coronavirus disease 2019-associated respiratory failure. DESIGN: Data were derived from the Study of the Treatment and Outcomes in Critically Ill Patients with coronavirus disease 2019, a multicenter cohort study of critically ill adults with coronavirus disease 2019 admitted to 68 U.S. hospitals. Using these data, we emulated a target trial of prone positioning ventilation by categorizing mechanically ventilated hypoxemic (ratio of Pao2 over the corresponding Fio2 ≤ 200 mm Hg) patients as having been initiated on proning or not within 2 days of ICU admission. We fit an inverse probability-weighted Cox model to estimate the mortality hazard ratio for early proning versus no early proning. Patients were followed until death, hospital discharge, or end of follow-up. SETTING: ICUs at 68 U.S. sites. PATIENTS: Critically ill adults with laboratory-confirmed coronavirus disease 2019 receiving invasive mechanical ventilation with ratio of Pao2 over the corresponding Fio2 less than or equal to 200 mm Hg. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 2,338 eligible patients, 702 (30.0%) were proned within the first 2 days of ICU admission. After inverse probability weighting, baseline and severity of illness characteristics were well-balanced between groups. A total of 1,017 (43.5%) of the 2,338 patients were discharged alive, 1,101 (47.1%) died, and 220 (9.4%) were still hospitalized at last follow-up. Patients proned within the first 2 days of ICU admission had a lower adjusted risk of death compared with nonproned patients (hazard ratio, 0.84; 95% CI, 0.73-0.97). CONCLUSIONS: In-hospital mortality was lower in mechanically ventilated hypoxemic patients with coronavirus disease 2019 treated with early proning compared with patients whose treatment did not include early proning.

Hyperglycemia Is Associated With Increased Mortality in Critically Ill Patients With COVID-19

Objective: To explore the relationship between diabetes mellitus (DM), hyperglycemia, and adverse outcomes in critically ill patients with coronavirus disease 2019 (COVID-19).

Molecular Analysis of the Kidney From a Patient With COVID-19-Associated Collapsing Glomerulopathy.

Recent case reports suggest that coronavirus disease 2019 (COVID-19) is associated with collapsing glomerulopathy in African Americans with apolipoprotein L1 gene (APOL1) risk alleles; however, it is unclear whether disease pathogenesis is similar to HIV-associated nephropathy. RNA sequencing analysis of a kidney biopsy specimen from a patient with COVID-19-associated collapsing glomerulopathy and APOL1 risk alleles (G1/G1) revealed similar levels of APOL1 and angiotensin-converting enzyme 2 (ACE2) messenger RNA transcripts as compared with 12 control kidney samples downloaded from the GTEx (Genotype-Tissue Expression) Portal. Whole-genome sequencing of the COVID-19-associated collapsing glomerulopathy kidney sample identified 4 indel gene variants, 3 of which are of unknown significance with respect to chronic kidney disease and/or focal segmental glomerulosclerosis. Molecular profiling of the kidney demonstrated activation of COVID-19-associated cell injury pathways such as inflammation and coagulation. Evidence for direct severe acute respiratory syndrome coronavirus 2 infection of kidney cells was lacking, which is consistent with the findings of several recent studies. Interestingly, immunostaining of kidney biopsy sections revealed increased expression of phospho-STAT3 (signal transducer and activator of transcription 3) in both COVID-19-associated collapsing glomerulopathy and HIV-associated nephropathy as compared with control kidney tissue. Importantly, interleukin 6-induced activation of STAT3 may be a targetable mechanism driving COVID-19-associated acute kidney injury.

Hyperglycemia is Associated With Increased Mortality in Critically Ill Patients With COVID-19.

OBJECTIVE: To explore the relationship between hyperglycemia in the presence and absence of diabetes mellitus (DM) and adverse outcomes in critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: The study included 133 patients with COVID-19 admitted to an intensive care unit (ICU) at an urban academic quaternary-care center between March 10 and April 8, 2020. Patients were categorized based on the presence or absence of DM and early-onset hyperglycemia (EHG), defined as a blood glucose >180 mg/dL during the first 2 days after ICU admission. The primary outcome was 14-day all-cause in-hospital mortality; also examined were 60-day all-cause in-hospital mortality and the levels of C-reactive protein, interleukin 6, procalcitonin, and lactate. RESULTS: Compared to non-DM patients without EHG, non-DM patients with EHG exhibited higher adjusted hazard ratios (HRs) for mortality at 14 days (HR 7.51, CI 1.70-33.24) and 60 days (HR 6.97, CI 1.86-26.13). Non-DM patients with EHG also featured higher levels of median C-reactive protein (306.3 mg/L, P = .036), procalcitonin (1.26 ng/mL, P = .028), and lactate (2.2 mmol/L, P = .023). CONCLUSION: Among critically ill COVID-19 patients, those without DM with EHG were at greatest risk of 14-day and 60-day in-hospital mortality. Our study was limited by its retrospective design and relatively small cohort. However, our results suggest the combination of elevated glucose and lactate may identify a specific cohort of individuals at high risk for mortality from COVID-19. Glucose testing and control are important in individuals with COVID-19, even those without preexisting diabetes.

Impact of the COVID-19 Pandemic on Nephrology Fellow Training and Well-Being in the United States: A National Survey.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic's effects on nephrology fellows' educational experiences, preparedness for practice, and emotional wellbeing are unknown. METHODS: We recruited current adult and pediatric fellows and 2020 graduates of nephrology training programs in the United States to participate in a survey measuring COVID-19's effects on their training experiences and wellbeing. RESULTS: Of 1005 nephrology fellows-in-training and recent graduates, 425 participated (response rate 42%). Telehealth was widely adopted (90% for some or all outpatient nephrology consults), as was remote learning (76% of conferences were exclusively online). Most respondents (64%) did not have in-person consults on COVID-19 inpatients; these patients were managed by telehealth visits (27%), by in-person visits with the attending faculty without fellows (29%), or by another approach (9%). A majority of fellows (84%) and graduates (82%) said their training programs successfully sustained their education during the pandemic, and most fellows (86%) and graduates (90%) perceived themselves as prepared for unsupervised practice. Although 42% indicated the pandemic had negatively affected their overall quality of life and 33% reported a poorer work-life balance, only 15% of 412 respondents who completed the Resident Well-Being Index met its distress threshold. Risk for distress was increased among respondents who perceived the pandemic had impaired their knowledge base (odds ratio [OR], 3.04; 95% confidence interval [CI], 2.00 to 4.77) or negatively affected their quality of life (OR, 3.47; 95% CI, 2.29 to 5.46) or work-life balance (OR, 3.16; 95% CI, 2.18 to 4.71). CONCLUSIONS: Despite major shifts in education modalities and patient care protocols precipitated by the COVID-19 pandemic, participants perceived their education and preparation for practice to be minimally affected.

AKI in Hospitalized Patients with COVID-19.

BACKGROUND: Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. METHODS: This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. RESULTS: Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. CONCLUSIONS: AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.