key: cord-0705844-ggnd8y06
authors: Flythe, Jennifer E.; Assimon, Magdalene M.; Tugman, Matthew J.; Chang, Emily H.; Gupta, Shruti; Shah, Jatan; Sosa, Marie Anne; DeMauro Renaghan, Amanda; Melamed, Michal L.; Wilson, F. Perry; Neyra, Javier A.; Rashidi, Arash; Boyle, Suzanne M.; Anand, Shuchi; Christov, Marta; Thomas, Leslie F.; Edmonston, Daniel; Leaf, David E.
title: Characteristics and Outcomes of Individuals With Pre-existing Kidney Disease and COVID-19 Admitted to Intensive Care Units in the United States
date: 2020-09-19
journal: Am J Kidney Dis
DOI: 10.1053/j.ajkd.2020.09.003
sha: 0c9d956100157de196bc069baaaba6d9b3556c79
doc_id: 705844
cord_uid: ggnd8y06

RATIONALE & OBJECTIVE: Underlying kidney disease is an emerging risk factor for more severe COVID-19 illness. We examined the clinical courses of critically ill COVID-19 patients with and without pre-existing kidney disease and investigated the association between degree of underlying kidney disease and in-hospital outcomes. STUDY DESIGN: Retrospective cohort study SETTINGS & PARTICIPANTS: 4,264 critically ill COVID-19 patients (143 dialysis patients, 521 chronic kidney disease [CKD] patients, and 3,600 patients without CKD) admitted to ICUs at 68 hospitals in the United States. PREDICTOR(S): Presence (versus absence) of pre-existing kidney disease OUTCOME(S): In-hospital mortality (primary); respiratory failure, shock, ventricular arrhythmia/ cardiac arrest, thromboembolic event, major bleed, and acute liver injury (secondary) ANALYTICAL APPROACH: We used standardized differences to compare patient characteristics (values >0.10 indicate a meaningful difference between groups) and multivariable adjusted Fine and Gray survival models to examine outcome associations. RESULTS: Dialysis patients had a shorter time from symptom onset to ICU admission compared to other groups (median [quartile 1-quartile 3] days: 4 [2-9] for dialysis patients; 7 [3-10] for CKD patients; 7 [4-10] for patients without pre-existing kidney disease). More dialysis patients (25%) reported altered mental status than those with CKD (20%, standardized difference = 0.12) and no kidney disease (12%, standardized difference = 0.36). Half of dialysis and CKD patients died within 28-days of ICU admission versus 35% of patients without pre-existing kidney disease. Compared to patients without pre-existing kidney disease, dialysis patients had a higher risk of 28-day in-hospital death (adjusted HR 1.41; 95% CI 1.09, 1.81), while patients with CKD had an intermediate risk (adjusted HR 1.25; 95% CI 1.08, 1.44). LIMITATIONS: Potential residual confounding CONCLUSIONS: Findings highlight the high mortality of individuals with underlying kidney disease and severe COVID-19, underscoring the importance of identifying safe and effective COVID-19 therapies for this vulnerable population.

Individuals with underlying kidney disease may be particularly vulnerable to severe COVID-19 illness, marked by multi-system organ failure, thrombosis, and a heightened inflammatory response. Among 4,264 critically ill adults with COVID-19 admitted to 68 intensive care units across the U.S., we found that both chronic kidney disease and dialysis patients had a ~50% 28-day in-hospital mortality rate. Patients with underlying kidney disease had higher in-hospital mortality than patients without kidney disease, with patients on maintenance dialysis having the highest risk. As evidenced by differences in symptoms and clinical trajectories, patients with pre-existing kidney disease may have unique susceptibility to COVID-19-related complications which warrants additional study and special consideration in the pursuit and development of targeted therapies. (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has snowballed into a global pandemic, infecting over 28 million people across the globe and killing more than 900,000 as of mid-September 2020. 1 Emerging data suggest that individuals with underlying kidney dysfunction have worse COVID-19-related outcomes than those without kidney dysfunction. [2] [3] [4] [5] [6] [7] [8] Similar outcome differences across patients with and without kidney dysfunction have been observed in other illness states (e.g., general critical illness, 9 influenza 10 ), and may relate, in part, to the innate immunity impairment, vascular dysfunction, and heightened inflammatory state that are characteristic of advanced kidney disease (CKD). [11] [12] [13] As such, individuals with underlying kidney dysfunction may be particularly vulnerable to COVID-19-related critical illness, marked by multi-system organ failure, thrombosis, and a heightened inflammatory response. COVID-19-related critical illness affects ~10% of patients hospitalized with COVID-19 and has an exceedingly high mortality rate. [14] [15] [16] [17] Data from the United States (U.S.) indicate that patients with critical COVID-19 illness complicated by acute kidney injury (AKI) have worse outcomes than those without AKI. 18-21 Single-center and regional studies suggest similarly poor outcomes among individuals with critical COVID-19 illness and pre-existing kidney dysfunction, especially dialysis-dependent kidney failure, but sample sizes were limited, and most lacked comparator populations. 20-25 Given the rapidly changing landscape of COVID-19 therapeutics and potential for impaired kidney function to limit therapeutic options (e.g., remdesivir), granular, broadly representative data characterizing clinical courses of critically ill patients with COVID-19 and pre-existing kidney disease are needed to inform management of this vulnerable population.

To address this knowledge gap, we used data from Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID), a cohort study of >4,000 patients with COVID-19 admitted to ICUs at 68 hospitals across the U.S., and examined the clinical courses of critically ill COVID-19 patients with and without pre-existing kidney disease. We also investigated the association between degree of underlying kidney disease and occurrence of inhospital mortality and other outcomes (e.g., respiratory failure, shock, thromboembolic events).

We used data from STOP-COVID, a multicenter cohort study that enrolled consecutive adults (≥18 years old) with laboratory-confirmed COVID-19 admitted to ICUs at 68 geographically diverse U.S. hospitals (Supplemental Material). Cohort compilation and initial results have been previously reported. 26 The STOP-COVID parent study was approved by the institutional review boards (IRBs) at each participating site. This ancillary study was approved by the University of North Carolina at Chapel Hill IRB (#20-1395). A waiver of informed consent was granted due to the anonymity of the STOP-COVID limited dataset used for this project.

In this study focused on pre-existing kidney disease, we included 4,264 critically ill COVID-19 patients with and without pre-existing kidney disease admitted to 68 ICUs between March 4, 2020 and May 10, 2020. Using a retrospective cohort study design, we followed patients forward in historical time from ICU admission to in-hospital death, hospital discharge, or June 6, 2020 -the date of database locking for these analyses. All patients still hospitalized at the time of analysis had at least 28-days of follow-up. We excluded patients without documented vital signs on ICU day 1 (n = 5).

J o u r n a l P r e -p r o o f

Study personnel at each STOP-COVID site collected data by detailed medical chart review and used a standardized electronic case report form to enter data into a secure Research Electronic Data Capture (REDCap) database. Abstracted data included: demographics, comorbidities, and home medications; symptoms and vital signs at ICU admission; longitudinal laboratory and physiologic parameters, therapeutic interventions, and acute organ injury and support during the first 14 days after ICU admission; and dates and contributing causes of inhospital death. For individuals with pre-existing dialysis-dependent kidney failure, we also collected data on dialysis modality, length of time receiving maintenance dialysis, and vascular access type (for hemodialysis patients), all preceding hospital admission.

The exposures of interest were the presence of pre-existing CKD and dialysis-dependent kidney failure. We defined pre-existing CKD as a baseline estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 (based on either the Modification of Diet in Renal Disease

[MDRD] Study 27 or CKD Epidemiology Collaboration [CKD-EPI] equations 28 ) prior to hospitalization on at least 2 consecutive occasions at least 12 weeks apart or, in cases where prehospitalization eGFRs were unavailable, the presence of CKD in the medical chart problem list or past medical history. Individuals with prior kidney transplant were classified according to their baseline eGFR. We defined pre-existing dialysis-dependent kidney failure as medical chartdocumented maintenance dialysis therapy prior to hospital admission. We categorized patients without evidence of CKD or dialysis-dependent kidney failure as having no pre-existing kidney disease.

The primary outcomes were 14-and 28-day in-hospital mortality. The secondary outcomes included 14-day in-hospital respiratory failure, shock, ventricular arrhythmia or cardiac arrest, thromboembolic event (including ischemic stroke, pulmonary embolism, or deep vein thrombosis), major bleed, and acute liver injury (Supplemental Table S1 ).

All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc, Cary, NC). We described patient characteristics on ICU day 1, therapies administered, and laboratory parameters across exposure groups as count (%) for categorical variables and as median [quartile 1, quartile 3] for continuous variables. We compared baseline covariate distributions using absolute standardized mean differences (ASMDs). An ASMD >0.10 represents an imbalance (i.e. difference) between exposure groups. 29, 30 A larger ASMD is indicative of a larger between group difference.

We assessed the association between the presence of kidney disease (CKD and dialysisdependent ESKD, separately) vs. no pre-existing kidney disease and 14-and 28-day in-hospital mortality using Fine and Gray proportional subdistribution hazards models. Individuals were followed forward in historical time from ICU admission to the first occurrence of an outcome, censoring event (completion of 14 and 28 days of follow-up), or competing event (hospital discharge). Pre-specified subgroup analyses evaluated the association between vascular access type prior to hospital admission and dialysis vintage (separately) and mortality in hemodialysis patients, and the degree of baseline creatinine (pre-hospital serum creatinine <1.2, 1.2-1.9, and ≥2.0 mg/dL) and mortality in CKD patients.

We used similar methods to examine the association between the presence (vs. absence) of pre-existing kidney disease and the occurrence of select secondary outcomes during the 14 J o u r n a l P r e -p r o o f days after ICU admission. We restricted these secondary analyses to individuals who were alive and free of the outcome of interest on ICU day 1. Follow-up began on ICU day 2, with both inhospital death and hospital discharge treated as competing events. We adjusted associative models for demographics (model 1), and separately for demographics and comorbid conditions (model 2) when the number of outcome events was sufficient. Model 1 assesses the association of outcomes and underlying kidney disease overall, while model 2 assesses the association of outcomes and underlying kidney disease independent of comorbid conditions known to associate with COVID-19 outcomes. 17, 21, 31-35 Using analogous methods, we performed separate sensitivity analyses excluding patients on therapeutic-level anticoagulation on ICU day 1 from models examining major bleed and thromboembolic events, and excluding patients with histories of liver disease from models examining acute liver injury.

A total of 4,264 individuals with COVID-19 critical illness were included in the study: 143 (3%) with pre-existing dialysis-dependent kidney failure, 521 (12%) with pre-existing nondialysis-dependent CKD, and 3,600 (85%) without pre-existing kidney disease. Table 1 and Supplemental Tables S2-S4 display the demographic and clinical characteristics on ICU day 1 across study groups. The majority of patients in the study (58%) were cared for in ICUs located in the northeastern U.S. CKD patients were older than dialysis patients (median [quartile 1- Of the 143 individuals with pre-existing dialysis-dependent kidney failure, 128 (90%) received in-center hemodialysis, 9 (6%) received peritoneal dialysis, 2 (1%) received home hemodialysis, and 4 (3%) had an undocumented modality prior to hospital admission. Of the 128 hemodialysis patients with known vascular access type, 82 (64%), 35 (27%), and 11 (9%) dialyzed via a fistula, catheter, and graft, respectively, prior to admission.

The median time from COVID-19-related symptom onset to ICU admission was 4 [2] [3] [4] [5] [6] [7] [8] [9] days among dialysis patients, 7 [3-10] days among CKD patients, and 7 [4-10] days among patients without pre-existing kidney disease. In general, dialysis patients reported COVID-19related symptoms prior to ICU admission at a lower frequency than patients without kidney disease, with one exception: the percentage of dialysis patients reporting altered mental status was more than twice that of patients without kidney disease (25% vs. 12%, ASMD = 0.36) and slightly more than patients with CKD (25% vs. 20%, ASMD = 0.12). In addition, respiratory symptoms were less frequent in dialysis patients compared to the other groups. Table 2 and Supplemental Tables S2-S4 display COVID-19 severity and laboratory findings on ICU day 1 across study groups. A modestly higher percentage of patients without kidney disease (63%) required invasive mechanical ventilation on ICU day 1 compared to dialysis patients (56%, ASMD = 0.15). Median white cell counts, platelet counts, and fibrinogen concentrations on ICU day 1 were lower in dialysis patients compared to patients without kidney disease, whereas median C-reactive protein, interleukin-6, ferritin, and troponin levels were higher in dialysis patients (all ASMDs >0.10). Similar laboratory patterns were observed for platelet count, fibrinogen, and troponin levels when comparing CKD patients to patients without kidney disease, but the differences were of lower magnitudes. Targeted Therapies and Clinical Trajectories   Table 3 displays COVID-19-targeted therapies administered during the 14 days after ICU admission in each group (Supplemental Table S5 : corresponding ASMDs). Compared to dialysis patients, a higher percentage of patients without pre-existing kidney disease were mechanically ventilated (74% vs. 80%, ASMD = 0.15). Proned positioning was used in a higher percentage of patients without kidney disease (42%) compared to CKD (27%, ASMD = 0.30) and dialysis (24%, ASMD = 0.37) patients. Remdesivir was more commonly administered to patients without kidney disease (7%) compared to CKD patients (2%, ASMD = 0.22). No dialysis patients received remdesivir. Patients without kidney disease received tocilizumab (19%) more often than those with CKD (14%, ASMD = 0.12) and dialysis-dependent kidney failure (9%, ASMD = 0.28). Figure S1 display laboratory parameter trajectories during the first 14 days after ICU admission across groups. In general, dialysis and CKD patients had lower platelet counts and higher levels of C-reactive protein compared to patients without kidney disease. Lactate levels on ICU day 1 were similar across groups, but elevated levels persisted longer in dialysis patients compared to the other groups. Longitudinally, ferritin and troponin levels were highest in dialysis patients and lowest in patients without kidney disease. Figure S2 ). Compared to no pre-existing kidney disease, pre-existing CKD and dialysisdependent kidney failure associated with higher risks of 14-and 28-day in-hospital mortality ( Table 4 ). In models examining the association between in-hospital mortality and pre-existing J o u r n a l P r e -p r o o f kidney disease status, independent of other comorbid conditions (i.e. models adjusted for demographic and comorbid conditions), the associations were slightly attenuated but remained statistically significant (fully adjusted HR (95% CI) for 28-day in-hospital mortality): 1.25 (1.08, 1.44) for CKD and 1.41 (1.09, 1.81) for dialysis-dependent kidney failure. Models evaluating 14day in-hospital mortality produced similar results. Of the patients who died during the 28-days following ICU admission, the median [quartile 1-quartile 3] time from ICU admission to death was 8 [5] [6] [7] [8] [9] [10] [11] , 8 [5] [6] [7] [8] [9] [10] [11] [12] [13] , and 10 [6-16] days for the dialysis, CKD, and no kidney disease groups, respectively. Mortality rates across exposure groups were stable during the study period (Supplemental Table S6 ). Table S7 display secondary outcomes across patient groups.

Dialysis patients trended toward having higher risks of shock, ventricular arrhythmia or cardiac arrest, major bleeding events, and acute liver injury during the 14 days after ICU admission. The occurrence of thromboembolic events was similar across patient groups. Sensitivity analyses excluding patients receiving therapeutic anticoagulation from major bleed and thromboembolic event models and patients with histories of liver disease from acute liver injury models produced similar results (Supplemental Tables S8-S9) .

Supplemental Tables S10-S12 display results from all pre-existing kidney disease subgroup analyses. Of the 397 individuals with pre-existing non-dialysis-dependent CKD and known baseline creatinine levels, a higher baseline creatinine trended toward associations with higher in-hospital mortality, but results did not reach statistical significance. Among the 128 incenter hemodialysis patients, dialysis via a catheter (vs. arteriovenous access) was associated with higher 28-day in-hospital mortality, demographic-adjusted HR (95% CI): 1.94 (1.09, 3.44).

In this study of over 4,200 critically ill adult patients admitted to 68 U.S. ICUs with COVID-19, we found that having pre-existing kidney disease was associated with higher inhospital mortality rates, with the strength of this association varying by degree of baseline kidney dysfunction. Compared to no pre-existing kidney disease, the presence of pre-existing kidney failure (dialysis-dependent) was associated with the highest hazard of in-hospital death, while pre-existing CKD (non-dialysis-dependent) had an intermediate association. Our findings highlight the importance of identifying effective COVID-19 therapies that can be safely administered to patients with underlying kidney dysfunction. Moreover, they underscore the urgency of proactive, pre-hospital advanced care planning conversations with this vulnerable population.

Our findings, from a large, geographically diverse sample of critically ill COVID-19 patients, expand on the existing evidence base demonstrating higher in-hospital mortality among patients with underlying kidney disease and newly report detailed clinical trajectories and outcomes among CKD patients. The observed association between pre-existing kidney disease and in-hospital mortality persisted in models adjusted for medical conditions known to associate with poorer COVID-19 outcomes, suggesting that underlying kidney disease confers risk for individuals with severe COVID-19 beyond that related to the comorbid disease burden characteristic of the disease state. Such findings may relate, in part, to uremia-induced innate immune system changes that hinder neutrophil, monocyte, and B-and T-cell function, thereby impairing bactericidal capacity and antimicrobial ability. 11- 13 We also found that dialysis patients receiving ICU-level care for COVID-19 had an in-J o u r n a l P r e -p r o o f hospital death rate of 50%, which is lower than rates reported in regional studies. 36-38 Strikingly, the unadjusted death rate among CKD patients (51%) was equivalent to that of dialysis patients (50%) yet notably higher than that of patients without underlying kidney disease (35%). These findings not only highlight the importance of discussing COVID-19 risks with both dialysis and CKD patients, but also engaging in advanced care planning conversations in the ambulatory setting, prior to patients falling ill with COVID-19. These discussions are particularly germane for individuals with kidney disease since remdesivir, one of the few evidence-based COVID-19 therapeutic options currently available, is generally not recommended for adults with an eGFR <30 mL/min/1.73m 2 . 39 However, the purported risks of remdesivir in the setting of kidney dysfunction that stem from concerns related to accumulation of its carrier, sulfobutylether-βcyclodextrin, may be overstated. 39 

Our study has several strengths. First, we used data from a cohort of over 4 200 critically ill individuals with COVID-19 who were admitted to 67 geographically diverse U.S. ICUs, increasing the generalizability of our findings and substantially expanding the evidence base about critically ill COVID-19 patients with pre-existing kidney disease. Second, we performed detailed chart reviews using standardized data extraction tools to collect daily, granular information on patients' clinical courses. This obviated the need for reliance on administrative billing codes that may lead to misclassification and supported the study of detailed comparisons across study groups. Third, data were collected from critically ill patients consecutively admitted to each ICU, minimizing potential selection bias. Fourth, whereas some prior studies of dialysis patients hospitalized with COVID-19 had limited follow-up time, we followed patients until the occurrence of hospital discharge, death, or 28-days.

We also acknowledge several study limitations. First, as with all observational studies, residual confounding may exist. However, to examine the association between underlying kidney disease and outcomes independent of coexistent medical conditions, we accounted for key demographic factors and comorbid conditions known to have strong associations with outcomes in individuals with COVID-19 in our multivariable models. Second, we defined pre-existing kidney disease based on the presence of prior eGFR measurements or documentation of CKD in the admitting hospital's medical record. It is possible that some exposure misclassification may have occurred. Third, data on organ injury and organ support were captured during the first 14 days following ICU admission only. Events after the 14-day time period may have been missed.

However, it is reassuring that most of the observed events occurred early in ICU courses, suggesting that the majority of events were likely captured. Fourth, data on inflammatory markers were not available for many patients (Supplemental Table S12 ) and may not have been J o u r n a l P r e -p r o o f missing at random (i.e., laboratory values were likely drawn more often in patients with more severe COVID-19). As such, it is possible that the observed trends in such markers may not generalize to individuals with less severe COVID-19. Related, it is possible that individuals with pre-existing kidney disease may have been preferentially declined ICU admission or died prior to ICU admission, raising the possibility of potential selection bias in our cohort. However, such selection bias would likely bias our findings toward the null. Fifth, we did not have information on 14-and 28-day vital status for patients discharged from the hospital prior to these time points.

Finally, limited numbers of some secondary outcomes (e.g., major bleeding events, acute liver injury) in the pre-existing kidney disease groups may have limited our ability to detect significant associations. Therefore, these findings should be considered hypothesis generating and fodder for future study.

In conclusion, in this multicenter, nationally representative cohort of U.S. adults with COVID-19 critical illness, we found that both CKD and dialysis patients had a ~50% 28-day inhospital mortality rate and that patients with underlying kidney disease had higher in-hospital mortality than patients without kidney disease, with maintenance dialysis patients having the highest risk in adjusted analyses. As evidenced by differences in symptoms and clinical trajectories, patients with pre-existing kidney disease may have unique vulnerability to COVID-19-related complications that warrant additional study and special consideration in the pursuit and development of targeted therapies. Table S7 . Association between pre-existing kidney disease and 14-day in-hospital outcomes among critically ill COVID-19 patients J o u r n a l P r e -p r o o f Supplemental Table S8 . Sensitivity analyses evaluating the association between pre-existing kidney disease and 14-day in-hospital major bleeding and thromboembolic events excluding patients on therapeutic anticoagulation on ICU day 1 Supplemental Table S9 . Sensitivity analyses evaluating the association between pre-existing kidney disease and 14-day in-hospital acute liver injury excluding patients with histories of liver disease Supplemental Table S10 . Association between baseline serum creatinine and 14-and 28-day inhospital mortality among critically ill CKD patients with COVID-19

Supplemental Table S11 . Association between vascular access type and 14-and 28-day inhospital mortality among critically ill hemodialysis patients with COVID-19

Supplemental Table S12 . Association between dialysis vintage and 14-and 28-day in-hospital mortality among critically ill hemodialysis patients with COVID-19

Supplemental Table S13. ICU day 1 variables with missing data Fine and Gray proportional subdistribution hazards models were used to estimate the association between the presence of pre-existing kidney disease (dialysis-dependent kidney failure and CKD, separately) vs. no pre-existing kidney disease and 14-and 28-day in-hospital mortality. Hospital discharge was treated as a competing event. a Model 1 was adjusted for age, sex, race, and Hispanic ethnicity. 

Values presented in the figure are medians. Dialysis represents patients with pre-existing dialysis-dependent kidney failure. CKD represents patients with pre-existing non-dialysis-dependent CKD. No kidney disease represents patients without pre-existing kidney disease. Supplemental Figure S1 displays analogous figures for the laboratory values of creatinine, interleukin-6, fibrinogen, D-dimer, direct bilirubin, and troponin I.

Abbreviations: CKD, chronic kidney disease; CRP, C-reactive protein; ICU, intensive care unit; IL, interleukin.

Dialysis represents patients with pre-existing dialysis-dependent kidney failure. CKD represents patients with pre-existing non-dialysisdependent CKD. No kidney disease represents patients without pre-existing kidney disease.

Abbreviations: CKD, chronic kidney disease; ICU, intensive care unit.

Dialysis represents patients with pre-existing dialysis-dependent kidney failure. CKD represents patients with pre-existing non-dialysisdependent CKD. No kidney dis represents patients without pre-existing kidney disease. Fine and Gray proportional subdistribution hazards models were used to estimate the association between the presence of pre-existing kidney disease (dialysis-dependent kidney failure and non-dialysis-dependent CKD, separately) vs. no pre-existing kidney disease and 14-day in-hospital outcomes. In mortality analyses, hospital discharge was treated as a competing event. In analyses of other outcomes both death and hospital discharge were treated as competing events. Analyses assessing mortality, respiratory failure, shock, and ventricular arrhythmia or cardiac arrest were adjusted for age, sex, race, Hispanic ethnicity, diabetes, hypertension, coronary artery disease, heart failure, and atrial fibrillation or flutter. Analyses evaluating thrombotic events, major bleeding, events, and acute liver injury were only adjusted for age, sex, race, Hispanic ethnicity only due to the low number of event counts.

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Values are n (%) for categorical variables and median

a Renal component of the SOFA score was based on serum creatinine levels. Patients who did not have a serum creatinine drawn on ICU day 1 were classified as having a renal SOFA score of 0, and patients on RRT were classified as having a renal SOFA score of 4