Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19

Abstract

Coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had devastating effects worldwide. Patients with kidney failure on dialysis may have a higher risk of worse outcomes. Reports from China found that these patients with SARS-CoV-2 had fewer symptoms and required less intensive care than expected (1). A recent observational study of hospitalized patients with kidney failure and COVID-19 reported 31% mortality (2). However, this study lacked a comparator group, and thus, it is unclear if this high mortality would be found in patients without kidney failure with a similarly high comorbidity burden. Therefore, we conducted this retrospective cohort study of patients with kidney failure hospitalized with COVID-19 in the Mount Sinai Health Care System (MSHS) and compared it with a propensity-matched cohort without kidney failure. Only patients age ≥18 years admitted between March 15 and June 7, 2020, with laboratory-confirmed SARS-CoV-2 within 48 hours of admission were included. Patients with kidney failure were identified by a combination of kidney failure diagnosis and dialysis procedure International Classificaton of Diseases codes. Patients with previous kidney transplants were not excluded if they had kidney failure at the time of study. The Mount Sinai Institutional Review Board approved this research. We propensity matched patients with kidney failure to those without kidney failure (1:5) without use of a caliper by age, sex, race/ethnicity, comorbidities (atrial fibrillation, coronary artery disease, cancer, congestive heart failure, diabetes, hypertension, chronic obstructive pulmonary disease, asthma, peripheral vascular disease, stroke, and liver disease), body mass index (kilograms per meter2), admission facility, and admission week using nearest neighbor matching. Despite propensity matching, significant differences in patient characteristics remained between kidney failure and non-kidney failure cohorts. Therefore, we performed logistic regression analysis after controlling for age, diabetes, hypertension, stroke, coronary artery disease, and congestive heart failure to determine the association between kidney failure and mechanical ventilation, intensive care unit (ICU) admission, and mortality. All analyses were performed using R 4.0.0 (R Foundation, Vienna, Austria). In total, 122 patients with kidney failure were admitted at MSHS with COVID-19 and matched to 610 patients without kidney failure with COVID-19 from a total of 3270 patients without kidney failure. Patients with kidney failure had a higher prevalence of diabetes (55% versus 43%, P=0.02) and hypertension (66% versus 55%, P=0.03). There were no significant differences in admission symptoms between patients with kidney failure and patients without kidney failure. Patients with kidney failure had higher systolic BP, lower heart rates, and higher oxygen saturation at admission. Patients with kidney failure had lower white blood cell counts (5.5 versus 7.1 103/μl, P<0.001) and higher inflammatory markers of ferritin (3174 versus 1041 ng/ml, P<0.001), erythrocyte sedimentation rate (84 versus 64 mm/h, P=0.001), and procalcitonin (3.4 versus 0.3 ng/ml, P<0.001) (Table 1). Table 1. - Clinical characteristics of patients admitted with coronavirus disease 2019 Patient Characteristics Patients without Kidney Failure Patients with Kidney Failure P Value N 610 122 Age, yr, median (IQR) 63.1 [52.0–74.0] 65.6 [53.9–71.2] 0.66 Sex, no. (%) Women 178 (29) 36 (30) 0.97 Men 432 (71) 86 (71) BMI (kg/m2), median (IQR) 26.9 [23.7–31.0] 26.4 [23.1–31.3] 0.38 Facility, n (%) Mount Sinai Brooklyn 109 (18) 23 (19) 0.44 Mount Sinai Hospital 241 (40) 42 (34) Mount Sinai Queens 165 (27) 41 (34) Mount Sinai Morningside 95 (16) 16 (13) Race/ethnicity, n (%) Asian 46 (8) 14 (12) 0.56 Black 249 (41) 51 (42) Hispanic/Latino 216 (35) 42 (34) Other 55 (9) 8 (7) White 44 (7) 7 (6) Comorbidities, no. (%) Atrial fibrillation 54 (9) 13 (11) 0.65 Asthma 50 (8) 10 (8) >0.99 Coronary artery disease 160 (26) 43 (35) 0.06 Cancer 29 (5) 5 (4) 0.94 Chronic obstructive pulmonary disease 30 (5) 6 (5) >0.99 Diabetes 263 (43) 67 (55) 0.02 Congestive heart failure 119 (20) 41 (34) 0.001 Hypertension 336 (55) 81 (66) 0.03 Stroke 47 (8) 15 (12) 0.14 Liver disease 37 (6) 8 (7) >0.99 Week of admission/infection, n (%) 03/15/2020–03/21/2020 47 (8) 11 (9) >0.99 03/22/2020–03/28/2020 154 (25) 30 (25) 03/29/2020–04/04/2020 164 (27) 32 (26) 04/05/2020–04/11/2020 124 (20) 25 (21) 04/12/2020–04/18/2020 87 (14) 17 (14) 04/19/2020–04/25/2020 34 (6) 7 (6) DNR/DNI, n (%) 106 (17) 19 (16) 0.73 Admission symptoms, n (%) Nausea/vomiting 109 (19) 25 (21) 0.66 Myalgias 82 (14) 9 (8) 0.07 Diarrhea 93 (16) 22 (18) 0.60 Fever 342 (58) 73 (61) 0.69 Cough/dyspnea 451 (77) 85 (71) 0.19 Admission vitals, median (IQR) Systolic BP, mm Hg 120 [105–133] 125 [108–145] 0.001 Diastolic BP, mm Hg 70 [61–77] 66 [58–76] 0.04 Temperature, °C 37.1 [36.7–37.8] 37.3 [36.8–37.9] 0.08 Heart rate, beats per minute 97 [85–110] 86 [77–100] <0.001 Pulse oximetry, % 95 [93–97] 96 [94–98] 0.002 Respiration rate, breaths per minute 20 [18–22] 20 [18–20] 0.55 Admission metabolic markers, median (IQR) Sodium, mEq/L 137 [134–140] 137 [135–139] 0.78 Chloride, mEq/L 102 [98–105] 95 [94–99] <0.001 Potassium, mEq/L 4.4 [4.0–4.8] 4.7 [4.2–5.4] <0.001 CO2, mEq/L 22 [19–25] 24 [21–27] <0.001 BUN, mg/dl 20 [13–37] 51 [35–73] <0.001 Creatinine, mg/dl 1.1 [0.8–1.9] 8.1 [5.8–10.3] <0.001 Glucose, mg/dl 128 [103–202] 107 [92–149] <0.001 Anion gap, mEq/L 13 [11–15] 16 [14–18] <0.001 Calcium, mEq/L 8.4 [8.1–8.9] 8.4 [7.9–8.9] 0.15 Admission hematologic markers, median (IQR) White blood cells, 103 μl 7.1 [5.4–10.1] 5.5 [4.3–7.4] <0.001 Hematocrit, % 40 [34–44] 32 [29–36] <0.001 Hemoglobin, g/dl 13.1 [11.4–14.6] 10.5 [9.4–11.9] <0.001 Neutrophil percentage 78 [70–85] 76 [69–83] 0.15 Lymphocyte percentage 13 [8–20] 14 [9–19] 0.55 Eosinophil percentage 0.2 [0.1–0.5] 0.3 [0.2–0.9] <0.001 Monocyte percentage 7 [5–10] 8 [6–10] 0.08 Platelets, 103 μl 200 [153–271] 156 [120–208] <0.001 Admission liver function tests, median (IQR) Aspartate transaminase, U/L 42 [27–64] 33 [24–48] <0.001 Alkaline phosphatase, U/L 79 [61–103] 93 [67–137] 0.004 Alanine transaminase, U/L 29 [18–50] 19 [13–30] <0.001 Total bilirubin, mg/dl 0.6 [0.4–0.9] 0.6 [0.5–0.7] 0.34 Direct bilirubin, mg/dla 0.3 [0.2–0.4] 0.3 [0.2–0.4] 0.11 Albumin, g/dl 3.3 [2.9–3.7] 3.3 [2.8–3.6] 0.38 Total protein, g/dl 7.1 [6.6–7.6] 7.0 [6.5–7.6] 0.97 Maximum inflammatory markers, median (IQR) C-reactive protein, mg/La 153 [80–250] 168 [86–276] 0.23 Ferritin, ng/mla 1041 [464–2556] 3174 [1866–6821] <0.001 d-dimer, ng/mla 2.5 [1.1–8.2] 2.9 [1.7–4.7] 0.66 Fibrinogen, mg/dla 666 [552–789] 589 [505–753] 0.05 IL-6, pg/mla 74 [39–202] 91 [29–206] 0.89 Lactate dehydrogenase, U/La 485 [348–692] 396 [309–548] 0.001 Erythrocyte sedimentation rate, mm/ha 64 [37–85] 84 [57–107] 0.001 Procalcitonin, ng/mla 0.3 [0.1–1.5] 3.4 [0.9–10.7] <0.001 Lactatea 1.6 [1.1–2.2] 1.4 [1.0–1.8] 0.001 Medication usage, n (%) Apixaban 113 (19) 45 (37) <0.001 Argatroban 3 (1) 0 >0.99 Heparin 57 (9) 11 (9) 0.96 Enoxaparin 115 (19) 0 <0.001 Azithromycin 414 (68) 61 (50) <0.001 Hydroxychloroquine 493 (81) 83 (68) 0.002 Tocilizumab 30 (5) 2 (2) 0.17 Clinical outcomes, n (%) Mechanical ventilation 103 (17) 13 (11) 0.11 ICU admission 129 (21) 11 (9) 0.003 Mortality 78 (13) 11 (9) 0.31 IQR, interquartile range; BMI, body mass index; DNR, do not resuscitate; DNI, do not intubate; CO2, carbon dioxide; ICU, intensive care unit.aIndicates missing in >10% of patients (ranging from 16% to 71%). Patients with kidney failure were less likely to receive mechanical ventilation (11% versus 17%, P=0.11) or be admitted to the ICU (9% versus 21%, P=0.003) and had similar in-hospital mortality (9% versus 12%, P=0.31). There was no difference in do not resuscitate/intubate orders (16% in patients with kidney failure versus 17% in patients without kidney failure, P=0.70). After further adjustments, kidney failure status was associated with lower odds of ICU admission (adjusted odds ratio [aOR], 0.37; 95% confidence interval [95% CI], 0.19 to 0.71), with similar direction of association for mechanical ventilation (aOR, 0.6; 95% CI, 0.32 to 1.11) and mortality (aOR, 0.67; 95% CI, 0.33 to 1.38). Patients with kidney failure have the highest hospital admission rates out of all Medicare beneficiaries. In this propensity-matched study, we found that although patients with kidney failure had higher comorbidity burden and higher inflammatory markers than patients without kidney failure, there were no significant differences in presenting symptoms and vital signs between patients with kidney failure and patients without kidney failure. Additionally, need for intensive care was lower in patients with kidney failure, and there was no difference in mechanical ventilation or in-hospital mortality. We report lower in-hospital mortality of patients with kidney failure than other institutions (27%–32%) (2(3–4). This is likely due to differences in baseline characteristics; patients with kidney failure who were admitted to MSHS had less diabetes and hypertension than other studies. Additionally, our study time had a longer follow-up period (3 months versus 1 month), and patients who were admitted later in the course of the pandemic may have received different treatments than patients who were admitted earlier. We found no statistically significant difference in in-hospital mortality between patients with kidney failure and propensity-matched patients without kidney failure who were matched on age and comorbidities. Additionally, there has been speculation that uremia-associated immune dysfunction may blunt the COVID-19 cytokine storm; however, this remains to be proven. Despite propensity matching, patients with kidney failure had more comorbidities and higher inflammatory markers of ferritin and procalcitonin, but they had lower odds of ICU transfer and similar risk for mechanical ventilation. This is in contrast to previous literature that documents the association of kidney failure status with adverse outcomes (5). Patients with kidney failure had a less severe COVID-19 phenotype with lower heart rate, lower white blood cell count, and higher oxygen saturation than patients without kidney failure. Differences in mechanical ventilation and ICU transfer were unlikely to be driven by code status differences given that the proportion of patients with do not resuscitate/do not intubate status was similar. Limitations include lack of data on the proportion of patients with kidney failure and COVID-19 who died out of hospital. Additionally, not all patients had inflammatory markers. Also, the use of propensity scores has inherent drawbacks, including the inability to adjust for unmeasured variables such as smoking status, which may bias patient selection and subsequent outcomes. In conclusion, this is the first study to compare in-hospital outcomes for COVID-19 in patients with kidney failure and matched patients without kidney failure. Although patients with kidney failure had higher inflammatory markers and higher comorbidity burden versus patients without, they had lower odds of mechanical ventilation and similar odds of intensive care use and in-hospital mortality. Disclosures E.P. Bottinger reports consultancy agreements with Deloitte and Roland Berger; ownership interest in Digital Medicine E.Böttinger GmbH, EBCW GmbH, and Ontomics, Inc.; receiving honoraria from Bayer, Bosch Health Campus, Sanofi, and Siemens; and serving as a scientific advisor or member of Bosch Health Campus and Seer Biosciences Inc. L. Chan reports receiving research funding from the National Institutes of Health (R01AG066471) and consulting fees from GLG consulting, outside the submitted work. S.G. Coca reports employment with Icahn School of Medicine at Mount Sinai (Mount Sinai owns part of Renalytix AI); consultancy agreements with Akebia, Bayer, Boehringer Ingelheim, CHF Solutions, Goldfinch Bio, inRegen, Quark, Relypsa, Renalytix AI, and Takeda; ownership interest in pulseData and Renalytix AI; receiving research funding from inRegen and Renalytix AI; patents and inventions with Renalytix AI; serving as a scientific advisor or member of Renalytix AI; and serving as an associate editor for Kidney360 and on the editorial board for JASN, CJASN, and Kidney International. S.G. Coca is supported by the following grants: U01DK106962, R01DK115562, R01HL085757, U01OH011326, R01DK112258, and RRTI UG 2019. Z.A. Fayad reports consultancy agreements and ownership interest in Trained Therapeutix Discovery; receiving research funding from the National Institutes of Health; patents and inventions with Trained Therapeutix Discovery; and serving as a scientific advisor or member of Trained Therapeutix Discovery. J. He reports consultancy agreements and ownership interest in Renalytix AI; receiving research funding from Shangpharma Innovation; receiving honoraria from Otsuka; and serving as a scientific advisor or member of the editorial board for Kidney International and JASN, a board member of the Chinese American Society of Nephrology and the International Chinese Society of Nephrology, an associate editor for Kidney Disease, and a section editor for Nephron. B. Murphy reports consultancy agreements with Regeneron and Renalytix AI; ownership interest in Renalytix AI; receiving research funding from the National Institutes of Health; patents and inventions with Fractal Dx; serving on the advisory board for ITBmed, as a board member of Renalytix AI, on the scientific advisory board for Veloxis, and on the advisory board for Vertex; and other interests/relationships with DSMBHansa–DSMB. She is a nonexecutive director of Renalytix AI. G.N. Nadkarni reports employment with, consultancy agreements with, and ownership interest in Pensieve Health and Renalytix AI; receiving consulting fees from AstraZeneca, BioVie, GLG Consulting, and Reata; and serving as a scientific advisor or member of Pensieve Health and Renalytix AI. G.N. Nadkarni is supported by a career development award from the National Institute of Diabetes and Digestive and Kidney Diseases (K23DK107908) and is also supported by R01DK108803, U01HG007278, U01HG009610, and U01DK116100. S. Somani reports consultancy agreements and ownership interest in Monogram Orthopedics. All remaining authors have nothing to disclose. Funding This study received support from National Institute of Diabetes and Digestive and Kidney Diseases grant K23DK107908.

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